vision model

minor fix
fix: CWE-119
2026-08-03 01:26:42 +07:00 · 2026-08-03 01:25:02 +07:00 · 2026-07-16 03:46:24 +03:00 · 2026-07-16 03:21:17 +03:00 · 2026-07-16 03:20:26 +03:00 · 2026-07-16 03:18:20 +03:00
65 changed files with 15714 additions and 0 deletions
--- a/3d_models/.gitignore
+++ b/3d_models/.gitignore
@@ -0,0 +1,2 @@
+*.FCBak
+/export
--- a/3d_models/conveer.FCStd
+++ b/3d_models/conveer.FCStd
--- a/README.md
+++ b/README.md
@@ -0,0 +1,49 @@
+# Структура репозитория:
+
+```
+├── arduino_code
+│   └── Test
+│       ├── include
+│       ├── lib
+│       ├── platformio.ini
+│       ├── src
+│       └── test
+├── backend_control
+│   ├── create_venv.sh
+│   ├── main.py
+│   └── testing
+│       ├── bin
+│       ├── include
+│       ├── lib
+│       ├── lib64 -> lib
+│       └── pyvenv.cfg
+├── kicad
+│   └── ozon
+│       ├── ozon.kicad_pcb
+│       ├── ozon.kicad_pro
+│       ├── ozon.kicad_sch
+│       └── ~ozon.kicad_sch.lck
+├── README.md
+└── specification
+    ├── mindmap.md
+    ├── mvp_1.drawio
+    ├── mvp_1.jpg
+    ├── mvp_1.md
+    └── specification.md
+```
+
+## Папка arduino_code
+
+Тут находится код для контроллера
+
+## Папка Backend_control
+
+Тут находится простой python скрипт для управления шагововым двигателем по средствам последовательных команд.
+
+## Папка kicad 
+
+Тут будут находится электрические схемы проекта
+
+## Папка specification
+
+В этой папке разрабатывается спецификация на проект
--- a/arduino_code/Test/.gitignore
+++ b/arduino_code/Test/.gitignore
@@ -0,0 +1,5 @@
+.pio
+.vscode/.browse.c_cpp.db*
+.vscode/c_cpp_properties.json
+.vscode/launch.json
+.vscode/ipch
--- a/arduino_code/Test/.vscode/extensions.json
+++ b/arduino_code/Test/.vscode/extensions.json
@@ -0,0 +1,10 @@
+{
+    // See http://go.microsoft.com/fwlink/?LinkId=827846
+    // for the documentation about the extensions.json format
+    "recommendations": [
+        "platformio.platformio-ide"
+    ],
+    "unwantedRecommendations": [
+        "ms-vscode.cpptools-extension-pack"
+    ]
+}
--- a/arduino_code/Test/README.md
+++ b/arduino_code/Test/README.md
@@ -0,0 +1,95 @@
+# 📡 Документация по MQTT интерфейсу (ESP32 + TMC2209 + Servo + VL53L0X)
+
+## 📌 Общая информация
+- **Архитектура**: ESP32 (FreeRTOS задача `mqttTask`).
+- **Период опроса телеметрии**: 500 мс.
+- **Оптимизация трафика**: 
+  1. Публикация данных происходит **только при изменении значения** (строгое кэширование).
+  2. Используется статический буфер (`intToString`/`uintToString`) вместо динамического класса `String` для экономии памяти и предотвращения фрагментации кучи.
+- **Префиксы**: 
+  - `.../control/...` — топики для **отправки команд** устройству (подписка).
+  - `.../feedback/...` — топики для **получения статуса/телеметрии** от устройства (публикация).
+
+---
+
+## ⚙️ 1. Управление шаговым двигателем (Motor Control)
+
+| Топик | Тип данных | Описание | Пример Payload |
+| :--- | :---: | :--- | :--- |
+| `motor/control/rpm` | Integer | Целевая скорость в об/мин (RPM). Отрицательные значения включают реверс. | `-150`, `0`, `300` |
+| `motor/control/driver` | String | Аппаратное вкл/выкл драйвера (пин `EN_PIN`). `on` = LOW (вкл), иначе = HIGH (выкл). | `on`, `off` |
+| `motor/control/totalsteps/reset`| Any | Сброс счетчика шагов в ноль. Устройство сразу опубликует `"0"` в feedback. | `1`, `reset` |
+
+### Телеметрия двигателя (Motor Feedback)
+*(Публикуется только при изменении)*
+- `motor/feedback/rpm` (Integer): Текущая скорость.
+- `motor/feedback/totalsteps` (Integer): Общее количество шагов.
+- `motor/feedback/is_run` (String: `true`/`false`): Двигатель движется.
+- `motor/feedback/driver/status` (String: `on`/`off`): Общий статус драйвера.
+- `motor/feedback/tmc/status` (String: `on`/`off`): Статус программного включения TMC.
+
+#### Детальная телеметрия TMC2209 (`motor/feedback/tmc/...`)
+- `current_percent` (Integer): Текущий % рабочего тока.
+- `microsteps` (Integer): Текущий режим микрошага.
+- `sg_result` (Integer): Текущее значение StallGuard (нагрузка).
+- `interstep_duration` (Integer): Длительность между шагами.
+- `status/over_temp` (String: `true`/`false`): Перегрев.
+- `status/short_to_ground` (String: `true`/`false`): КЗ на землю.
+- `status/open_load` (String: `true`/`false`): Обрыв нагрузки.
+- `status/stealth_chop_active` (String: `true`/`false`): Активен ли StealthChop.
+- `status/standstill` (String: `true`/`false`): Двигатель в покое.
+- `status/current_scaling` (Integer): Внутренний масштабный коэффициент тока.
+
+---
+
+## 🦾 2. Управление сервоприводами (Servo Control)
+
+Поддержка нескольких каналов (`{channel}` от `0` до `MAX_SERVOS - 1`).
+
+### Команды
+| Топик (пример для канала 0) | Тип данных | Описание | Пример Payload |
+| :--- | :---: | :--- | :--- |
+| `servo/control/0/angle` | Integer (0-180) | Установить угол поворота. | `90` |
+| `servo/control/0/enable` | String | Включить (`on`, `1`, `true`) или выключить. | `on` |
+
+### Обратная связь
+- `servo/0/feedback/status` (String: `on`/`off`): Статус питания сервопривода.
+- `servo/0/feedback/angle` (Integer): Текущий установленный угол.
+
+---
+
+## 📏 3. Управление датчиками VL53L0X (Sensor Control) **(НОВОЕ)**
+
+Поддержка до 8 каналов (`VL53L0X_MAX_CHANNELS = 8`). Топики используют параметр `{channel}` (0–7).
+
+| Топик | Тип данных | Описание | Пример Payload |
+| :--- | :---: | :--- | :--- |
+| `sensor/control/mode` | Integer | Установка глобального режима измерения (0 до `MODE_COUNT - 1`). | `0`, `1` |
+| `sensor/control/mode_name` | String | *Заглушка/Логирование.* Принимает имя режима для отладки. | `LongRange` |
+| `sensor/control/calibrate/start/{ch}`| Integer | Начало калибровки: указать близкое расстояние в мм. | `50` |
+| `sensor/control/calibrate/finish/{ch}`| Integer | Завершение калибровки: указать дальнее расстояние в мм. | `500` |
+| `sensor/control/clear_cal/{ch}` | Any | Сбросить калибровку для указанного канала. | `1` |
+| `sensor/control/enable/{ch}` | String | Включить (`on`, `1`, `true`) или выключить конкретный канал. | `on` |
+| `sensor/control/publish_all` | Any | **Принудительный сброс кэша.** Заставляет устройство немедленно опубликовать текущие значения всех датчиков, даже если они не изменились. | `1` |
+
+---
+
+## 📊 4. Телеметрия датчиков VL53L0X (Sensor Feedback) **(НОВОЕ)**
+
+### Глобальная информация о режиме
+Публикуется только при смене режима измерения:
+- `sensor/feedback/mode` (String): Человекочитаемое имя текущего режима (например, "Default", "LongRange").
+- `sensor/feedback/mode_id` (Integer): Числовой ID текущего режима.
+- `sensor/feedback/max_range` (Integer): Максимальная дальность для текущего режима (в мм).
+
+### Постатусная информация по каналам (`{channel}` = 0..7)
+*(Публикуется только при изменении состояния или значения)*
+
+| Топик (пример для канала 0) | Тип данных | Описание |
+| :--- | :---: | :--- |
+| `sensor/feedback/0/status` | String (`on`/`off`) | Включен ли логически данный канал. |
+| `sensor/feedback/0/calibrated` | String (`true`/`false`)| Была ли проведена калибровка для этого канала. |
+| `sensor/feedback/0/distance` | Integer или String | **Калиброванное** расстояние в мм. Если значение `65535` (ошибка/вне диапазона), публикуется строка `"out_of_range"`. |
+| `sensor/feedback/0/raw` | Integer | **Сырое** (некалиброванное) значение расстояния в мм. |
+
+*Примечание: Топики `distance` и `raw` публикуются только если канал активен (`vl53l0xIsChannelActive`).*
--- a/arduino_code/Test/include/README
+++ b/arduino_code/Test/include/README
@@ -0,0 +1,37 @@
+
+This directory is intended for project header files.
+
+A header file is a file containing C declarations and macro definitions
+to be shared between several project source files. You request the use of a
+header file in your project source file (C, C++, etc) located in `src` folder
+by including it, with the C preprocessing directive `#include'.
+
+```src/main.c
+
+#include "header.h"
+
+int main (void)
+{
+ ...
+}
+```
+
+Including a header file produces the same results as copying the header file
+into each source file that needs it. Such copying would be time-consuming
+and error-prone. With a header file, the related declarations appear
+in only one place. If they need to be changed, they can be changed in one
+place, and programs that include the header file will automatically use the
+new version when next recompiled. The header file eliminates the labor of
+finding and changing all the copies as well as the risk that a failure to
+find one copy will result in inconsistencies within a program.
+
+In C, the convention is to give header files names that end with `.h'.
+
+Read more about using header files in official GCC documentation:
+
+* Include Syntax
+* Include Operation
+* Once-Only Headers
+* Computed Includes
+
+https://gcc.gnu.org/onlinedocs/cpp/Header-Files.html
--- a/arduino_code/Test/lib/README
+++ b/arduino_code/Test/lib/README
@@ -0,0 +1,46 @@
+
+This directory is intended for project specific (private) libraries.
+PlatformIO will compile them to static libraries and link into the executable file.
+
+The source code of each library should be placed in a separate directory
+("lib/your_library_name/[Code]").
+
+For example, see the structure of the following example libraries `Foo` and `Bar`:
+
+|--lib
+|  |
+|  |--Bar
+|  |  |--docs
+|  |  |--examples
+|  |  |--src
+|  |     |- Bar.c
+|  |     |- Bar.h
+|  |  |- library.json (optional. for custom build options, etc) https://docs.platformio.org/page/librarymanager/config.html
+|  |
+|  |--Foo
+|  |  |- Foo.c
+|  |  |- Foo.h
+|  |
+|  |- README --> THIS FILE
+|
+|- platformio.ini
+|--src
+   |- main.c
+
+Example contents of `src/main.c` using Foo and Bar:
+```
+#include <Foo.h>
+#include <Bar.h>
+
+int main (void)
+{
+  ...
+}
+
+```
+
+The PlatformIO Library Dependency Finder will find automatically dependent
+libraries by scanning project source files.
+
+More information about PlatformIO Library Dependency Finder
+- https://docs.platformio.org/page/librarymanager/ldf.html
--- a/arduino_code/Test/platformio.ini
+++ b/arduino_code/Test/platformio.ini
@@ -0,0 +1,28 @@
+; PlatformIO Project Configuration File
+;
+;   Build options: build flags, source filter
+;   Upload options: custom upload port, speed and extra flags
+;   Library options: dependencies, extra library storages
+;   Advanced options: extra scripting
+;
+; Please visit documentation for the other options and examples
+; https://docs.platformio.org/page/projectconf.html
+
+[env:upesy_wroom]
+platform = espressif32
+board = upesy_wroom
+framework = arduino
+monitor_speed = 115200
+upload_speed = 921600
+upload_port = /dev/ttyUSB0
+lib_deps = 
+	knolleary/PubSubClient@^2.8
+	janelia-arduino/TMC2209@^9.4.0
+	madhephaestus/ESP32Servo@^3.2.1
+	adafruit/Adafruit PWM Servo Driver Library@^3.0.3
+	pololu/VL53L0X@^1.3.1
+build_flags = 
+	-Os
+	-ffunction-sections
+	-fdata-sections
+	-Wl,--gc-sections
--- a/arduino_code/Test/src/config.cpp
+++ b/arduino_code/Test/src/config.cpp
@@ -0,0 +1,38 @@
+#include "config.h"
+
+const char* WIFI_SSID = "Home";
+const char* WIFI_PASS = "88888888qwE";
+const char* MQTT_SERVER = "192.168.31.225";
+const int MQTT_PORT = 1883;
+const char* MQTT_USER = "test";
+const char* MQTT_PASS = "1234";
+const char* MQTT_CLIENT_ID = "ESP32_Stepper";
+
+// UART2: RX=16, TX=17
+HardwareSerial& TMC_SERIAL = Serial2;
+const uint32_t TMC_BAUD_RATE = 115200;
+const uint8_t TMC_SERIAL_ADDRESS = 0; // Если MS1 и MS2 на GND
+
+const int16_t TMC_RX_PIN = 16;
+const int16_t TMC_TX_PIN = 17;
+const int EN_PIN = 18;
+
+const int STEPS_PER_REVOLUTION = 200;
+const unsigned long RAMP_DURATION_MS = 2000;
+
+// Ток задается в процентах от максимума (зависит от R_sense). 
+// Для R_sense=0.11 Ом, 100% ~ 1.77А RMS. Для R_sense=0.15 Ом, 100% ~ 1.2А RMS.
+const uint8_t TMC_RUN_CURRENT_PERCENT = 50;   // 50% тока при движении
+const uint8_t TMC_HOLD_CURRENT_PERCENT = 20;  // 20% тока в простое
+const uint8_t TMC_STALL_GUARD_THRESH = 10;    
+const uint16_t TMC_MICROSTEPS = 1;           
+
+// I2C Настройка
+const int16_t I2C_SDA_PIN = 21;
+const int16_t I2C_SCL_PIN = 22;
+
+
+// ========== SERVO CONFIGURATION ==========
+#define SERVO_DEFAULT_CHANNEL 0
+#define SERVO_MIN_ANGLE 0
+#define SERVO_MAX_ANGLE 180
--- a/arduino_code/Test/src/config.h
+++ b/arduino_code/Test/src/config.h
@@ -0,0 +1,38 @@
+#ifndef CONFIG_H
+#define CONFIG_H
+
+#include <stdint.h>
+#include <Arduino.h>
+
+// WiFi & MQTT
+extern const char* WIFI_SSID;
+extern const char* WIFI_PASS;
+extern const char* MQTT_SERVER;
+extern const int MQTT_PORT;
+extern const char* MQTT_USER;
+extern const char* MQTT_PASS;
+extern const char* MQTT_CLIENT_ID;
+
+// UART for TMC2209
+extern HardwareSerial& TMC_SERIAL;
+extern const uint32_t TMC_BAUD_RATE;
+extern const uint8_t TMC_SERIAL_ADDRESS; // Адрес драйвера (0-3)
+extern const int16_t TMC_RX_PIN;
+extern const int16_t TMC_TX_PIN;
+extern const int EN_PIN;
+
+// Motor Params
+extern const int STEPS_PER_REVOLUTION; // Базовые шаги мотора (обычно 200)
+extern const unsigned long RAMP_DURATION_MS;
+
+// TMC2209 Defaults (Токи в процентах 0-100%)
+extern const uint8_t TMC_RUN_CURRENT_PERCENT;   
+extern const uint8_t TMC_HOLD_CURRENT_PERCENT;  
+extern const uint8_t TMC_STALL_GUARD_THRESH;    
+extern const uint16_t TMC_MICROSTEPS;          
+
+// I2C Настройка
+extern const int16_t I2C_SDA_PIN;
+extern const int16_t I2C_SCL_PIN;
+
+#endif
--- a/arduino_code/Test/src/main.cpp
+++ b/arduino_code/Test/src/main.cpp
@@ -0,0 +1,42 @@
+#include <Arduino.h>
+#include <TMC2209.h>
+#include "config.h"
+#include "motor.h"
+#include "vl53l0x_sensor.h"
+#include "mqtt_handler.h"
+
+void setup() {
+    Serial.begin(115200);
+    
+    // Инициализация мотора (Core 1 context initially)
+    motorInit();
+
+    xTaskCreatePinnedToCore(
+        sensorTask, 
+        "SensorTask", 
+        4096, 
+        NULL, 
+        1, 
+        NULL, 
+        0
+    );
+
+    // Запуск задачи MQTT на Core 0
+    xTaskCreatePinnedToCore(
+        mqttTask,
+        "MQTT_Task",
+        20480,
+        NULL,
+        3,
+        NULL,
+        0 // CORE 0
+    );
+
+    Serial.println("System Initialized. Multi-core ready.");
+}
+
+void loop() {
+    // Loop выполняется на Core 1
+    motorLoop();
+    vTaskDelay(pdMS_TO_TICKS(5));
+}
--- a/arduino_code/Test/src/motor.cpp
+++ b/arduino_code/Test/src/motor.cpp
@@ -0,0 +1,295 @@
+#include "motor.h"
+#include "config.h"
+
+static TMC2209 stepper_driver;
+static bool tmc_initialized = false;
+static SemaphoreHandle_t tmc_uart_mutex = NULL;
+
+volatile unsigned long total_steps = 0;
+static int target_rpm = 0;
+static int current_rpm_display = 0;
+
+static bool is_ramping = false;
+static unsigned long ramp_start_ms = 0;
+static float start_speed_sps = 0;
+static float end_speed_sps = 0;
+static float current_speed_sps = 0;
+static int32_t last_vactual = 0;
+static bool velocity_sent = false; // Флаг для отправки хотя бы раз
+
+static uint16_t current_microsteps = TMC_MICROSTEPS;
+static uint8_t current_run_percent = TMC_RUN_CURRENT_PERCENT;
+
+#define TMC_LOCK() xSemaphoreTake(tmc_uart_mutex, portMAX_DELAY)
+#define TMC_UNLOCK() xSemaphoreGive(tmc_uart_mutex)
+
+const float TMC_FCLK = 12800000.0;
+const float VACTUAL_FACTOR = 8388608.0 / TMC_FCLK;
+
+int32_t calculateVActual(float microsteps_per_second) {
+    return (int32_t)(microsteps_per_second * VACTUAL_FACTOR);
+}
+
+void motorInit() {
+    pinMode(EN_PIN, OUTPUT);
+    digitalWrite(EN_PIN, LOW);
+    tmc_uart_mutex = xSemaphoreCreateMutex();
+
+    TMC_SERIAL.begin(TMC_BAUD_RATE, SERIAL_8N1, TMC_RX_PIN, TMC_TX_PIN);
+    delay(500);
+    
+    TMC_LOCK();
+    
+    stepper_driver.setup(TMC_SERIAL, TMC_BAUD_RATE, 
+                        (TMC2209::SerialAddress)TMC_SERIAL_ADDRESS, 
+                        TMC_RX_PIN, TMC_TX_PIN);
+    
+    delay(200);
+    
+    // Проверка связи
+    if (!stepper_driver.isCommunicating()) {
+        Serial.println("ERROR: TMC2209 not communicating!");
+        TMC_UNLOCK();
+        tmc_initialized = false;
+        return;
+    }
+    
+    Serial.println("TMC2209 communicating OK");
+    
+    // Базовая настройка
+    stepper_driver.setMicrostepsPerStep(TMC_MICROSTEPS);
+    stepper_driver.setRunCurrent(TMC_RUN_CURRENT_PERCENT);
+    stepper_driver.setHoldCurrent(TMC_HOLD_CURRENT_PERCENT);
+    stepper_driver.setHoldDelay(7);
+    stepper_driver.setStallGuardThreshold(TMC_STALL_GUARD_THRESH);
+    
+    stepper_driver.enableAutomaticCurrentScaling();
+    stepper_driver.enableAutomaticGradientAdaptation();
+    
+    // КРИТИЧНО: Отключаем StealthChop для работы moveAtVelocity()!
+    stepper_driver.disableStealthChop();
+    delay(10);
+    
+    // Включаем CoolStep для энергосбережения
+    stepper_driver.enableCoolStep();
+    
+    // Программное включение драйвера
+    stepper_driver.enable();
+    delay(100);
+    
+    tmc_initialized = stepper_driver.isSetupAndCommunicating();
+    
+    if (tmc_initialized) {
+        Serial.println("TMC2209 initialized successfully");
+        TMC2209::Settings settings = stepper_driver.getSettings();
+        Serial.printf("Run: %d%%, Hold: %d%%, Microsteps: %d, StealthChop: %s\n", 
+            settings.irun_percent, settings.ihold_percent, 
+            settings.microsteps_per_step, settings.stealth_chop_enabled ? "ON" : "OFF");
+    } else {
+        Serial.println("ERROR: TMC2209 setup failed!");
+    }
+    
+    TMC_UNLOCK();
+
+    current_microsteps = TMC_MICROSTEPS;
+    current_run_percent = TMC_RUN_CURRENT_PERCENT;
+}
+
+void motorLoop() {
+    if (is_ramping) {
+        unsigned long now = millis();
+        unsigned long elapsed = now - ramp_start_ms;
+
+        if (elapsed >= RAMP_DURATION_MS) {
+            is_ramping = false;
+            current_speed_sps = end_speed_sps;
+        } else {
+            float progress = (float)elapsed / RAMP_DURATION_MS;
+            current_speed_sps = start_speed_sps + (end_speed_sps - start_speed_sps) * progress;
+        }
+
+        int32_t vactual = calculateVActual(current_speed_sps);
+        
+        // Отправляем если: скорость изменилась ИЛИ это первая отправка в рампе
+        if (abs(vactual - last_vactual) >= 0 || !velocity_sent) {
+            TMC_LOCK();
+            stepper_driver.moveAtVelocity(vactual);
+            TMC_UNLOCK();
+            last_vactual = vactual;
+            velocity_sent = true;
+            
+            Serial.printf("VACTUAL: %d (SPS: %.1f, RPM: %d)\n", 
+                vactual, current_speed_sps, current_rpm_display);
+        }
+
+        unsigned long steps_per_rev = (unsigned long)STEPS_PER_REVOLUTION * current_microsteps;
+        current_rpm_display = ((unsigned long)abs(current_speed_sps) * 60) / steps_per_rev;
+    } else if (!velocity_sent && current_speed_sps == 0) {
+        // Если мотор стоит и скорость не отправлялась - отправляем 0
+        TMC_LOCK();
+        stepper_driver.moveAtVelocity(0);
+        TMC_UNLOCK();
+        velocity_sent = true;
+    }
+    if (current_speed_sps != 0) {
+            total_steps += (unsigned long)(abs(current_speed_sps) * 0.005);
+    }
+    
+    vTaskDelay(pdMS_TO_TICKS(5));
+}
+
+void setTargetRPM(int rpm) {
+    target_rpm = rpm;
+    if (rpm != 0 && current_rpm_display < 5) resetSteps();
+
+    unsigned long steps_per_rev = (unsigned long)STEPS_PER_REVOLUTION * current_microsteps;
+    
+    start_speed_sps = current_speed_sps;
+    end_speed_sps = (rpm != 0) ? ((float)rpm * steps_per_rev) / 60.0f : 0;
+
+    ramp_start_ms = millis();
+    is_ramping = true;
+    velocity_sent = false; // Сбрасываем флаг для новой отправки
+    
+    Serial.printf("Target RPM: %d -> SPS: %.1f\n", rpm, end_speed_sps);
+}
+
+void resetSteps() {
+    total_steps = 0;
+}
+
+unsigned long getMotorSteps() { return total_steps; }
+int getCurrentRPM() { return current_rpm_display; }
+bool isMotorRunning() { return (abs(current_speed_sps) > 1); }
+
+void tmcSetCurrentPercent(uint8_t run_percent, uint8_t hold_percent) {
+    if (!tmc_initialized) return;
+    TMC_LOCK();
+    stepper_driver.setAllCurrentValues(run_percent, hold_percent, 7);
+    TMC_UNLOCK();
+    current_run_percent = run_percent;
+}
+
+void tmcSetMicrosteps(uint16_t ms) {
+    if (!tmc_initialized) return;
+    TMC_LOCK();
+    stepper_driver.setMicrostepsPerStep(ms);
+    TMC_UNLOCK();
+    current_microsteps = ms;
+    if (target_rpm != 0) setTargetRPM(target_rpm);
+}
+
+void tmcSetStallGuard(uint8_t threshold) {
+    if (!tmc_initialized) return;
+    TMC_LOCK();
+    stepper_driver.setStallGuardThreshold(threshold);
+    TMC_UNLOCK();
+}
+
+void tmcSoftwareEnable(bool enable) {
+    if (!tmc_initialized) return;
+    TMC_LOCK();
+    if (enable) {
+        stepper_driver.enable();
+        // После enable нужно заново отправить скорость
+        velocity_sent = false;
+    } else {
+        stepper_driver.moveAtVelocity(0);
+        stepper_driver.disable();
+        last_vactual = 0;
+        current_speed_sps = 0;
+        is_ramping = false;
+    }
+    TMC_UNLOCK();
+}
+
+void tmcSetStealthChop(bool enable) {
+    if (!tmc_initialized) return;
+    TMC_LOCK();
+    if (enable) {
+        stepper_driver.enableStealthChop();
+        // В StealthChop VACTUAL не работает, останавливаем мотор
+        stepper_driver.moveAtVelocity(0);
+        last_vactual = 0;
+        current_speed_sps = 0;
+    } else {
+        stepper_driver.disableStealthChop();
+        velocity_sent = false;
+    }
+    TMC_UNLOCK();
+}
+
+void tmcSetCoolStep(bool enable) {
+    if (!tmc_initialized) return;
+    TMC_LOCK();
+    enable ? stepper_driver.enableCoolStep() : stepper_driver.disableCoolStep();
+    TMC_UNLOCK();
+}
+
+bool tmcIsInitialized() { return tmc_initialized; }
+
+bool tmcIsCommunicating() {
+    if (!tmc_initialized) return false;
+    TMC_LOCK();
+    bool res = stepper_driver.isCommunicating();
+    TMC_UNLOCK();
+    return res;
+}
+
+// Функция проверки состояния EN_PIN
+bool checkDriverStatus() {
+    bool en_state = (digitalRead(EN_PIN) == LOW);
+    return en_state;
+}
+
+// Функция проверки программного состояния TMC
+bool checkTmcSoftwareEnable() {
+    TMC2209::Settings s = tmcGetSettings();
+    bool tmc_state = s.software_enabled;
+    return tmc_state;
+}
+
+uint16_t tmcGetMicrostepsSetting() { return current_microsteps; }
+uint8_t tmcGetRunCurrentPercent() { return current_run_percent; }
+
+TMC2209::Status tmcGetStatus() {
+    TMC2209::Status s = {};
+    if (!tmc_initialized) return s;
+    TMC_LOCK();
+    s = stepper_driver.getStatus();
+    TMC_UNLOCK();
+    return s;
+}
+
+TMC2209::Settings tmcGetSettings() {
+    TMC2209::Settings s = {};
+    if (!tmc_initialized) return s;
+    TMC_LOCK();
+    s = stepper_driver.getSettings();
+    TMC_UNLOCK();
+    return s;
+}
+
+uint16_t tmcGetStallGuardResult() {
+    if (!tmc_initialized) return 0;
+    TMC_LOCK();
+    uint16_t res = stepper_driver.getStallGuardResult();
+    TMC_UNLOCK();
+    return res;
+}
+
+uint32_t tmcGetInterstepDuration() {
+    if (!tmc_initialized) return 0;
+    TMC_LOCK();
+    uint32_t res = stepper_driver.getInterstepDuration();
+    TMC_UNLOCK();
+    return res;
+}
+
+uint16_t tmcGetMicrostepCounter() {
+    if (!tmc_initialized) return 0;
+    TMC_LOCK();
+    uint16_t res = stepper_driver.getMicrostepCounter();
+    TMC_UNLOCK();
+    return res;
+}
--- a/arduino_code/Test/src/motor.h
+++ b/arduino_code/Test/src/motor.h
@@ -0,0 +1,42 @@
+#ifndef MOTOR_H
+#define MOTOR_H
+
+#include <Arduino.h>
+#include <TMC2209.h>
+
+void motorInit();
+void motorLoop();
+
+// Управление движением (через UART VACTUAL)
+void setTargetRPM(int rpm); // Поддерживает отрицательные значения для реверса!
+void resetSteps();
+
+// Геттеры состояния движения
+unsigned long getMotorSteps(); // Считается программно
+int getCurrentRPM();
+bool isMotorRunning();
+
+// Управление TMC2209 через UART
+void tmcSetCurrentPercent(uint8_t run_percent, uint8_t hold_percent);
+void tmcSetMicrosteps(uint16_t ms);
+void tmcSetStallGuard(uint8_t threshold);
+void tmcSoftwareEnable(bool enable); // Вкл/Выкл драйвер программно
+void tmcSetStealthChop(bool enable);
+void tmcSetCoolStep(bool enable);
+
+// Расширенная телеметрия
+bool tmcIsInitialized();
+bool tmcIsCommunicating();
+uint16_t tmcGetMicrostepsSetting();
+uint8_t tmcGetRunCurrentPercent();
+
+// Структуры статусов для MQTT
+TMC2209::Status tmcGetStatus();
+TMC2209::Settings tmcGetSettings();
+uint16_t tmcGetStallGuardResult();
+uint32_t tmcGetInterstepDuration();
+uint16_t tmcGetMicrostepCounter();
+bool checkDriverStatus();
+bool checkTmcSoftwareEnable();
+
+#endif
--- a/arduino_code/Test/src/mqtt_handler.cpp
+++ b/arduino_code/Test/src/mqtt_handler.cpp
@@ -0,0 +1,506 @@
+#include "mqtt_handler.h"
+#include "config.h"
+#include "motor.h"
+#include "servo_control.h"
+#include "vl53l0x_sensor.h"
+
+static WiFiClient espClient;
+static PubSubClient client(espClient);
+
+// Кэш телеметрии
+static unsigned long last_feedback_time = 0;
+static int last_pub_rpm = -1;
+static unsigned long last_pub_steps = -1;
+static int last_pub_is_run = -1;
+
+// TMC Кэш
+static uint16_t last_pub_sg = 65535;
+static uint32_t last_pub_interstep = 0;
+static uint8_t last_pub_current_pct = 255;
+static uint16_t last_pub_microsteps = 0;
+
+// Статусы (битовые флаги)
+static int last_pub_over_temp = -1;
+static int last_pub_short_gnd = -1;
+static int last_pub_open_load = -1;
+static int last_pub_stealth_active = -1;
+static int last_pub_standstill = -1;
+static int last_pub_driver_status = -1;
+static int last_pub_tmc_software_enable = -1;
+static uint8_t last_pub_current_scaling = 255;
+
+// ============================================
+// КЭШИРОВАНИЕ ДЛЯ VL53L0X
+// ============================================
+
+#define VL53L0X_MAX_CHANNELS 8
+static uint16_t last_pub_vl53_distance[VL53L0X_MAX_CHANNELS] = {65535};
+static uint16_t last_pub_vl53_raw[VL53L0X_MAX_CHANNELS] = {65535};
+static int last_pub_vl53_status[VL53L0X_MAX_CHANNELS] = {-1};
+static int last_pub_vl53_calibrated[VL53L0X_MAX_CHANNELS] = {-1};
+static MeasurementMode last_pub_vl53_mode = MODE_COUNT;
+
+// ============================================
+// БУФЕРЫ ДЛЯ ПРЕОБРАЗОВАНИЯ
+// ============================================
+
+static char int_buffer[16];
+static char uint_buffer[16];
+
+static const char* intToString(int value) {
+    snprintf(int_buffer, sizeof(int_buffer), "%d", value);
+    return int_buffer;
+}
+
+static const char* uintToString(unsigned long value) {
+    snprintf(uint_buffer, sizeof(uint_buffer), "%lu", value);
+    return uint_buffer;
+}
+
+// ============================================
+// WIFI И MQTT ПОДКЛЮЧЕНИЕ
+// ============================================
+
+static void setup_wifi() {
+    Serial.print("Connecting to WiFi");
+    WiFi.begin(WIFI_SSID, WIFI_PASS);
+    while (WiFi.status() != WL_CONNECTED) { 
+        vTaskDelay(pdMS_TO_TICKS(500)); 
+        Serial.print("."); 
+    }
+    Serial.println("\nWiFi Connected");
+}
+
+static void resetAllCaches() {
+    // Motor
+    last_pub_rpm = -1; 
+    last_pub_steps = (unsigned long)-1; 
+    last_pub_is_run = -1;
+    last_pub_sg = 65535; 
+    last_pub_interstep = 0; 
+    last_pub_current_pct = 255;
+    last_pub_microsteps = 0; 
+    last_pub_over_temp = -1; 
+    last_pub_short_gnd = -1;
+    last_pub_open_load = -1; 
+    last_pub_stealth_active = -1; 
+    last_pub_standstill = -1;
+    last_pub_current_scaling = 255;
+    last_pub_driver_status = -1;
+    last_pub_tmc_software_enable = -1;
+    
+    // VL53L0X
+    for (int i = 0; i < VL53L0X_MAX_CHANNELS; i++) {
+        last_pub_vl53_distance[i] = 65535;
+        last_pub_vl53_raw[i] = 65535;
+        last_pub_vl53_status[i] = -1;
+        last_pub_vl53_calibrated[i] = -1;
+    }
+    last_pub_vl53_mode = MODE_COUNT;
+}
+
+static void subscribeToAllTopics() {
+    // Motor
+    client.subscribe("motor/control/rpm");
+    client.subscribe("motor/control/driver");
+    client.subscribe("motor/control/totalsteps/reset");
+    client.subscribe("motor/control/tmc/current_percent");
+    client.subscribe("motor/control/tmc/microsteps");
+    client.subscribe("motor/control/tmc/stallguard");
+    client.subscribe("motor/control/tmc/enable");
+    client.subscribe("motor/control/tmc/stealthchop");
+    client.subscribe("motor/control/tmc/coolstep");
+
+    // Servo
+    client.subscribe("servo/control/+/#");
+    
+    // VL53L0X
+    client.subscribe("sensor/control/mode");
+    client.subscribe("sensor/control/mode_name");
+    client.subscribe("sensor/control/calibrate/start/+");
+    client.subscribe("sensor/control/calibrate/finish/+");
+    client.subscribe("sensor/control/clear_cal/+");
+    client.subscribe("sensor/control/enable/+");
+    client.subscribe("sensor/control/publish_all");
+}
+
+static void reconnect() {
+    while (!client.connected()) {
+        if (client.connect(MQTT_CLIENT_ID, MQTT_USER, MQTT_PASS)) {
+            resetAllCaches();
+            subscribeToAllTopics();
+            Serial.println("MQTT Connected and subscribed");
+        } else {
+            Serial.printf("MQTT connection failed, rc=%d, retrying...\n", client.state());
+            vTaskDelay(pdMS_TO_TICKS(5000));
+        }
+    }
+}
+
+// ============================================
+// ОБРАБОТКА ВХОДЯЩИХ MQTT КОМАНД
+// ============================================
+static void callback(char* topic, byte* payload, unsigned int length) {
+    char msg[length + 1];
+    memcpy(msg, payload, length);
+    msg[length] = '\0';
+
+    if (strcmp(topic, "motor/control/rpm") == 0) {
+        setTargetRPM(atoi(msg)); // Поддерживает отрицательные для реверса!
+    }
+    else if (strcmp(topic, "motor/control/driver") == 0) {
+        // TMC2209: LOW = Enabled, HIGH = Disabled
+        bool enable = (strcmp(msg, "on") == 0);
+        digitalWrite(EN_PIN, enable ? LOW : HIGH);
+    }
+    else if (strcmp(topic, "motor/control/totalsteps/reset") == 0) {
+        resetSteps();
+        if (client.connected()) client.publish("motor/feedback/totalsteps", "0");
+        last_pub_steps = 0;
+    }
+    // --- TMC Control ---
+    else if (strcmp(topic, "motor/control/tmc/current_percent") == 0) {
+        uint8_t pct = atoi(msg);
+        if (pct <= 100) tmcSetCurrentPercent(pct, pct / 2); // Hold = 50% от Run
+    }
+    else if (strcmp(topic, "motor/control/tmc/microsteps") == 0) {
+        uint16_t ms = atoi(msg);
+        tmcSetMicrosteps(ms);
+    }
+    else if (strcmp(topic, "motor/control/tmc/stallguard") == 0) {
+        tmcSetStallGuard(atoi(msg));
+    }
+    else if (strcmp(topic, "motor/control/tmc/enable") == 0) {
+        tmcSoftwareEnable(strcmp(msg, "on") == 0);
+    }
+    else if (strcmp(topic, "motor/control/tmc/stealthchop") == 0) {
+        tmcSetStealthChop(strcmp(msg, "on") == 0);
+    }
+    else if (strcmp(topic, "motor/control/tmc/coolstep") == 0) {
+        tmcSetCoolStep(strcmp(msg, "on") == 0);
+    } 
+    else if (strncmp(topic, "servo/control", 12) == 0) {
+        handleServoMQTTCommand(topic, msg);
+    }
+    // === VL53L0X ===
+    else if (strcmp(topic, "sensor/control/mode") == 0) {
+        int mode = atoi(msg);
+        if (mode >= 0 && mode < MODE_COUNT) {
+            vl53l0xSetMode((MeasurementMode)mode);
+        }
+    }
+    else if (strcmp(topic, "sensor/control/mode_name") == 0) {
+        // Маппинг имени режима на ID (если нужно)
+        // Пока просто логируем
+        Serial.printf("Mode name request: %s\n", msg);
+    }
+    else if (strncmp(topic, "sensor/control/calibrate/start/", 31) == 0) {
+        int channel = atoi(topic + 31);
+        int near_mm = atoi(msg);
+        if (channel >= 0 && channel < VL53L0X_MAX_CHANNELS && near_mm > 0) {
+            vl53l0xStartCalibration(channel, near_mm);
+        }
+    }
+    else if (strncmp(topic, "sensor/control/calibrate/finish/", 32) == 0) {
+        int channel = atoi(topic + 32);
+        int far_mm = atoi(msg);
+        if (channel >= 0 && channel < VL53L0X_MAX_CHANNELS && far_mm > 0) {
+            vl53l0xFinishCalibration(channel, far_mm);
+        }
+    }
+    else if (strncmp(topic, "sensor/control/clear_cal/", 25) == 0) {
+        int channel = atoi(topic + 25);
+        if (channel >= 0 && channel < VL53L0X_MAX_CHANNELS) {
+            vl53l0xClearCalibration(channel);
+        }
+    }
+    else if (strncmp(topic, "sensor/control/enable/", 22) == 0) {
+        int channel = atoi(topic + 22);
+        bool enable = (strcmp(msg, "on") == 0 || strcmp(msg, "1") == 0 || strcmp(msg, "true") == 0);
+        if (channel >= 0 && channel < VL53L0X_MAX_CHANNELS) {
+            vl53l0xEnableChannel(channel, enable);
+        }
+    }
+    else if (strcmp(topic, "sensor/control/publish_all") == 0) {
+        // Сбрасываем кэш для принудительной публикации
+        for (int i = 0; i < VL53L0X_MAX_CHANNELS; i++) {
+            last_pub_vl53_distance[i] = 65535;
+            last_pub_vl53_raw[i] = 65535;
+        }
+    }
+}
+
+// ============================================
+// ПУБЛИКАЦИЯ MOTOR TELEMETRY
+// ============================================
+
+static void publishMotorTelemetry() {
+    // RPM
+    int rpm = getCurrentRPM();
+    if (rpm != last_pub_rpm) {
+        client.publish("motor/feedback/rpm", intToString(rpm));
+        last_pub_rpm = rpm;
+    }
+
+    // Steps
+    unsigned long steps = getMotorSteps();
+    if (steps != last_pub_steps) {
+        client.publish("motor/feedback/totalsteps", uintToString(steps));
+        last_pub_steps = steps;
+    }
+
+    // Is running
+    int run = isMotorRunning() ? 1 : 0;
+    if (run != last_pub_is_run) {
+        client.publish("motor/feedback/is_run", run ? "true" : "false");
+        last_pub_is_run = run;
+    }
+
+    // TMC
+    if (tmcIsInitialized()) {
+        uint8_t pct = tmcGetRunCurrentPercent();
+        if (pct != last_pub_current_pct) {
+            client.publish("motor/feedback/tmc/current_percent", intToString(pct));
+            last_pub_current_pct = pct;
+        }
+
+        uint16_t ms = tmcGetMicrostepsSetting();
+        if (ms != last_pub_microsteps) {
+            client.publish("motor/feedback/tmc/microsteps", intToString(ms));
+            last_pub_microsteps = ms;
+        }
+
+        uint16_t sg = tmcGetStallGuardResult();
+        if (sg != last_pub_sg) {
+            client.publish("motor/feedback/tmc/sg_result", intToString(sg));
+            last_pub_sg = sg;
+        }
+
+        uint32_t interstep = tmcGetInterstepDuration();
+        if (interstep != last_pub_interstep) {
+            client.publish("motor/feedback/tmc/interstep_duration", uintToString(interstep));
+            last_pub_interstep = interstep;
+        }
+
+        TMC2209::Status status = tmcGetStatus();
+        
+        int ot = (status.over_temperature_warning || status.over_temperature_shutdown) ? 1 : 0;
+        if (ot != last_pub_over_temp) {
+            client.publish("motor/feedback/tmc/status/over_temp", ot ? "true" : "false");
+            last_pub_over_temp = ot;
+        }
+
+        int sgnd = (status.short_to_ground_a || status.short_to_ground_b) ? 1 : 0;
+        if (sgnd != last_pub_short_gnd) {
+            client.publish("motor/feedback/tmc/status/short_to_ground", sgnd ? "true" : "false");
+            last_pub_short_gnd = sgnd;
+        }
+
+        int ol = (status.open_load_a || status.open_load_b) ? 1 : 0;
+        if (ol != last_pub_open_load) {
+            client.publish("motor/feedback/tmc/status/open_load", ol ? "true" : "false");
+            last_pub_open_load = ol;
+        }
+
+        int sa = status.stealth_chop_mode ? 1 : 0;
+        if (sa != last_pub_stealth_active) {
+            client.publish("motor/feedback/tmc/status/stealth_chop_active", sa ? "true" : "false");
+            last_pub_stealth_active = sa;
+        }
+
+        int ss = status.standstill ? 1 : 0;
+        if (ss != last_pub_standstill) {
+            client.publish("motor/feedback/tmc/status/standstill", ss ? "true" : "false");
+            last_pub_standstill = ss;
+        }
+
+        if (status.current_scaling != last_pub_current_scaling) {
+            client.publish("motor/feedback/tmc/status/current_scaling", intToString(status.current_scaling));
+            last_pub_current_scaling = status.current_scaling;
+        }
+
+        int cds = checkDriverStatus() ? 1 : 0;
+        if (cds != last_pub_driver_status) {
+            client.publish("motor/feedback/driver/status", cds ? "on" : "off");
+            last_pub_driver_status = cds;
+        }
+        
+        int tse = checkTmcSoftwareEnable() ? 1 : 0;
+        if (tse != last_pub_tmc_software_enable) {
+            client.publish("motor/feedback/tmc/status", tse ? "on" : "off");
+            last_pub_tmc_software_enable = tse;
+        }
+    }
+}
+
+// ============================================
+// ПУБЛИКАЦИЯ VL53L0X TELEMETRY
+// ============================================
+
+static void publishVL53L0XTelemetry() {
+    // Публикация режима
+    MeasurementMode current_mode = vl53l0xGetMode();
+    if (current_mode != last_pub_vl53_mode) {
+        const ModeProfile* profile = vl53l0xGetModeProfile();
+        
+        client.publish("sensor/feedback/mode", profile->name);
+        client.publish("sensor/feedback/mode_id", intToString(current_mode));
+        client.publish("sensor/feedback/max_range", intToString(profile->max_range_mm));
+        
+        last_pub_vl53_mode = current_mode;
+    }
+    
+    // Публикация данных с каждого канала
+    for (uint8_t ch = 0; ch < VL53L0X_MAX_CHANNELS; ch++) {
+        if (!vl53l0xIsChannelPresent(ch)) continue;
+        
+        char topic[64];
+        
+        // Статус канала
+        int status = vl53l0xIsChannelEnabled(ch) ? 1 : 0;
+        if (status != last_pub_vl53_status[ch]) {
+            snprintf(topic, sizeof(topic), "sensor/feedback/%d/status", ch);
+            client.publish(topic, status ? "on" : "off");
+            last_pub_vl53_status[ch] = status;
+        }
+        
+        // Статус калибровки
+        int calibrated = vl53l0xIsCalibrated(ch) ? 1 : 0;
+        if (calibrated != last_pub_vl53_calibrated[ch]) {
+            snprintf(topic, sizeof(topic), "sensor/feedback/%d/calibrated", ch);
+            client.publish(topic, calibrated ? "true" : "false");
+            last_pub_vl53_calibrated[ch] = calibrated;
+        }
+        
+        // Только если канал активен, публикуем расстояния
+        if (vl53l0xIsChannelActive(ch)) {
+            // Калиброванное расстояние
+            uint16_t distance = vl53l0xReadDistance(ch);
+            if (distance != last_pub_vl53_distance[ch]) {
+                snprintf(topic, sizeof(topic), "sensor/feedback/%d/distance", ch);
+                if (distance != 65535) {
+                    client.publish(topic, intToString(distance));
+                } else {
+                    client.publish(topic, "out_of_range");
+                }
+                last_pub_vl53_distance[ch] = distance;
+            }
+            
+            // Сырое значение
+            uint16_t raw = vl53l0xReadRawDistance(ch);
+            if (raw != last_pub_vl53_raw[ch]) {
+                snprintf(topic, sizeof(topic), "sensor/feedback/%d/raw", ch);
+                if (raw != 65535) {
+                    client.publish(topic, intToString(raw));
+                }
+                last_pub_vl53_raw[ch] = raw;
+            }
+        }
+    }
+}
+
+/////
+
+void checkAndPublishServoStatus(uint8_t channel) {
+    if (channel >= MAX_SERVOS) return;
+    
+    bool current_state = servo_enabled[channel];
+    if (current_state != last_published_status[channel]) {
+        last_published_status[channel] = current_state;
+        
+        char topic[64];
+        snprintf(topic, sizeof(topic), "servo/%d/feedback/status", channel);
+        
+        String status = current_state ? "on" : "off";
+        client.publish(topic, status.c_str());
+        
+        Serial.printf("Published servo %d status: %s\n", channel, status.c_str());
+    }
+}
+
+void checkAndPublishServoAngle(uint8_t channel) {
+    if (channel >= MAX_SERVOS) return;
+    
+    uint8_t current_angle = current_angles[channel];
+    if (current_angle != last_published_angles[channel]) {
+        last_published_angles[channel] = current_angle;
+        
+        char topic[64];
+        snprintf(topic, sizeof(topic), "servo/%d/feedback/angle", channel);
+        
+        char payload[8];
+        snprintf(payload, sizeof(payload), "%d", current_angle);
+        client.publish(topic, payload);
+        
+        Serial.printf("Published servo %d angle: %d\n", channel, current_angle);
+    }
+}
+
+void handleServoMQTTCommand(const char* topic, const char* payload) {
+    // Парсим топик: servo/control/{channel}/{command}
+    int channel = -1;
+    char command[32] = {0};
+    
+    if (sscanf(topic, "servo/control/%2d/%8s", &channel, command) != 2) {
+        Serial.printf("Invalid servo topic: %s\n", topic);
+        return;
+    }
+    
+    if (channel < 0 || channel >= MAX_SERVOS) {
+        Serial.printf("Invalid servo channel: %d\n", channel);
+        return;
+    }
+    
+    Serial.printf("Servo %d command: %s = %s\n", channel, command, payload);
+    
+    if (strcmp(command, "angle") == 0) {
+        int angle = atoi(payload);
+        if (angle >= 0 && angle <= 180) {
+            setServoAngle(channel, (uint8_t)angle);
+            checkAndPublishServoAngle(channel);
+            checkAndPublishServoStatus(channel);
+        }
+    }
+    else if (strcmp(command, "enable") == 0) {
+        bool enable = (strcmp(payload, "on") == 0 || strcmp(payload, "1") == 0 || strcmp(payload, "true") == 0);
+        if (enable) {
+            enableServo(channel);
+        } else {
+            disableServo(channel);
+        }
+        checkAndPublishServoStatus(channel);
+    }
+}
+
+/////
+
+// ============================================
+// ГЛАВНЫЙ ЦИКЛ ПУБЛИКАЦИИ
+// ============================================
+
+static void publishTelemetry() {
+    unsigned long now = millis();
+    if (now - last_feedback_time >= 500) {
+        publishMotorTelemetry();
+        publishVL53L0XTelemetry();
+        last_feedback_time = now;
+    }
+}
+
+void mqttTask(void *parameter) {
+    static unsigned long last_stack_check = 0;
+
+    setup_wifi();
+    client.setServer(MQTT_SERVER, MQTT_PORT);
+    client.setCallback(callback);
+
+    servoInit();
+
+    for (;;) {
+        if (!client.connected()) reconnect();
+        client.loop();
+        publishTelemetry();
+
+        vTaskDelay(pdMS_TO_TICKS(10));
+    }
+}
--- a/arduino_code/Test/src/mqtt_handler.h
+++ b/arduino_code/Test/src/mqtt_handler.h
@@ -0,0 +1,11 @@
+#ifndef MQTT_HANDLER_H
+#define MQTT_HANDLER_H
+
+#include <Arduino.h>
+#include <WiFi.h>
+#include <PubSubClient.h>
+
+void mqttTask(void *parameter);
+void handleServoMQTTCommand(const char* topic, const char* payload);
+
+#endif
--- a/arduino_code/Test/src/servo_control.cpp
+++ b/arduino_code/Test/src/servo_control.cpp
@@ -0,0 +1,98 @@
+#include "servo_control.h"
+#include "mqtt_handler.h"
+#include "config.h"
+
+static Adafruit_PWMServoDriver pwm = Adafruit_PWMServoDriver();
+static bool servo_initialized = false;
+
+
+
+void servoInit() {
+    Serial.println("Initializing PCA9685 servo driver...");
+    
+    // Инициализация I2C на пинах 21 (SDA) и 22 (SCL)
+    Wire.begin(I2C_SDA_PIN, I2C_SCL_PIN);
+    
+    pwm.begin();
+    pwm.setOscillatorFrequency(27000000);
+    pwm.setPWMFreq(50); // 50 Hz для сервоприводов
+    
+    delay(10);
+    
+    servo_initialized = true;
+    Serial.println("PCA9685 initialized successfully");
+    
+    // Инициализируем все каналы как выключенные
+    for (int i = 0; i < MAX_SERVOS; i++) {
+        current_angles[i] = 90; // Начальное положение - середина
+        servo_enabled[i] = false;
+        disableServo(i);
+    }
+}
+
+// Преобразование угла (0-180) в длину импульса
+uint16_t angleToPulse(uint8_t angle) {
+    if (angle > 180) angle = 180;
+    return map(angle, 0, 180, SERVO_MIN_PULSE, SERVO_MAX_PULSE);
+}
+
+// Преобразование длины импульса в угол
+uint8_t pulseToAngle(uint16_t pulse) {
+    if (pulse < SERVO_MIN_PULSE) return 0;
+    if (pulse > SERVO_MAX_PULSE) return 180;
+    return map(pulse, SERVO_MIN_PULSE, SERVO_MAX_PULSE, 0, 180);
+}
+
+void setServoAngle(uint8_t channel, uint8_t angle) {
+    if (!servo_initialized || channel >= MAX_SERVOS) return;
+    
+    if (angle > 180) angle = 180;
+    
+    current_angles[channel] = angle;
+    servo_enabled[channel] = true;
+    
+    uint16_t pulse = angleToPulse(angle);
+    setServoPulse(channel, pulse);
+    
+    Serial.printf("Servo %d: angle=%d, pulse=%d\n", channel, angle, pulse);
+}
+
+void setServoPulse(uint8_t channel, uint16_t pulse) {
+    if (!servo_initialized || channel >= MAX_SERVOS) return;
+    
+    // Преобразование микросекунд в тики PCA9685
+    // PCA9685 имеет 4096 тиков на период при 50Hz = 20000 мкс
+    // 1 мкс = 4096 / 20000 = 0.2048 тика
+    double pulselength = 4096.0 / 20000.0; // тиков на микросекунду
+    uint16_t ticks = pulse * pulselength;
+    
+    pwm.setPWM(channel, 0, ticks);
+}
+
+void enableServo(uint8_t channel) {
+    if (!servo_initialized || channel >= MAX_SERVOS) return;
+    
+    servo_enabled[channel] = true;
+    setServoAngle(channel, current_angles[channel]);
+    
+    Serial.printf("Servo %d: ENABLED\n", channel);
+}
+
+void disableServo(uint8_t channel) {
+    if (!servo_initialized || channel >= MAX_SERVOS) return;
+    
+    servo_enabled[channel] = false;
+    pwm.setPWM(channel, 0, 0); // Отключаем сигнал
+    
+    Serial.printf("Servo %d: DISABLED\n", channel);
+}
+
+uint8_t getServoAngle(uint8_t channel) {
+    if (channel >= MAX_SERVOS) return 0;
+    return current_angles[channel];
+}
+
+bool isServoEnabled(uint8_t channel) {
+    if (channel >= MAX_SERVOS) return false;
+    return servo_enabled[channel];
+}
--- a/arduino_code/Test/src/servo_control.h
+++ b/arduino_code/Test/src/servo_control.h
@@ -0,0 +1,32 @@
+#ifndef SERVO_H
+#define SERVO_H
+
+#include <Arduino.h>
+#include <Adafruit_PWMServoDriver.h>
+
+
+// Хранение текущего состояния сервоприводов
+#define MAX_SERVOS 16
+static uint8_t current_angles[MAX_SERVOS] = {0};
+static bool servo_enabled[MAX_SERVOS] = {false};
+static uint8_t last_published_angles[MAX_SERVOS] = {255};
+static bool last_published_status[MAX_SERVOS] = {false};
+
+// Минимальная и максимальная длина импульса для сервопривода (в микросекундах)
+static const uint16_t SERVO_MIN_PULSE = 600;
+static const uint16_t SERVO_MAX_PULSE = 2400;
+
+// Инициализация сервопривода
+void servoInit();
+
+// Управление сервоприводом
+void setServoAngle(uint8_t channel, uint8_t angle);
+void setServoPulse(uint8_t channel, uint16_t pulse);
+void enableServo(uint8_t channel);
+void disableServo(uint8_t channel);
+
+// Получение состояния
+uint8_t getServoAngle(uint8_t channel);
+bool isServoEnabled(uint8_t channel);
+
+#endif // SERVO_H
--- a/arduino_code/Test/src/vl53l0x_sensor.cpp
+++ b/arduino_code/Test/src/vl53l0x_sensor.cpp
@@ -0,0 +1,477 @@
+#include "vl53l0x_sensor.h"
+#include "config.h"
+
+// ============================================
+// КОНСТАНТЫ
+// ============================================
+
+#define TCA9548A_ADDRESS 0x70
+#define TCA9548A_CHANNELS 8
+
+#define MIN_DISTANCE_MM 30
+#define OUT_OF_RANGE_VALUE 65535
+
+#define FILTER_SIZE 5
+
+// ============================================
+// ПРОФИЛИ РЕЖИМОВ
+// ============================================
+
+static const ModeProfile MODES[MODE_COUNT] = {
+    {
+        "HIGH_ACCURACY",
+        200000, 14, 10, 0.5f, 500, 2
+    },
+    {
+        "PRECISION",
+        66000, 14, 10, 0.3f, 1000, 5
+    },
+    {
+        "DEFAULT",
+        33000, 14, 10, 0.25f, 1200, 15
+    },
+    {
+        "LONG_RANGE",
+        33000, 18, 14, 0.1f, 2000, 40
+    },
+    {
+        "ULTRA_LONG",
+        100000, 18, 14, 0.05f, 2500, 80
+    }
+};
+
+// ============================================
+// ГЛОБАЛЬНЫЕ ПЕРЕМЕННЫЕ
+// ============================================
+
+static VL53L0X sensor;
+static Preferences preferences;
+
+static MeasurementMode current_mode = MODE_DEFAULT;
+static bool sensor_present[TCA9548A_CHANNELS] = {false};
+static bool channel_enabled[TCA9548A_CHANNELS] = {false};
+static CalibrationData calibration[TCA9548A_CHANNELS];
+
+static uint16_t filter_buffer[TCA9548A_CHANNELS][FILTER_SIZE];
+static uint8_t filter_index[TCA9548A_CHANNELS] = {0};
+
+static bool calibration_in_progress = false;
+static uint8_t calibration_channel = 0;
+static uint16_t calibration_near_raw = 0;
+static uint16_t calibration_near_known = 0;
+
+// ============================================
+// TCA9548A МУЛЬТИПЛЕКСОР
+// ============================================
+
+static void TCA9548A_Select(uint8_t channel) {
+    Wire.beginTransmission(TCA9548A_ADDRESS);
+    Wire.write((channel < TCA9548A_CHANNELS) ? (1 << channel) : 0x00);
+    Wire.endTransmission();
+    delay(3);
+}
+
+static void TCA9548A_DisableAll() {
+    Wire.beginTransmission(TCA9548A_ADDRESS);
+    Wire.write(0x00);
+    Wire.endTransmission();
+}
+
+static bool checkTCA9548A() {
+    Wire.beginTransmission(TCA9548A_ADDRESS);
+    return (Wire.endTransmission() == 0);
+}
+
+// ============================================
+// NVS (СОХРАНЕНИЕ В FLASH)
+// ============================================
+
+static void loadCalibration() {
+    preferences.begin("vl53_cal", true);
+    
+    for (uint8_t ch = 0; ch < TCA9548A_CHANNELS; ch++) {
+        char key[16];
+        snprintf(key, sizeof(key), "ch%d", ch);
+        
+        size_t len = preferences.getBytesLength(key);
+        if (len == sizeof(CalibrationData)) {
+            preferences.getBytes(key, &calibration[ch], sizeof(CalibrationData));
+        } else {
+            calibration[ch].valid = false;
+            calibration[ch].scale = 1.0f;
+            calibration[ch].offset = 0.0f;
+        }
+    }
+    
+    int saved_mode = preferences.getInt("mode", MODE_DEFAULT);
+    if (saved_mode >= 0 && saved_mode < MODE_COUNT) {
+        current_mode = (MeasurementMode)saved_mode;
+    }
+    
+    preferences.end();
+}
+
+static void saveCalibration(uint8_t channel) {
+    preferences.begin("vl53_cal", false);
+    char key[16];
+    snprintf(key, sizeof(key), "ch%d", channel);
+    preferences.putBytes(key, &calibration[channel], sizeof(CalibrationData));
+    preferences.end();
+}
+
+static void saveMode() {
+    preferences.begin("vl53_cal", false);
+    preferences.putInt("mode", (int)current_mode);
+    preferences.end();
+}
+
+// ============================================
+// ПРИМЕНЕНИЕ РЕЖИМА
+// ============================================
+
+static bool applyModeProfile() {
+    const ModeProfile& profile = MODES[current_mode];
+    
+    sensor.setTimeout(500);
+    
+    if (!sensor.init()) {
+        return false;
+    }
+    
+    sensor.setAddress(0x29);
+    sensor.setSignalRateLimit(profile.signal_rate_limit);
+    
+    sensor.setVcselPulsePeriod(VL53L0X::VcselPeriodPreRange, profile.vcsel_prerange);
+    sensor.setVcselPulsePeriod(VL53L0X::VcselPeriodFinalRange, profile.vcsel_final);
+    sensor.setMeasurementTimingBudget(profile.timing_budget_us);
+    
+    return true;
+}
+
+// ============================================
+// КАЛИБРОВКА И ФИЛЬТРАЦИЯ
+// ============================================
+
+static uint16_t applyCalibration(uint8_t channel, uint16_t raw_mm) {
+    if (!calibration[channel].valid || raw_mm == OUT_OF_RANGE_VALUE) {
+        return raw_mm;
+    }
+    
+    float calibrated = (float)raw_mm * calibration[channel].scale + calibration[channel].offset;
+    
+    const ModeProfile& profile = MODES[current_mode];
+    if (calibrated < MIN_DISTANCE_MM) calibrated = MIN_DISTANCE_MM;
+    if (calibrated > profile.max_range_mm) return OUT_OF_RANGE_VALUE;
+    
+    return (uint16_t)calibrated;
+}
+
+static uint16_t applyFilter(uint8_t channel, uint16_t new_value) {
+    if (new_value == OUT_OF_RANGE_VALUE) return OUT_OF_RANGE_VALUE;
+    
+    filter_buffer[channel][filter_index[channel]] = new_value;
+    filter_index[channel] = (filter_index[channel] + 1) % FILTER_SIZE;
+    
+    uint32_t sum = 0;
+    uint8_t count = 0;
+    for (uint8_t i = 0; i < FILTER_SIZE; i++) {
+        if (filter_buffer[channel][i] != 0) {
+            sum += filter_buffer[channel][i];
+            count++;
+        }
+    }
+    
+    return (count > 0) ? (uint16_t)(sum / count) : new_value;
+}
+
+// ============================================
+// ПУБЛИЧНЫЕ ФУНКЦИИ
+// ============================================
+
+void vl53l0xInit() {
+    Serial.println("Initializing VL53L0X sensors...");
+    
+    Wire.begin(I2C_SDA_PIN, I2C_SCL_PIN);
+    Wire.setClock(400000);
+    delay(100);
+    
+    if (!checkTCA9548A()) {
+        Serial.println("ERROR: TCA9548A not found!");
+        return;
+    }
+    Serial.println("✓ TCA9548A found");
+    TCA9548A_DisableAll();
+    
+    loadCalibration();
+    Serial.printf("✓ Loaded mode: %s\n", MODES[current_mode].name);
+    
+    Serial.println("\nScanning VL53L0X channels:");
+    for (uint8_t channel = 0; channel < TCA9548A_CHANNELS; channel++) {
+        TCA9548A_Select(channel);
+        delay(20);
+        
+        if (applyModeProfile()) {
+            sensor_present[channel] = true;
+            channel_enabled[channel] = true;
+            Serial.printf("  ✓ Channel %d: VL53L0X found", channel);
+            if (calibration[channel].valid) Serial.print(" [CALIBRATED]");
+            Serial.println();
+            
+            memset(filter_buffer[channel], 0, sizeof(filter_buffer[channel]));
+            filter_index[channel] = 0;
+        } else {
+            sensor_present[channel] = false;
+            channel_enabled[channel] = false;
+            Serial.printf("  ✗ Channel %d: No device\n", channel);
+        }
+        
+        TCA9548A_DisableAll();
+        delay(5);
+    }
+    
+    Serial.printf("\n✓ VL53L0X initialized: %d sensors found\n\n", 
+                  vl53l0xGetChannelCount());
+}
+
+void vl53l0xLoop() {
+    // Внутренняя логика датчиков (если нужна)
+    // Сейчас вся публикация в mqtt_handle.cpp
+}
+
+bool vl53l0xSetMode(MeasurementMode mode) {
+    if (mode < 0 || mode >= MODE_COUNT) {
+        Serial.printf("ERROR: Invalid mode %d\n", mode);
+        return false;
+    }
+    
+    current_mode = mode;
+    saveMode();
+    
+    const ModeProfile& profile = MODES[current_mode];
+    Serial.printf("✓ Mode changed to: %s (max %d mm)\n", 
+                  profile.name, profile.max_range_mm);
+    
+    return true;
+}
+
+MeasurementMode vl53l0xGetMode() {
+    return current_mode;
+}
+
+const ModeProfile* vl53l0xGetModeProfile() {
+    return &MODES[current_mode];
+}
+
+uint16_t vl53l0xReadDistance(uint8_t channel) {
+    if (channel >= TCA9548A_CHANNELS || !sensor_present[channel] || !channel_enabled[channel]) {
+        return OUT_OF_RANGE_VALUE;
+    }
+    
+    TCA9548A_Select(channel);
+    
+    if (!applyModeProfile()) {
+        TCA9548A_DisableAll();
+        return OUT_OF_RANGE_VALUE;
+    }
+    
+    uint16_t distance = sensor.readRangeSingleMillimeters();
+    bool timeout = sensor.timeoutOccurred();
+    
+    TCA9548A_DisableAll();
+    
+    if (distance == 65535 || timeout) return OUT_OF_RANGE_VALUE;
+    
+    const ModeProfile& profile = MODES[current_mode];
+    if (distance < MIN_DISTANCE_MM || distance > profile.max_range_mm) {
+        return OUT_OF_RANGE_VALUE;
+    }
+    
+    uint16_t filtered = applyFilter(channel, distance);
+    uint16_t calibrated = applyCalibration(channel, filtered);
+    
+    return calibrated;
+}
+
+uint16_t vl53l0xReadRawDistance(uint8_t channel) {
+    if (channel >= TCA9548A_CHANNELS || !sensor_present[channel] || !channel_enabled[channel]) {
+        return OUT_OF_RANGE_VALUE;
+    }
+    
+    TCA9548A_Select(channel);
+    
+    if (!applyModeProfile()) {
+        TCA9548A_DisableAll();
+        return OUT_OF_RANGE_VALUE;
+    }
+    
+    uint16_t distance = sensor.readRangeSingleMillimeters();
+    bool timeout = sensor.timeoutOccurred();
+    
+    TCA9548A_DisableAll();
+    
+    if (distance == 65535 || timeout) return OUT_OF_RANGE_VALUE;
+    
+    return distance;
+}
+
+bool vl53l0xIsChannelActive(uint8_t channel) {
+    return (channel < TCA9548A_CHANNELS && sensor_present[channel] && channel_enabled[channel]);
+}
+
+int vl53l0xGetChannelCount() {
+    int count = 0;
+    for (uint8_t i = 0; i < TCA9548A_CHANNELS; i++) {
+        if (sensor_present[i]) count++;
+    }
+    return count;
+}
+
+bool vl53l0xStartCalibration(uint8_t channel, uint16_t near_known_mm) {
+    if (channel >= TCA9548A_CHANNELS || !sensor_present[channel]) {
+        Serial.printf("ERROR: Channel %d not available\n", channel);
+        return false;
+    }
+    
+    Serial.printf("Starting calibration for channel %d (near point: %d mm)\n", 
+                  channel, near_known_mm);
+    
+    uint32_t sum = 0;
+    uint8_t valid = 0;
+    
+    for (uint8_t i = 0; i < 20; i++) {
+        uint16_t d = vl53l0xReadRawDistance(channel);
+        if (d != OUT_OF_RANGE_VALUE) {
+            sum += d;
+            valid++;
+        }
+        delay(50);
+    }
+    
+    if (valid == 0) {
+        Serial.println("ERROR: Failed to read near point");
+        return false;
+    }
+    
+    calibration_near_raw = (uint16_t)(sum / valid);
+    calibration_near_known = near_known_mm;
+    calibration_channel = channel;
+    calibration_in_progress = true;
+    
+    Serial.printf("✓ Near point captured: raw=%d mm, actual=%d mm\n", 
+                  calibration_near_raw, calibration_near_known);
+    Serial.println("Now place object at FAR point and call vl53l0xFinishCalibration()");
+    
+    return true;
+}
+
+bool vl53l0xFinishCalibration(uint8_t channel, uint16_t far_known_mm) {
+    if (!calibration_in_progress || channel != calibration_channel) {
+        Serial.println("ERROR: Calibration not in progress or wrong channel");
+        return false;
+    }
+    
+    Serial.printf("Finishing calibration for channel %d (far point: %d mm)\n", 
+                  channel, far_known_mm);
+    
+    uint32_t sum = 0;
+    uint8_t valid = 0;
+    
+    for (uint8_t i = 0; i < 20; i++) {
+        uint16_t d = vl53l0xReadRawDistance(channel);
+        if (d != OUT_OF_RANGE_VALUE) {
+            sum += d;
+            valid++;
+        }
+        delay(50);
+    }
+    
+    if (valid == 0) {
+        Serial.println("ERROR: Failed to read far point");
+        calibration_in_progress = false;
+        return false;
+    }
+    
+    uint16_t far_raw = (uint16_t)(sum / valid);
+    
+    Serial.printf("✓ Far point captured: raw=%d mm, actual=%d mm\n", 
+                  far_raw, far_known_mm);
+    
+    if (far_raw == calibration_near_raw) {
+        Serial.println("ERROR: Raw values are identical");
+        calibration_in_progress = false;
+        return false;
+    }
+    
+    float scale = (float)(far_known_mm - calibration_near_known) / 
+                  (float)(far_raw - calibration_near_raw);
+    float offset = (float)calibration_near_known - 
+                   (float)calibration_near_raw * scale;
+    
+    calibration[channel].valid = true;
+    calibration[channel].near_raw = calibration_near_raw;
+    calibration[channel].near_known = calibration_near_known;
+    calibration[channel].far_raw = far_raw;
+    calibration[channel].far_known = far_known_mm;
+    calibration[channel].scale = scale;
+    calibration[channel].offset = offset;
+    
+    saveCalibration(channel);
+    
+    Serial.printf("✓ Calibration complete: scale=%.5f, offset=%.2f\n", scale, offset);
+    
+    calibration_in_progress = false;
+    
+    return true;
+}
+
+void vl53l0xClearCalibration(uint8_t channel) {
+    if (channel >= TCA9548A_CHANNELS) return;
+    
+    calibration[channel].valid = false;
+    calibration[channel].scale = 1.0f;
+    calibration[channel].offset = 0.0f;
+    saveCalibration(channel);
+    
+    Serial.printf("✓ Channel %d calibration cleared\n", channel);
+}
+
+bool vl53l0xIsCalibrated(uint8_t channel) {
+    return (channel < TCA9548A_CHANNELS && calibration[channel].valid);
+}
+
+CalibrationData vl53l0xGetCalibration(uint8_t channel) {
+    if (channel >= TCA9548A_CHANNELS) {
+        CalibrationData empty = {false, 0, 0, 0, 0, 1.0f, 0.0f};
+        return empty;
+    }
+    return calibration[channel];
+}
+
+void vl53l0xEnableChannel(uint8_t channel, bool enable) {
+    if (channel >= TCA9548A_CHANNELS) return;
+    
+    if (!sensor_present[channel]) {
+        Serial.printf("ERROR: Channel %d not present\n", channel);
+        return;
+    }
+    
+    channel_enabled[channel] = enable;
+    Serial.printf("✓ Channel %d %s\n", channel, enable ? "enabled" : "disabled");
+}
+
+bool vl53l0xIsChannelEnabled(uint8_t channel) {
+    return (channel < TCA9548A_CHANNELS && channel_enabled[channel]);
+}
+
+bool vl53l0xIsChannelPresent(uint8_t channel) {
+    return (channel < TCA9548A_CHANNELS && sensor_present[channel]);
+}
+
+void sensorTask(void *parameter) {
+    vl53l0xInit();
+    
+    for (;;) {
+        vl53l0xLoop();
+        vTaskDelay(pdMS_TO_TICKS(50));
+    }
+}
--- a/arduino_code/Test/src/vl53l0x_sensor.h
+++ b/arduino_code/Test/src/vl53l0x_sensor.h
@@ -0,0 +1,68 @@
+#ifndef VL53L0X_SENSOR_H
+#define VL53L0X_SENSOR_H
+
+#include <Arduino.h>
+#include <VL53L0X.h>
+#include <Wire.h>
+#include <Preferences.h>
+
+// Режимы измерения
+enum MeasurementMode {
+    MODE_HIGH_ACCURACY = 0,
+    MODE_PRECISION = 1,
+    MODE_DEFAULT = 2,
+    MODE_LONG_RANGE = 3,
+    MODE_ULTRA_LONG = 4,
+    MODE_COUNT = 5
+};
+
+struct ModeProfile {
+    const char* name;
+    uint32_t timing_budget_us;
+    uint8_t vcsel_prerange;
+    uint8_t vcsel_final;
+    float signal_rate_limit;
+    uint16_t max_range_mm;
+    uint8_t accuracy_mm;
+};
+
+struct CalibrationData {
+    bool valid;
+    uint16_t near_raw;
+    uint16_t near_known;
+    uint16_t far_raw;
+    uint16_t far_known;
+    float scale;
+    float offset;
+};
+
+// Инициализация и цикл
+void vl53l0xInit();
+void vl53l0xLoop();
+
+// Управление режимами
+bool vl53l0xSetMode(MeasurementMode mode);
+MeasurementMode vl53l0xGetMode();
+const ModeProfile* vl53l0xGetModeProfile();
+
+// Чтение данных
+uint16_t vl53l0xReadDistance(uint8_t channel);
+uint16_t vl53l0xReadRawDistance(uint8_t channel);
+bool vl53l0xIsChannelActive(uint8_t channel);
+int vl53l0xGetChannelCount();
+
+// Калибровка
+bool vl53l0xStartCalibration(uint8_t channel, uint16_t near_known_mm);
+bool vl53l0xFinishCalibration(uint8_t channel, uint16_t far_known_mm);
+void vl53l0xClearCalibration(uint8_t channel);
+bool vl53l0xIsCalibrated(uint8_t channel);
+CalibrationData vl53l0xGetCalibration(uint8_t channel);
+
+// Управление каналами
+void vl53l0xEnableChannel(uint8_t channel, bool enable);
+bool vl53l0xIsChannelEnabled(uint8_t channel);
+bool vl53l0xIsChannelPresent(uint8_t channel);
+
+void sensorTask(void *parameter);
+
+#endif // VL53L0X_SENSOR_H
--- a/arduino_code/Test/test/README
+++ b/arduino_code/Test/test/README
@@ -0,0 +1,11 @@
+
+This directory is intended for PlatformIO Test Runner and project tests.
+
+Unit Testing is a software testing method by which individual units of
+source code, sets of one or more MCU program modules together with associated
+control data, usage procedures, and operating procedures, are tested to
+determine whether they are fit for use. Unit testing finds problems early
+in the development cycle.
+
+More information about PlatformIO Unit Testing:
+- https://docs.platformio.org/en/latest/advanced/unit-testing/index.html
--- a/backend_control/.gitignore
+++ b/backend_control/.gitignore
@@ -0,0 +1 @@
+/testing
--- a/backend_control/README.md
+++ b/backend_control/README.md
@@ -0,0 +1,61 @@
+# Интерфейс управления
+
+![](img/gui_interface.png)
+
+## Область Управления
+
+`Целевой RPM` - Задается уставка скорости в диапозоне от -1000 до 1000 оборотов в минуту
+
+`Ток` - Уставка тока в диапозоне 0 - 100%
+
+`StallGuard` - 
+
+`Микрошаг` - Уставка микрошага
+
+`Сброс счетчика шагов` - Сброс счетчика шагов
+
+## Область Режимы
+
+`Аппаратное вкл. (Driver EN)` - Аппаратное Включение/Выключение драйвера tmc2209
+
+`Программное вкл. (TMC Chip)` - Программное Включение/Выключение драйвера tmc2209
+
+`StealthChop (Тихий)` - Включение/Выключение тихого режима работы шагового двигателя.
+
+`CoolStep (Энергосбер.)` - Включение/Выключение энергосберегающего режима работы шагового двигателя.
+
+## Область Телеметрия и Статусы
+
+`Текущий RPM (Факт)`
+
+`Всего шагов`
+
+`Вращение`
+
+`SG Result` - Для отслеживания нагрузки на вал или момента срыва шагов. Резкое падение значения sg_result при движении обычно означает столкновение или заклинивание механизма.
+
+`Interstep (ns)`
+
+`Current Scaling`
+
+## Область Ошибки и Флаги
+
+`Перегрев`
+
+`КЗ на землю`
+
+`Обрыв нагрузки`
+
+`StealthChop активен`
+
+`Остановка (Standstill)`
+
+![](img/servo_interface.png)
+
+## Область Управление Серво
+
+Тут можно задать угол сервопривода и отключить сервопривод
+
+## Облать Статус и телеметрия
+
+Вывод информации о сервоприводе включен или выключен. Так же выведен текущий угол.
--- a/backend_control/create_venv.sh
+++ b/backend_control/create_venv.sh
@@ -0,0 +1,6 @@
+#!/bin/bash
+
+python -m venv testing
+
+source testing/bin/activate
+pip install -r requirements.txt
--- a/backend_control/gui.py
+++ b/backend_control/gui.py
@@ -0,0 +1,460 @@
+import customtkinter as ctk
+import paho.mqtt.client as mqtt
+
+# ================= НАСТРОЙКИ =================
+MQTT_BROKER = "192.168.0.200"
+MQTT_PORT = 1883
+MQTT_USER = "test"
+MQTT_PASSWORD = "1234"
+
+MAX_SERVOS = 4 
+MAX_SENSORS = 8  # Количество каналов VL53L0X
+
+# Цвета
+COLOR_OK = "#28a745"
+COLOR_ERR = "#dc3545"
+COLOR_OFF = "#555555"
+COLOR_ACTIVE = "#00d2ff"
+COLOR_PENDING = "#ffaa00"
+COLOR_WARN = "#ff9900" # Для out_of_range
+
+class MotorSCADA:
+    def __init__(self):
+        ctk.set_appearance_mode("Dark")
+        ctk.set_default_color_theme("blue")
+        
+        self.root = ctk.CTk()
+        self.root.title("🚀 Motor, Servo & Sensor SCADA")
+        self.root.geometry("1200x900")
+        self.root.minsize(1100, 800)
+        
+        # Флаги ожидания
+        self.driver_pending = False
+        self.tmc_pending = False
+        self.servo_pending = {i: False for i in range(MAX_SERVOS)}
+        self.sensor_pending = {i: False for i in range(MAX_SENSORS)}
+        
+        self.setup_gui()
+        self.setup_mqtt()
+        
+    def setup_gui(self):
+        # --- Шапка ---
+        header = ctk.CTkFrame(self.root, height=60)
+        header.pack(fill="x", padx=20, pady=(20, 10))
+        header.pack_propagate(False)
+        ctk.CTkLabel(header, text="Motor, Servo & Sensor SCADA", font=ctk.CTkFont(size=24, weight="bold")).pack(side="left", padx=20)
+        self.lbl_status = ctk.CTkLabel(header, text="● Отключено", text_color=COLOR_ERR, font=ctk.CTkFont(size=16, weight="bold"))
+        self.lbl_status.pack(side="right", padx=20)
+
+        # --- Вкладки ---
+        self.tabview = ctk.CTkTabview(self.root)
+        self.tabview.pack(fill="both", expand=True, padx=20, pady=10)
+        
+        self.tab_motor = self.tabview.add("Шаговый двигатель (TMC2209)")
+        self.tab_servo = self.tabview.add(f"Сервоприводы (0-{MAX_SERVOS-1})")
+        self.tab_sensor = self.tabview.add(f"Датчики VL53L0X (0-{MAX_SENSORS-1})")
+        
+        self.create_motor_tab(self.tab_motor)
+        self.create_servo_tab(self.tab_servo)
+        self.create_sensor_tab(self.tab_sensor)
+
+    # ================= ВКЛАДКА ШАГОВОГО ДВИГАТЕЛЯ =================
+    # (Код для мотора остался без изменений, чтобы не раздувать ответ, 
+    # но в реальном файле он должен быть здесь полностью)
+    def create_motor_tab(self, parent):
+        grid = ctk.CTkFrame(parent, fg_color="transparent")
+        grid.pack(fill="both", expand=True)
+        grid.grid_columnconfigure((0, 1, 2), weight=1, uniform="col")
+        grid.grid_rowconfigure(0, weight=1)
+        self.create_control_frame(grid)
+        self.create_modes_frame(grid)
+        self.create_telemetry_frame(grid)
+
+    def create_control_frame(self, parent):
+        frame = ctk.CTkFrame(parent)
+        frame.grid(row=0, column=0, sticky="nsew", padx=(0, 10))
+        ctk.CTkLabel(frame, text="⚙️ Управление", font=ctk.CTkFont(size=18, weight="bold")).pack(pady=(10, 20))
+        ctk.CTkLabel(frame, text="Целевой RPM:").pack(anchor="w", padx=20)
+        rpm_frame = ctk.CTkFrame(frame, fg_color="transparent")
+        rpm_frame.pack(fill="x", padx=20, pady=5)
+        self.sld_rpm = ctk.CTkSlider(rpm_frame, from_=-1000, to=1000, command=self.on_rpm_slider_change)
+        self.sld_rpm.pack(side="left", fill="x", expand=True, padx=(0, 10))
+        self.ent_rpm = ctk.CTkEntry(rpm_frame, width=80, justify="right")
+        self.ent_rpm.insert(0, "0"); self.ent_rpm.pack(side="left", padx=(0, 10))
+        self.ent_rpm.bind("<Return>", self.on_rpm_entry_apply); self.ent_rpm.bind("<FocusOut>", self.on_rpm_entry_apply)
+        self.lbl_rpm_val = ctk.CTkLabel(rpm_frame, text="0", width=50); self.lbl_rpm_val.pack(side="right")
+        
+        ctk.CTkLabel(frame, text="Ток (%):").pack(anchor="w", padx=20, pady=(15,0))
+        cur_frame = ctk.CTkFrame(frame, fg_color="transparent")
+        cur_frame.pack(fill="x", padx=20, pady=5)
+        self.sld_current = ctk.CTkSlider(cur_frame, from_=0, to=100, command=self.on_current_change)
+        self.sld_current.pack(side="left", fill="x", expand=True)
+        self.lbl_cur_val = ctk.CTkLabel(cur_frame, text="50", width=50); self.lbl_cur_val.pack(side="right", padx=(10, 0))
+        
+        ctk.CTkLabel(frame, text="StallGuard (0-255):").pack(anchor="w", padx=20, pady=(15,0))
+        self.ent_sg = ctk.CTkEntry(frame, width=100); self.ent_sg.insert(0, "0")
+        self.ent_sg.pack(anchor="w", padx=20, pady=5)
+        ctk.CTkButton(frame, text="Применить SG", width=150, command=self.on_sg_apply).pack(pady=5)
+        
+        ctk.CTkLabel(frame, text="Микрошаги:").pack(anchor="w", padx=20, pady=(15,0))
+        self.opt_msteps = ctk.CTkOptionMenu(frame, values=["1", "2", "4", "8", "16", "32", "64", "128", "256"], command=self.on_msteps_change)
+        self.opt_msteps.set("16"); self.opt_msteps.pack(anchor="w", padx=20, pady=5)
+        ctk.CTkButton(frame, text="Сбросить счетчик шагов", fg_color="#dc3545", hover_color="#b02a37", command=self.on_reset_steps).pack(pady=20)
+
+    def create_modes_frame(self, parent):
+        frame = ctk.CTkFrame(parent)
+        frame.grid(row=0, column=1, sticky="nsew", padx=10)
+        ctk.CTkLabel(frame, text="🔌 Режимы и Включение", font=ctk.CTkFont(size=18, weight="bold")).pack(pady=(10, 20))
+        self.sw_driver, self.led_driver_fb = self.create_switch_with_feedback(frame, "Аппаратное вкл. (Driver EN)", self.on_driver_change)
+        self.sw_tmc_enable, self.led_tmc_fb = self.create_switch_with_feedback(frame, "Программное вкл. (TMC Chip)", self.on_tmc_enable_change)
+        ctk.CTkFrame(frame, height=2, fg_color="#4a4a6a").pack(fill="x", padx=20, pady=15)
+        self.sw_stealth = self.create_switch(frame, "StealthChop (Тихий)", self.on_stealth_change)
+        self.sw_cool = self.create_switch(frame, "CoolStep (Энергосбер.)", self.on_cool_change)
+
+    def create_telemetry_frame(self, parent):
+        frame = ctk.CTkFrame(parent)
+        frame.grid(row=0, column=2, sticky="nsew", padx=(10, 0))
+        ctk.CTkLabel(frame, text="📊 Телеметрия и Статусы", font=ctk.CTkFont(size=18, weight="bold")).pack(pady=(10, 10))
+        tel_frame = ctk.CTkFrame(frame); tel_frame.pack(fill="x", padx=10, pady=5)
+        self.lbl_fb_rpm = self.create_telemetry_row(tel_frame, "Текущий RPM:")
+        self.lbl_fb_steps = self.create_telemetry_row(tel_frame, "Всего шагов:")
+        self.lbl_fb_run = self.create_telemetry_row(tel_frame, "Вращение:")
+        self.lbl_fb_sg = self.create_telemetry_row(tel_frame, "SG Result:")
+        self.lbl_fb_interstep = self.create_telemetry_row(tel_frame, "Interstep:")
+        self.lbl_fb_cscale = self.create_telemetry_row(tel_frame, "Current Scaling:")
+        ctk.CTkLabel(frame, text="🚨 Ошибки и Флаги", font=ctk.CTkFont(size=16, weight="bold")).pack(pady=(15, 5))
+        stat_frame = ctk.CTkFrame(frame); stat_frame.pack(fill="x", padx=10, pady=5)
+        self.led_over_temp = self.create_led_row(stat_frame, "Перегрев:")
+        self.led_short_gnd = self.create_led_row(stat_frame, "КЗ на землю:")
+        self.led_open_load = self.create_led_row(stat_frame, "Обрыв нагрузки:")
+        self.led_stealth_act = self.create_led_row(stat_frame, "StealthChop активен:")
+        self.led_standstill = self.create_led_row(stat_frame, "Остановка:")
+
+    # ================= ВКЛАДКА СЕРВОПРИВОДОВ =================
+    def create_servo_tab(self, parent):
+        grid = ctk.CTkFrame(parent, fg_color="transparent")
+        grid.pack(fill="both", expand=True, padx=10, pady=10)
+        grid.grid_columnconfigure((0, 1), weight=1, uniform="col")
+        grid.grid_rowconfigure((0, 1), weight=1, uniform="row")
+        self.servo_ui = {}
+        for i in range(MAX_SERVOS):
+            row, col = divmod(i, 2)
+            frame = ctk.CTkFrame(grid)
+            frame.grid(row=row, column=col, sticky="nsew", padx=10, pady=10)
+            self.servo_ui[i] = self.create_servo_card(frame, i)
+
+    def create_servo_card(self, parent, channel):
+        ui = {}
+        ctk.CTkLabel(parent, text=f"🦾 Сервопривод #{channel}", font=ctk.CTkFont(size=16, weight="bold")).pack(pady=(10, 10))
+        ctk.CTkLabel(parent, text="Угол (0-180°):").pack(anchor="w", padx=20)
+        ang_frame = ctk.CTkFrame(parent, fg_color="transparent"); ang_frame.pack(fill="x", padx=20, pady=5)
+        sld = ctk.CTkSlider(ang_frame, from_=0, to=180, command=lambda val, ch=channel: self.on_servo_ang_slider(ch, val))
+        sld.pack(side="left", fill="x", expand=True, padx=(0, 10)); sld.set(90)
+        ent = ctk.CTkEntry(ang_frame, width=60, justify="right"); ent.insert(0, "90"); ent.pack(side="left", padx=(0, 10))
+        ent.bind("<Return>", lambda event, ch=channel: self.on_servo_ang_entry(ch, event))
+        ent.bind("<FocusOut>", lambda event, ch=channel: self.on_servo_ang_entry(ch, event))
+        lbl_val = ctk.CTkLabel(ang_frame, text="90", width=40); lbl_val.pack(side="right")
+        ui['slider_ang'], ui['entry_ang'], ui['lbl_ang_val'] = sld, ent, lbl_val
+        
+        sw, led_fb = self.create_switch_with_feedback(parent, "Включить серво", lambda ch=channel: self.on_servo_enable_change(ch))
+        ui['switch_en'], ui['led_fb'] = sw, led_fb
+        
+        tel_frame = ctk.CTkFrame(parent); tel_frame.pack(fill="x", padx=10, pady=15)
+        ui['lbl_fb_ang'] = self.create_telemetry_row(tel_frame, "Текущий угол:")
+        stat_frame = ctk.CTkFrame(parent); stat_frame.pack(fill="x", padx=10, pady=5)
+        ui['led_status'] = self.create_led_row(stat_frame, "Статус:")
+        return ui
+
+    # ================= ВКЛАДКА ДАТЧИКОВ VL53L0X =================
+    def create_sensor_tab(self, parent):
+        main_frame = ctk.CTkFrame(parent, fg_color="transparent")
+        main_frame.pack(fill="both", expand=True, padx=10, pady=10)
+        
+        # --- Глобальное управление ---
+        global_frame = ctk.CTkFrame(main_frame)
+        global_frame.pack(fill="x", padx=10, pady=(0, 10))
+        ctk.CTkLabel(global_frame, text="📏 Глобальные настройки VL53L0X", font=ctk.CTkFont(size=18, weight="bold")).pack(pady=(10, 5))
+        
+        info_frame = ctk.CTkFrame(global_frame, fg_color="transparent")
+        info_frame.pack(fill="x", padx=20, pady=10)
+        
+        self.lbl_sensor_mode = self.create_telemetry_row(info_frame, "Режим:")
+        self.lbl_sensor_mode_id = self.create_telemetry_row(info_frame, "ID режима:")
+        self.lbl_sensor_max_range = self.create_telemetry_row(info_frame, "Макс. дальность (мм):")
+        
+        ctrl_frame = ctk.CTkFrame(global_frame, fg_color="transparent")
+        ctrl_frame.pack(fill="x", padx=20, pady=(0, 10))
+        
+        ctk.CTkLabel(ctrl_frame, text="Выбрать режим:").pack(side="left", padx=(0, 10))
+        # Предполагаем, что режимов от 0 до 4 (Default, HighAccuracy, LongRange, HighSpeed)
+        self.opt_sensor_mode = ctk.CTkOptionMenu(ctrl_frame, values=["0", "1", "2", "3", "4"], width=100, command=self.on_sensor_mode_change)
+        self.opt_sensor_mode.set("0"); self.opt_sensor_mode.pack(side="left", padx=(0, 20))
+        
+        ctk.CTkButton(ctrl_frame, text="🔄 Принудительно обновить все", fg_color="#007bff", hover_color="#0056b3", command=self.on_sensor_publish_all).pack(side="right")
+
+        # --- Сетка каналов (Scrollable) ---
+        scroll_frame = ctk.CTkScrollableFrame(main_frame)
+        scroll_frame.pack(fill="both", expand=True, padx=10, pady=10)
+        scroll_frame.grid_columnconfigure((0, 1, 2, 3), weight=1, uniform="col")
+        
+        self.sensor_ui = {}
+        for i in range(MAX_SENSORS):
+            row, col = divmod(i, 4)
+            frame = ctk.CTkFrame(scroll_frame)
+            frame.grid(row=row, column=col, sticky="nsew", padx=5, pady=5)
+            self.sensor_ui[i] = self.create_sensor_card(frame, i)
+
+    def create_sensor_card(self, parent, channel):
+        ui = {}
+        ctk.CTkLabel(parent, text=f"📡 Канал #{channel}", font=ctk.CTkFont(size=14, weight="bold")).pack(pady=(5, 5))
+        
+        # Включение и калибровка
+        sw, led_fb = self.create_switch_with_feedback(parent, "Включить", lambda ch=channel: self.on_sensor_enable_change(ch))
+        ui['switch_en'], ui['led_fb'] = sw, led_fb
+        
+        cal_stat_frame = ctk.CTkFrame(parent, fg_color="transparent")
+        cal_stat_frame.pack(fill="x", padx=10, pady=5)
+        ctk.CTkLabel(cal_stat_frame, text="Калибровка:").pack(side="left")
+        ui['led_calibrated'] = ctk.CTkLabel(cal_stat_frame, text="●", font=ctk.CTkFont(size=16), text_color=COLOR_OFF)
+        ui['led_calibrated'].pack(side="right")
+        
+        # Поля калибровки
+        cal_ctrl_frame = ctk.CTkFrame(parent, fg_color="transparent")
+        cal_ctrl_frame.pack(fill="x", padx=10, pady=5)
+        
+        ctk.CTkLabel(cal_ctrl_frame, text="Ближняя (мм):").pack(anchor="w")
+        ent_near = ctk.CTkEntry(cal_ctrl_frame, width=60, justify="right"); ent_near.insert(0, "50"); ent_near.pack(side="left", padx=(0, 5))
+        btn_start = ctk.CTkButton(cal_ctrl_frame, text="Старт", width=60, height=28, command=lambda ch=channel, e=ent_near: self.on_sensor_cal_start(ch, e))
+        btn_start.pack(side="right")
+        
+        ctk.CTkLabel(cal_ctrl_frame, text="Дальняя (мм):").pack(anchor="w", pady=(5,0))
+        ent_far = ctk.CTkEntry(cal_ctrl_frame, width=60, justify="right"); ent_far.insert(0, "500"); ent_far.pack(side="left", padx=(0, 5), pady=(5,0))
+        btn_finish = ctk.CTkButton(cal_ctrl_frame, text="Финиш", width=60, height=28, command=lambda ch=channel, e=ent_far: self.on_sensor_cal_finish(ch, e))
+        btn_finish.pack(side="right")
+        
+        ctk.CTkButton(parent, text="Сбросить калибровку", fg_color="#6c757d", hover_color="#5a6268", height=28, command=lambda ch=channel: self.on_sensor_clear_cal(ch)).pack(pady=5)
+        
+        ui['ent_near'], ui['ent_far'] = ent_near, ent_far
+        
+        # Телеметрия
+        tel_frame = ctk.CTkFrame(parent)
+        tel_frame.pack(fill="x", padx=5, pady=5)
+        ui['lbl_dist'] = self.create_telemetry_row(tel_frame, "Дист. (мм):")
+        ui['lbl_raw'] = self.create_telemetry_row(tel_frame, "Сырое (мм):")
+        
+        return ui
+
+    # ================= ВСПОМОГАТЕЛЬНЫЕ МЕТОДЫ GUI =================
+    def create_switch(self, parent, text, command):
+        frame = ctk.CTkFrame(parent, fg_color="transparent"); frame.pack(fill="x", padx=10, pady=5)
+        ctk.CTkLabel(frame, text=text).pack(side="left")
+        switch = ctk.CTkSwitch(frame, text="", command=command); switch.pack(side="right")
+        return switch
+
+    def create_switch_with_feedback(self, parent, text, command):
+        frame = ctk.CTkFrame(parent, fg_color="transparent"); frame.pack(fill="x", padx=10, pady=5)
+        ctk.CTkLabel(frame, text=text).pack(side="left")
+        feedback_led = ctk.CTkLabel(frame, text="●", font=ctk.CTkFont(size=18), text_color=COLOR_OFF)
+        feedback_led.pack(side="right", padx=(10, 0))
+        switch = ctk.CTkSwitch(frame, text="", command=command); switch.pack(side="right", padx=(10, 0))
+        return switch, feedback_led
+
+    def create_telemetry_row(self, parent, text):
+        frame = ctk.CTkFrame(parent, fg_color="transparent"); frame.pack(fill="x", pady=2)
+        ctk.CTkLabel(frame, text=text, anchor="w", font=ctk.CTkFont(size=12)).pack(side="left")
+        val_lbl = ctk.CTkLabel(frame, text="-", font=ctk.CTkFont(weight="bold", size=12), text_color=COLOR_ACTIVE, anchor="e")
+        val_lbl.pack(side="right")
+        return val_lbl
+
+    def create_led_row(self, parent, text):
+        frame = ctk.CTkFrame(parent, fg_color="transparent"); frame.pack(fill="x", pady=2)
+        ctk.CTkLabel(frame, text=text, anchor="w", font=ctk.CTkFont(size=12)).pack(side="left")
+        led_lbl = ctk.CTkLabel(frame, text="●", font=ctk.CTkFont(size=16), text_color=COLOR_OFF)
+        led_lbl.pack(side="right")
+        return led_lbl
+
+    # ================= MQTT =================
+    def setup_mqtt(self):
+        self.client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION2, client_id="python_scada")
+        self.client.username_pw_set(MQTT_USER, MQTT_PASSWORD)
+        self.client.on_connect = self.on_mqtt_connect
+        self.client.on_disconnect = self.on_mqtt_disconnect
+        self.client.on_message = self.on_mqtt_message
+        try:
+            self.client.connect(MQTT_BROKER, MQTT_PORT, 60)
+            self.client.loop_start()
+        except Exception as e:
+            print(f"Ошибка подключения: {e}")
+            self.update_status(False)
+
+    def on_mqtt_connect(self, client, userdata, flags, reason_code, properties):
+        if reason_code == 0:
+            self.root.after(0, self.update_status, True)
+            client.subscribe("motor/feedback/#")
+            client.subscribe("servo/+/feedback/#")
+            client.subscribe("sensor/feedback/#") # Подписка на датчики
+        else:
+            self.root.after(0, self.update_status, False)
+
+    def on_mqtt_disconnect(self, client, userdata, flags, reason_code, properties):
+        self.root.after(0, self.update_status, False)
+
+    def on_mqtt_message(self, client, userdata, msg):
+        self.root.after(0, self.process_feedback, msg.topic, msg.payload.decode('utf-8'))
+
+    def process_feedback(self, topic, val):
+        parts = topic.split('/')
+        
+        # --- MOTOR ---
+        if parts[0] == 'motor' and parts[1] == 'feedback':
+            if topic == "motor/feedback/rpm": self.lbl_fb_rpm.configure(text=val)
+            elif topic == "motor/feedback/totalsteps": self.lbl_fb_steps.configure(text=val)
+            elif topic == "motor/feedback/is_run":
+                is_run = val == "true"
+                self.lbl_fb_run.configure(text="Да" if is_run else "Нет", text_color=COLOR_OK if is_run else COLOR_ERR)
+            elif topic == "motor/feedback/tmc/current_percent": self.lbl_cur_val.configure(text=val); self.sld_current.set(int(val))
+            elif topic == "motor/feedback/tmc/microsteps": self.opt_msteps.set(val)
+            elif topic == "motor/feedback/tmc/sg_result": self.lbl_fb_sg.configure(text=val)
+            elif topic == "motor/feedback/tmc/interstep_duration": self.lbl_fb_interstep.configure(text=val)
+            elif topic == "motor/feedback/tmc/status/current_scaling": self.lbl_fb_cscale.configure(text=val)
+            elif topic == "motor/feedback/tmc/status/over_temp": self.update_led(self.led_over_temp, val, True)
+            elif topic == "motor/feedback/tmc/status/short_to_ground": self.update_led(self.led_short_gnd, val, True)
+            elif topic == "motor/feedback/tmc/status/open_load": self.update_led(self.led_open_load, val, True)
+            elif topic == "motor/feedback/tmc/status/stealth_chop_active": self.update_led(self.led_stealth_act, val, False)
+            elif topic == "motor/feedback/tmc/status/standstill": self.update_led(self.led_standstill, val, False)
+            elif topic == "motor/feedback/driver/status":
+                is_on = val == "on"; self.driver_pending = False
+                if self.sw_driver.get() != is_on: self.sw_driver.select() if is_on else self.sw_driver.deselect()
+                self.led_driver_fb.configure(text_color=COLOR_OK if is_on else COLOR_OFF)
+            elif topic == "motor/feedback/tmc/status":
+                is_on = val == "on"; self.tmc_pending = False
+                if self.sw_tmc_enable.get() != is_on: self.sw_tmc_enable.select() if is_on else self.sw_tmc_enable.deselect()
+                self.led_tmc_fb.configure(text_color=COLOR_OK if is_on else COLOR_OFF)
+
+        # --- SERVO ---
+        elif parts[0] == 'servo' and len(parts) == 4 and parts[2] == 'feedback':
+            try:
+                ch = int(parts[1]); param = parts[3]
+                if ch in self.servo_ui:
+                    ui = self.servo_ui[ch]
+                    if param == 'angle': ui['lbl_fb_ang'].configure(text=val)
+                    elif param == 'status':
+                        is_on = val == "on"; self.servo_pending[ch] = False
+                        if ui['switch_en'].get() != is_on: ui['switch_en'].select() if is_on else ui['switch_en'].deselect()
+                        ui['led_fb'].configure(text_color=COLOR_OK if is_on else COLOR_OFF)
+                        self.update_led(ui['led_status'], val, False)
+            except ValueError: pass
+
+        # --- SENSOR ---
+        elif parts[0] == 'sensor' and parts[1] == 'feedback':
+            if len(parts) == 3: # Глобальные sensor/feedback/mode...
+                param = parts[2]
+                if param == 'mode': self.lbl_sensor_mode.configure(text=val)
+                elif param == 'mode_id': self.lbl_sensor_mode_id.configure(text=val); self.opt_sensor_mode.set(val)
+                elif param == 'max_range': self.lbl_sensor_max_range.configure(text=val)
+            elif len(parts) == 4: # Канальные sensor/feedback/{ch}/...
+                try:
+                    ch = int(parts[2]); param = parts[3]
+                    if ch in self.sensor_ui:
+                        ui = self.sensor_ui[ch]
+                        if param == 'status':
+                            is_on = val == "on"; self.sensor_pending[ch] = False
+                            if ui['switch_en'].get() != is_on: ui['switch_en'].select() if is_on else ui['switch_en'].deselect()
+                            ui['led_fb'].configure(text_color=COLOR_OK if is_on else COLOR_OFF)
+                        elif param == 'calibrated':
+                            is_cal = val == "true"
+                            ui['led_calibrated'].configure(text_color=COLOR_OK if is_cal else COLOR_OFF)
+                        elif param == 'distance':
+                            if val == "out_of_range":
+                                ui['lbl_dist'].configure(text="Вне диапазона", text_color=COLOR_WARN)
+                            else:
+                                ui['lbl_dist'].configure(text=val, text_color=COLOR_ACTIVE)
+                        elif param == 'raw':
+                            ui['lbl_raw'].configure(text=val, text_color=COLOR_ACTIVE)
+                except ValueError: pass
+
+    # ================= ОБРАБОТЧИКИ СОБЫТИЙ =================
+    def publish(self, topic, payload):
+        if self.client.is_connected(): self.client.publish(topic, str(payload), qos=1)
+
+    def update_status(self, is_online):
+        self.lbl_status.configure(text="● Подключено" if is_online else "● Отключено", text_color=COLOR_OK if is_online else COLOR_ERR)
+
+    def update_led(self, label, val, is_error):
+        is_true = val in ["true", "1", "on"]
+        label.configure(text_color=COLOR_ERR if (is_true and is_error) else (COLOR_OK if is_true else COLOR_OFF))
+
+    # --- Motor Handlers ---
+    def on_rpm_slider_change(self, value):
+        int_val = int(value); self.ent_rpm.delete(0, ctk.END); self.ent_rpm.insert(0, str(int_val))
+        self.lbl_rpm_val.configure(text=str(int_val)); self.publish("motor/control/rpm", int_val)
+    def on_rpm_entry_apply(self, event=None):
+        try:
+            int_val = max(-1000, min(1000, int(self.ent_rpm.get())))
+            self.sld_rpm.set(int_val); self.lbl_rpm_val.configure(text=str(int_val)); self.publish("motor/control/rpm", int_val)
+        except ValueError: self.ent_rpm.delete(0, ctk.END); self.ent_rpm.insert(0, str(int(self.sld_rpm.get())))
+    def on_current_change(self, value):
+        int_val = int(value); self.lbl_cur_val.configure(text=str(int_val)); self.publish("motor/control/tmc/current_percent", int_val)
+    def on_sg_apply(self):
+        val = self.ent_sg.get()
+        if val.isdigit() and 0 <= int(val) <= 255: self.publish("motor/control/tmc/stallguard", int(val))
+    def on_msteps_change(self, choice): self.publish("motor/control/tmc/microsteps", int(choice))
+    def on_reset_steps(self): self.publish("motor/control/totalsteps/reset", "1")
+    def on_driver_change(self):
+        is_on = self.sw_driver.get(); self.driver_pending = True; self.led_driver_fb.configure(text_color=COLOR_PENDING)
+        self.publish("motor/control/driver", "on" if is_on else "off")
+    def on_tmc_enable_change(self):
+        is_on = self.sw_tmc_enable.get(); self.tmc_pending = True; self.led_tmc_fb.configure(text_color=COLOR_PENDING)
+        self.publish("motor/control/tmc/enable", "on" if is_on else "off")
+    def on_stealth_change(self): self.publish("motor/control/tmc/stealthchop", "on" if self.sw_stealth.get() else "off")
+    def on_cool_change(self): self.publish("motor/control/tmc/coolstep", "on" if self.sw_cool.get() else "off")
+
+    # --- Servo Handlers ---
+    def on_servo_ang_slider(self, channel, value):
+        int_val = int(value); ui = self.servo_ui[channel]
+        ui['entry_ang'].delete(0, ctk.END); ui['entry_ang'].insert(0, str(int_val))
+        ui['lbl_ang_val'].configure(text=str(int_val)); self.publish(f"servo/control/{channel}/angle", int_val)
+    def on_servo_ang_entry(self, channel, event=None):
+        ui = self.servo_ui[channel]
+        try:
+            int_val = max(0, min(180, int(ui['entry_ang'].get())))
+            ui['slider_ang'].set(int_val); ui['lbl_ang_val'].configure(text=str(int_val)); self.publish(f"servo/control/{channel}/angle", int_val)
+        except ValueError: ui['entry_ang'].delete(0, ctk.END); ui['entry_ang'].insert(0, str(int(ui['slider_ang'].get())))
+    def on_servo_enable_change(self, channel):
+        ui = self.servo_ui[channel]; is_on = ui['switch_en'].get()
+        self.servo_pending[channel] = True; ui['led_fb'].configure(text_color=COLOR_PENDING)
+        self.publish(f"servo/control/{channel}/enable", "on" if is_on else "off")
+
+    # --- Sensor Handlers ---
+    def on_sensor_mode_change(self, choice):
+        self.publish("sensor/control/mode", int(choice))
+        
+    def on_sensor_publish_all(self):
+        self.publish("sensor/control/publish_all", "1")
+        
+    def on_sensor_enable_change(self, channel):
+        ui = self.sensor_ui[channel]; is_on = ui['switch_en'].get()
+        self.sensor_pending[channel] = True; ui['led_fb'].configure(text_color=COLOR_PENDING)
+        self.publish(f"sensor/control/enable/{channel}", "on" if is_on else "off")
+        
+    def on_sensor_cal_start(self, channel, entry_widget):
+        val = entry_widget.get()
+        if val.isdigit():
+            self.publish(f"sensor/control/calibrate/start/{channel}", int(val))
+            
+    def on_sensor_cal_finish(self, channel, entry_widget):
+        val = entry_widget.get()
+        if val.isdigit():
+            self.publish(f"sensor/control/calibrate/finish/{channel}", int(val))
+            
+    def on_sensor_clear_cal(self, channel):
+        self.publish(f"sensor/control/clear_cal/{channel}", "1")
+
+    def run(self):
+        self.root.mainloop()
+        self.client.loop_stop()
+        self.client.disconnect()
+
+if __name__ == "__main__":
+    app = MotorSCADA()
+    app.run()
--- a/backend_control/img/gui_interface.png
+++ b/backend_control/img/gui_interface.png
--- a/backend_control/img/servo_interface.png
+++ b/backend_control/img/servo_interface.png
--- a/backend_control/requirements.txt
+++ b/backend_control/requirements.txt
@@ -0,0 +1,2 @@
+paho-mqtt
+customtkinter 
--- a/kicad/ozon/.gitignore
+++ b/kicad/ozon/.gitignore
@@ -0,0 +1,2 @@
+*.lck
+.history
--- a/kicad/ozon/.history
+++ b/kicad/ozon/.history
--- a/kicad/ozon/ozon.kicad_pcb
+++ b/kicad/ozon/ozon.kicad_pcb
@@ -0,0 +1,2 @@
+(kicad_pcb (version 20260206) (generator "pcbnew") (generator_version "10.0")
+)
--- a/kicad/ozon/ozon.kicad_prl
+++ b/kicad/ozon/ozon.kicad_prl
@@ -0,0 +1,105 @@
+{
+  "board": {
+    "active_layer": 0,
+    "active_layer_preset": "",
+    "auto_track_width": true,
+    "hidden_netclasses": [],
+    "hidden_nets": [],
+    "high_contrast_mode": 0,
+    "net_color_mode": 1,
+    "opacity": {
+      "images": 0.6,
+      "pads": 1.0,
+      "shapes": 1.0,
+      "tracks": 1.0,
+      "vias": 1.0,
+      "zones": 0.6
+    },
+    "prototype_zone_fills": false,
+    "selection_filter": {
+      "dimensions": true,
+      "footprints": true,
+      "graphics": true,
+      "keepouts": true,
+      "lockedItems": false,
+      "otherItems": true,
+      "pads": true,
+      "text": true,
+      "tracks": true,
+      "vias": true,
+      "zones": true
+    },
+    "visible_items": [
+      "vias",
+      "footprint_text",
+      "footprint_anchors",
+      "ratsnest",
+      "grid",
+      "footprints_front",
+      "footprints_back",
+      "footprint_values",
+      "footprint_references",
+      "tracks",
+      "drc_errors",
+      "drawing_sheet",
+      "bitmaps",
+      "pads",
+      "zones",
+      "drc_warnings",
+      "drc_exclusions",
+      "locked_item_shadows",
+      "conflict_shadows",
+      "shapes",
+      "board_outline_area",
+      "ly_points"
+    ],
+    "visible_layers": "ffffffff_ffffffff_ffffffff_ffffffff",
+    "zone_display_mode": 0
+  },
+  "git": {
+    "integration_disabled": false,
+    "repo_type": "",
+    "repo_username": "",
+    "ssh_key": ""
+  },
+  "meta": {
+    "filename": "ozon.kicad_prl",
+    "version": 5
+  },
+  "net_inspector_panel": {
+    "col_hidden": [],
+    "col_order": [],
+    "col_widths": [],
+    "custom_group_rules": [],
+    "expanded_rows": [],
+    "filter_by_net_name": true,
+    "filter_by_netclass": true,
+    "filter_text": "",
+    "group_by_constraint": false,
+    "group_by_netclass": false,
+    "show_time_domain_details": false,
+    "show_unconnected_nets": false,
+    "show_zero_pad_nets": false,
+    "sort_ascending": true,
+    "sorting_column": -1
+  },
+  "open_jobsets": [],
+  "project": {
+    "files": []
+  },
+  "schematic": {
+    "hierarchy_collapsed": [],
+    "selection_filter": {
+      "graphics": true,
+      "images": true,
+      "labels": true,
+      "lockedItems": false,
+      "otherItems": true,
+      "pins": true,
+      "ruleAreas": true,
+      "symbols": true,
+      "text": true,
+      "wires": true
+    }
+  }
+}
--- a/kicad/ozon/ozon.kicad_pro
+++ b/kicad/ozon/ozon.kicad_pro
@@ -0,0 +1,435 @@
+{
+  "board": {
+    "3dviewports": [],
+    "ipc2581": {
+      "bom_rev": "",
+      "dist": "",
+      "distpn": "",
+      "internal_id": "",
+      "mfg": "",
+      "mpn": "",
+      "sch_revision": ""
+    },
+    "layer_pairs": [],
+    "layer_presets": [],
+    "viewports": []
+  },
+  "boards": [],
+  "component_class_settings": {
+    "assignments": [],
+    "meta": {
+      "version": 0
+    },
+    "sheet_component_classes": {
+      "enabled": false
+    }
+  },
+  "cvpcb": {
+    "equivalence_files": []
+  },
+  "erc": {
+    "erc_exclusions": [],
+    "meta": {
+      "version": 0
+    },
+    "pin_map": [
+      [
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        1,
+        0,
+        0,
+        0,
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+        2
+      ],
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+        2,
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+        1,
+        0,
+        0,
+        1,
+        0,
+        2,
+        2,
+        2,
+        2
+      ],
+      [
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        1,
+        0,
+        1,
+        0,
+        1,
+        2
+      ],
+      [
+        0,
+        1,
+        0,
+        0,
+        0,
+        0,
+        1,
+        1,
+        2,
+        1,
+        1,
+        2
+      ],
+      [
+        0,
+        0,
+        0,
+        0,
+        0,
+        0,
+        1,
+        0,
+        0,
+        0,
+        0,
+        2
+      ],
+      [
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+        0,
+        0,
+        0,
+        0,
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+        0,
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+      [
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+        1,
+        1,
+        1,
+        1,
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+        1,
+        1,
+        1,
+        1,
+        1,
+        2
+      ],
+      [
+        0,
+        0,
+        0,
+        1,
+        0,
+        0,
+        1,
+        0,
+        0,
+        0,
+        0,
+        2
+      ],
+      [
+        0,
+        2,
+        1,
+        2,
+        0,
+        0,
+        1,
+        0,
+        2,
+        2,
+        2,
+        2
+      ],
+      [
+        0,
+        2,
+        0,
+        1,
+        0,
+        0,
+        1,
+        0,
+        2,
+        0,
+        0,
+        2
+      ],
+      [
+        0,
+        2,
+        1,
+        1,
+        0,
+        0,
+        1,
+        0,
+        2,
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+      ],
+      [
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+        2,
+        2,
+        2,
+        2,
+        2,
+        2,
+        2,
+        2,
+        2,
+        2
+      ]
+    ],
+    "rule_severities": {
+      "bus_definition_conflict": "error",
+      "bus_entry_needed": "error",
+      "bus_to_bus_conflict": "error",
+      "bus_to_net_conflict": "error",
+      "different_unit_footprint": "error",
+      "different_unit_net": "error",
+      "duplicate_reference": "error",
+      "duplicate_sheet_names": "error",
+      "endpoint_off_grid": "warning",
+      "extra_units": "error",
+      "field_name_whitespace": "warning",
+      "footprint_filter": "ignore",
+      "footprint_link_issues": "warning",
+      "four_way_junction": "ignore",
+      "ground_pin_not_ground": "warning",
+      "hier_label_mismatch": "error",
+      "isolated_pin_label": "warning",
+      "label_dangling": "error",
+      "label_multiple_wires": "warning",
+      "lib_symbol_issues": "warning",
+      "lib_symbol_mismatch": "warning",
+      "missing_bidi_pin": "warning",
+      "missing_input_pin": "warning",
+      "missing_power_pin": "error",
+      "missing_unit": "warning",
+      "multiple_net_names": "warning",
+      "net_not_bus_member": "warning",
+      "no_connect_connected": "warning",
+      "no_connect_dangling": "warning",
+      "pin_not_connected": "error",
+      "pin_not_driven": "error",
+      "pin_to_pin": "warning",
+      "power_pin_not_driven": "error",
+      "same_local_global_label": "warning",
+      "similar_label_and_power": "warning",
+      "similar_labels": "warning",
+      "similar_power": "warning",
+      "simulation_model_issue": "ignore",
+      "single_global_label": "ignore",
+      "stacked_pin_name": "warning",
+      "unannotated": "error",
+      "unconnected_wire_endpoint": "warning",
+      "undefined_netclass": "error",
+      "unit_value_mismatch": "error",
+      "unresolved_variable": "error",
+      "wire_dangling": "error"
+    }
+  },
+  "libraries": {
+    "pinned_footprint_libs": [],
+    "pinned_symbol_libs": []
+  },
+  "meta": {
+    "filename": "ozon.kicad_pro",
+    "version": 3
+  },
+  "net_settings": {
+    "classes": [
+      {
+        "bus_width": 12,
+        "clearance": 0.2,
+        "diff_pair_gap": 0.25,
+        "diff_pair_via_gap": 0.25,
+        "diff_pair_width": 0.2,
+        "line_style": 0,
+        "microvia_diameter": 0.3,
+        "microvia_drill": 0.1,
+        "name": "Default",
+        "pcb_color": "rgba(0, 0, 0, 0.000)",
+        "priority": 2147483647,
+        "schematic_color": "rgba(0, 0, 0, 0.000)",
+        "track_width": 0.2,
+        "tuning_profile": "",
+        "via_diameter": 0.6,
+        "via_drill": 0.3,
+        "wire_width": 6
+      }
+    ],
+    "meta": {
+      "version": 5
+    },
+    "net_colors": null,
+    "netclass_assignments": null,
+    "netclass_patterns": []
+  },
+  "pcbnew": {
+    "last_paths": {
+      "idf": "",
+      "netlist": "",
+      "plot": "",
+      "specctra_dsn": "",
+      "vrml": ""
+    },
+    "page_layout_descr_file": ""
+  },
+  "schematic": {
+    "annotate_start_num": 0,
+    "annotation": {
+      "method": 0,
+      "sort_order": 0
+    },
+    "bom_export_filename": "${PROJECTNAME}.csv",
+    "bom_fmt_presets": [],
+    "bom_fmt_settings": {
+      "field_delimiter": ",",
+      "keep_line_breaks": false,
+      "keep_tabs": false,
+      "name": "CSV",
+      "ref_delimiter": ",",
+      "ref_range_delimiter": "",
+      "string_delimiter": "\""
+    },
+    "bom_presets": [],
+    "bom_settings": {
+      "exclude_dnp": false,
+      "fields_ordered": [
+        {
+          "group_by": false,
+          "label": "Reference",
+          "name": "Reference",
+          "show": true
+        },
+        {
+          "group_by": false,
+          "label": "Qty",
+          "name": "${QUANTITY}",
+          "show": true
+        },
+        {
+          "group_by": true,
+          "label": "Value",
+          "name": "Value",
+          "show": true
+        },
+        {
+          "group_by": true,
+          "label": "DNP",
+          "name": "${DNP}",
+          "show": true
+        },
+        {
+          "group_by": true,
+          "label": "Exclude from BOM",
+          "name": "${EXCLUDE_FROM_BOM}",
+          "show": true
+        },
+        {
+          "group_by": true,
+          "label": "Exclude from Board",
+          "name": "${EXCLUDE_FROM_BOARD}",
+          "show": true
+        },
+        {
+          "group_by": true,
+          "label": "Footprint",
+          "name": "Footprint",
+          "show": true
+        },
+        {
+          "group_by": false,
+          "label": "Datasheet",
+          "name": "Datasheet",
+          "show": true
+        }
+      ],
+      "filter_string": "",
+      "group_symbols": true,
+      "include_excluded_from_bom": true,
+      "name": "Default Editing",
+      "sort_asc": true,
+      "sort_field": "Обозначение"
+    },
+    "bus_aliases": {},
+    "connection_grid_size": 50.0,
+    "drawing": {
+      "dashed_lines_dash_length_ratio": 12.0,
+      "dashed_lines_gap_length_ratio": 3.0,
+      "default_line_thickness": 6.0,
+      "default_text_size": 50.0,
+      "field_names": [],
+      "hop_over_size_choice": 0,
+      "intersheets_ref_own_page": false,
+      "intersheets_ref_prefix": "",
+      "intersheets_ref_short": false,
+      "intersheets_ref_show": false,
+      "intersheets_ref_suffix": "",
+      "junction_size_choice": 3,
+      "label_size_ratio": 0.375,
+      "operating_point_overlay_i_precision": 3,
+      "operating_point_overlay_i_range": "~A",
+      "operating_point_overlay_v_precision": 3,
+      "operating_point_overlay_v_range": "~V",
+      "overbar_offset_ratio": 1.23,
+      "pin_symbol_size": 25.0,
+      "text_offset_ratio": 0.15
+    },
+    "legacy_lib_dir": "",
+    "legacy_lib_list": [],
+    "meta": {
+      "version": 1
+    },
+    "page_layout_descr_file": "",
+    "plot_directory": "",
+    "reuse_designators": true,
+    "subpart_first_id": 65,
+    "subpart_id_separator": 0,
+    "top_level_sheets": [
+      {
+        "filename": "ozon.kicad_sch",
+        "name": "Корневой лист",
+        "uuid": "8eb30ef0-8ef0-4108-b9d0-4c3ae489af42"
+      }
+    ],
+    "used_designators": "R1,M1-5,#PWR1-10,U1-6",
+    "variants": []
+  },
+  "sheets": [
+    [
+      "8eb30ef0-8ef0-4108-b9d0-4c3ae489af42",
+      "Корневой лист"
+    ]
+  ],
+  "text_variables": {},
+  "tuning_profiles": {
+    "meta": {
+      "version": 0
+    },
+    "tuning_profiles_impedance_geometric": []
+  }
+}
--- a/kicad/ozon/ozon.kicad_sch
+++ b/kicad/ozon/ozon.kicad_sch
--- a/specification/README.md
+++ b/specification/README.md
@@ -0,0 +1,26 @@
+# Наброски будущей схемы конвейера
+
+![](mvp_1.jpg)
+
+## Список материалов:
+
+В этот список необходимо доложить энкодер для двигателя!
+
+| Название | Сумма, ₽  | Количество |
+| :--- | :--- | :--- |
+| Медная лента для удаления припоя / Оплетка для выпайки диаметр 2 мм длина 1.5 м | 164 | 1 |
+| Набор проводов для пайки | 855 | 1 |
+| Флюс гель универсальный безотмывочный, для пайки микросхем и компонентов Flux RMA-223-UV-10г | 162 | 1 |
+| Припой для пайки с канифолью 1мм 50гр ПОС-61 на катушке (ГОСТ) | 423 | 1 |
+| ALIENTEK Паяльник 140 Вт, 7 предметов | 4 985 | 1 |
+| Преобразователь DC-DC понижающий с 8-60V до 1-36V 15A max | 805 | 1 |
+| Беспаечная макетная плата (breadboard) MB-102, 830 точек, для Arduino и прочих устройств | 1 112 | 2 |
+| 120 шт. Провода перемычки для макетных плат, соединительные провода для модулей, контроллеров arduino (10 см) 3 вида по 40 шт папа-папа, мама-мама, папа-мама | 636 | 2 |
+| Homeled, Блок питания, 12V, 200W, 180-265 вольт. С клеммами. Импульсный для светодиодных лент и светильников | 599 | 1 |
+| Сервопривод MG996R, 10 шт, 180 , металлические шестерни, для Arduino, роботов и RC, размеры стандарт | 2 990 | 1 |
+| PWM PCA9685 драйвер на 16 сервоприводов расширитель портов с I2C интерфейсом для Led и Servo (12 bit, I2C) в IIC/I2C/TWI/SPI c тестером сервоприводов 3 режима, набор | 1 178 | 2 |
+| Модуль I2C-мультиплексора CJMCU-9548 на базе TCA9548A / PCA9548A | 532 | 2 |
+| Модуль VL53L0X лазерный дальномер GY-530 (до 2м, питание 3-5В, I2C) | 1064 | 4 |
+| Модуль ESP32 TYPE-C CH340C + плата расширения ESP32 | 1040 | 2 | 
+
+[Ссылка на товары](https://www.ozon.ru/cart?share=wGhPkQd)
--- a/specification/mindmap.md
+++ b/specification/mindmap.md
@@ -0,0 +1,54 @@
+# Алгоритм работы сортировщика
+
+```mermaid
+mindmap
+  root((Алгоритм работы))
+    Этап 1: Ожидание и Движение
+      Arduino запускает шаговый двигатель
+      Лента движется с постоянной скоростью
+    Этап 2: Детекция и Анализ
+      Объект проходит под датчиком и камерой
+      Предмет соответствует габаритам?
+        Да
+          Есть признак круга в сечении?
+            Да - Требуется доупаковка
+              Секция 2
+            Нет - Подходит для сортировки
+              Секция 3
+        Нет
+          Не подходит по габаритам
+            Секция 1
+    Этап 3: Трекинг Синхронизация
+      Arduino отсчитывает шаги двигателя
+      Вычисляется момент времени T
+    Этап 4: Маршрутизация
+      В момент T сервопривод поворачивает барьер на 45°
+      Объект смещается в выбранную зону
+      Сервопривод возвращается в исходное положение
+    Этап 5: Завершение
+      Объект попадает в накопитель
+      Система возвращается в состояние Ожидание
+```
+
+## Блок схема:
+
+
+```mermaid
+flowchart TD
+    Start[Этап 1: Ожидание и Движение] --> Detect[Этап 2: Детекция и Анализ]
+    Detect --> SizeCheck{Предмет соответствует<br/>габаритам?}
+    
+    SizeCheck -->|Нет| Reject[Секция 1:<br/>Не габарит]
+    SizeCheck -->|Да| CircleCheck{Есть признак<br/>круга?}
+    
+    CircleCheck -->|Да| Repack[Секция 2:<br/>Требуется доупаковка]
+    CircleCheck -->|Нет| Sort[Секция 3:<br/>Подходит для сортировки]
+    
+    Reject --> Track[Этап 3: Трекинг]
+    Repack --> Track
+    Sort --> Track
+    
+    Track --> Route[Этап 4: Маршрутизация]
+    Route --> End[Этап 5: Завершение]
+    End --> Start
+```
--- a/specification/mvp_1.drawio
+++ b/specification/mvp_1.drawio
@@ -0,0 +1,277 @@
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+        <mxCell id="jfPUc6vKa1uVjcLF1lrC-38" parent="1" style="shape=note;whiteSpace=wrap;html=1;backgroundOutline=1;darkOpacity=0.05;fillColor=#f0a30a;strokeColor=#BD7000;fillStyle=solid;direction=west;gradientDirection=north;shadow=1;size=20;autosizeText=1;fontFamily=Architects Daughter;fontSource=https://fonts.googleapis.com/css?family=Architects+Daughter;fontColor=#000000;fontSize=26;align=left;" value="Датчик ультразвуковой, определят что объект приехал на сортировку" vertex="1">
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--- a/specification/mvp_1.jpg
+++ b/specification/mvp_1.jpg
--- a/specification/specification.md
+++ b/specification/specification.md
@@ -0,0 +1,97 @@
+Привет! Как инженер-конструктор и эксперт по электронике, я с удовольствием помогу тебе спроектировать этот макет. Задача ясна: создаем систему автоматизированной сортировки с точным управлением скоростью и маршрутизацией по высоте.
+
+Давай разберем твои вопросы по порядку.
+
+### 1. Выбор двигателя: Шаговый vs Коллекторный
+
+Для твоей задачи — **максимально точного выдерживания скорости** и управления с микроконтроллера — выбор очевиден.
+
+| Характеристика | Коллекторный двигатель (DC) | Шаговый двигатель (Stepper) |
+| :--- | :--- | :--- |
+| **Точность скорости** | Низкая. Скорость зависит от напряжения и нагрузки. Для точности нужен энкодер (обратная связь). | **Высокая**. Скорость задается частотой импульсов. Постоянна при заданной нагрузке. |
+| **Управление** | Простое (PWM/ШИМ). | Требует специальный драйвер (например, A4988 или TMC2208). |
+| **Пуск/Стоп** | Плавный разгон, сложно точно позиционировать. | **Идеальный**. Можно точно задать количество шагов и мгновенно остановиться. |
+| **Крутящий момент** | Высокий на высоких оборотах. | Высокий на низких скоростях (идеально для ленты). |
+| **Сложность реализации** | Очень низкая. | Средняя (нужен драйвер и настройка тока). |
+
+**Мой вердикт:** Используй **шаговый двигатель (например, NEMA 17)**. 
+Если ты хочешь «выдерживать скорость максимально точно», обычный DC-мотор тебя разочарует: при увеличении веса объекта на ленте скорость будет падать. Шаговый же двигатель будет поддерживать заданный темп, пока не будет достигнут предел его крутящего момента.
+
+---
+
+### 2. Селекторы (Сервоприводы)
+
+Использование сервоприводов с барьером под 45° — это классическое и эффективное решение для макета. 
+
+**Советы по реализации:**
+*   **Механика:** Чтобы объект не застревал и не «зажевывался», сделай барьер обтекаемым или используй гладкий пластик/алюминий.
+*   **Угол:** 45 градусов — оптимально, но убедись, что при срабатывании сервопривод не толкает объект слишком резко, чтобы тот не перевернулся.
+*   **Логика:** В промышленном подходе, как отмечено в контексте, важно отслеживать «корректность маршрутизации» [1]. Рекомендую добавить в код проверку: действительно ли объект ушел в нужную зону, или произошла ошибка.
+
+---
+
+### 3. Датчик определения высоты
+
+Для измерения высоты объекта сверху, когда лента движется, тебе подойдут три варианта в зависимости от требуемой точности:
+
+1.  **Ультразвуковой датчик (HC-SR04):** Самый дешевый и популярный. 
+    *   *Минус:* Широкий луч (может «цеплять» борта конвейера) и низкая скорость обновления.
+2.  **ИК-датчик расстояния (Sharp GP2Y0A21YK0F):** Более точный, узкий луч.
+    *   *Минус:* Аналоговый сигнал, чувствителен к цвету объекта (черный поглощает ИК).
+3.  **Лазерный ToF-датчик (VL53L0X / VL53L1X):** **Мой выбор для этого проекта.** 
+    *   *Плюсы:* Измеряет время полета фотона (Time-of-Flight), работает независимо от цвета объекта, очень высокая точность (до миллиметров) и очень узкий луч.
+
+---
+
+### Итоговая архитектура (предложение):
+
+*   **Контроллер:** Arduino (Uno или Mega, если планируешь расширять количество датчиков).
+*   **Привод ленты:** Шаговый двигатель NEMA 17 $\rightarrow$ Драйвер A4988/TMC2208 $\rightarrow$ Arduino.
+*   **Сортировка:** 3 $\times$ Сервоприводы SG90 или MG90S (с металлическим редуктором надежнее).
+*   **Датчик высоты:** VL53L0X (I2C интерфейс).
+*   **Питание:** Отдельный блок питания 12В для двигателя и 5В для Arduino/сервоприводов (общий минус/земля).
+
+**Важное замечание из спецификации:** 
+Не забудь предусмотреть в логике категорию «Не подходит для сортировки» [1]. Если датчик зафиксирует объект, который либо слишком высокий, либо слишком низкий (выходит за допустимые габариты), система должна отправить его в отдельный поток или оставить на ленте до конца [1].
+
+Поскольку мы проектируем макет, важно учитывать не только функциональность, но и ограничения, упомянутые в техническом контексте: доступную площадь участка [1], разнообразие форм товаров (включая круглые в сечении) и необходимость бережного обращения с хрупкими или ценными объектами [1].
+
+
+# Сервоприводы с барьером — это надежный вариант, но в зависимости от того, какие объекты вы будете сортировать, рассмотрите следующие альтернативы:
+
+### 1. Электромагнитные толкатели (Solenoids)
+Вместо плавного поворота барьера, соленоид дает резкий линейный толчок.
+*   **Плюсы:** Очень высокая скорость срабатывания, компактность [1].
+*   **Минусы:** Резкий удар. Если ваши объекты хрупкие, этот вариант **не рекомендуется**, так как он противоречит требованию к «мягкости обращения» [1].
+*   **Когда использовать:** Для прочных, тяжелых или однотипных деталей.
+
+### 2. Откидная платформа (Tipping Platform)
+Это участок конвейера, который может наклоняться в сторону или под ним открывается люк.
+*   **Плюсы:** Позволяет перемещать объекты за счет гравитации. Это один из самых бережных способов перемещения, что важно для ценных или хрупких товаров [1].
+*   **Минусы:** Требует более сложной механической интеграции в саму ленту.
+*   **Когда использовать:** Если приоритетом является сохранность объекта и минимизация механических ударов.
+
+### 3. Поворотный диск-распределитель (Rotating Disc)
+В конце основной ленты устанавливается диск, который поворачивается на определенный угол, направляя объект в один из трех лотков.
+*   **Плюсы:** Занимает минимум места (оптимально для ограниченной площади участка [1]). Отлично работает с объектами, имеющими круг в сечении [1].
+*   **Минусы:** Требует точной синхронизации остановки ленты и поворота диска.
+*   **Когда использовать:** Если макет должен быть максимально компактным, а объекты имеют схожую форму (например, цилиндры или сферы).
+
+### 4. Боковой конвейер (Cross-Belt / Diverter)
+Это короткий перпендикулярный отрезок ленты, который включается только тогда, когда объект должен быть сброшен в зону.
+*   **Плюсы:** Самый профессиональный и «мягкий» метод. Идеален для хрупких товаров [1].
+*   **Минусы:** Высокая стоимость и сложность (нужно еще 3 маленьких мотора и дополнительные ленты).
+*   **Когда использовать:** Если вы хотите создать максимально приближенный к реальному промышленному производству макет.
+
+### Сводная таблица для выбора:
+
+| Вариант | Бережность (для хрупких [1]) | Компактность (площадь [1]) | Сложность реализации | Работа с круглыми объектами [1] |
+| :--- | :--- | :--- | :--- | :--- |
+| **Серво-барьер** | Средняя | Высокая | Низкая | Хорошо |
+| **Соленоид** | Низкая | Очень высокая | Низкая | Средне |
+| **Платформа** | Высокая | Средняя | Средняя | Хорошо |
+| **Диск** | Средняя | Очень высокая | Средняя | Идеально |
+| **Боковой конвейер**| Очень высокая | Низкая | Высокая | Хорошо |
+
+**Моя рекомендация:**
+Если вы хотите сохранить простоту управления через Arduino, но при этом учесть требования к бережности и компактности [1], я рекомендую остаться на **сервоприводах**, но изменить конструкцию барьера: вместо «толкателя» сделать **«поворотный желоб»** или **«шлюз»**. Это позволит объекту плавно скатываться в нужную зону, не подвергаясь резким ударам.
--- a/vision_classifier/.gitignore
+++ b/vision_classifier/.gitignore
@@ -0,0 +1,7 @@
+.venv/
+__pycache__/
+*.pyc
+debug_frames/
+*.jpg
+*.png
+.pytest_cache/
--- a/vision_classifier/Dockerfile
+++ b/vision_classifier/Dockerfile
@@ -0,0 +1,23 @@
+# Vision classifier for Intel RealSense D415 on Orange PI (aarch64)
+FROM python:3.11-slim-bookworm
+
+ENV DEBIAN_FRONTEND=noninteractive \
+    PYTHONUNBUFFERED=1 \
+    PIP_NO_CACHE_DIR=1
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        libglib2.0-0 \
+        libgl1 \
+        libv4l-0 \
+        v4l-utils \
+        ffmpeg \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+COPY requirements.txt .
+RUN pip install -r requirements.txt
+
+COPY . .
+
+# Камера пробрасывается через docker-compose (--device)
+CMD ["python", "main.py", "-c", "config.yaml"]
--- a/vision_classifier/INTEGRATION.md
+++ b/vision_classifier/INTEGRATION.md
@@ -0,0 +1,187 @@
+# Полная инструкция: Vision + Arduino + шаговик (трек 3)
+
+Код в `arduino_code/Test` **не меняем**. Связка идёт только через MQTT — те же топики, что уже использует SCADA (`backend_control/gui.py`).
+
+## Архитектура
+
+```
+RealSense D415 ──► Orange PI (vision_classifier)
+                         │
+                         ▼ MQTT
+              ┌──── mosquitto :1883 ────┐
+              │                         │
+              ▼                         ▼
+         ESP32 (уже прошит)        SCADA gui.py
+         • motor/control/*         (опционально)
+         • servo/control/*
+              │
+              ▼
+         TMC2209 + шаговик ленты
+         серво-селекторы зон B/C/D
+```
+
+## 1. Сеть и MQTT (важно)
+
+На Orange PI уже крутится Docker-контейнер **mosquitto** на порту **1883**  
+(логин/пароль: `test` / `1234` — как в SCADA).
+
+| Кто | Куда подключается |
+|-----|-------------------|
+| `vision_classifier` | `127.0.0.1:1883` (уже в `config.yaml`) |
+| SCADA `gui.py` | `192.168.31.225` или `127.0.0.1` |
+| ESP32 (прошивка) | `MQTT_SERVER = "192.168.31.225"` (уже в `arduino_code/Test`) |
+
+Orange PI в сети: **`192.168.31.225`**. Vision ходит на локальный брокер `127.0.0.1`; ESP и SCADA — на `192.168.31.225:1883`.
+
+Краткая шпаргалка запуска/стопа: **[START.md](START.md)**.
+
+Проверка с Orange PI:
+
+```bash
+# локальный брокер на OPI
+python3 -c "
+import paho.mqtt.client as m, time
+c=m.Client(m.CallbackAPIVersion.VERSION2); c.username_pw_set('test','1234')
+c.connect('127.0.0.1',1883); c.loop_start(); time.sleep(0.5); print('MQTT OK'); c.disconnect()
+"
+```
+
+MQTT Explorer: http://localhost:3000 (контейнер `mqtt-explorer`).
+
+## 2. Что уже должно работать на Arduino
+
+Не трогая `arduino_code/Test`, убедитесь что ESP32 в сети и отвечает на команды (через SCADA или mosquitto):
+
+| Действие | Топик | Payload |
+|----------|-------|---------|
+| Вкл. драйвер | `motor/control/driver` | `on` |
+| Вкл. TMC | `motor/control/tmc/enable` | `on` |
+| Ток % | `motor/control/tmc/current_percent` | `50` |
+| Микрошаг | `motor/control/tmc/microsteps` | `16` |
+| Скорость RPM | `motor/control/rpm` | `-200` (у вас направление с минусом; диапазон примерно −1000…1000) |
+| Серво угол | `servo/control/{N}/angle` | `0`…`180` |
+| Серво вкл | `servo/control/{N}/enable` | `on` |
+
+Телеметрия: `motor/feedback/#`, `servo/+/feedback/#`.
+
+Ручной тест ленты (если `mosquitto_pub` есть):
+
+```bash
+mosquitto_pub -h 127.0.0.1 -u test -P 1234 -t motor/control/driver -m on
+mosquitto_pub -h 127.0.0.1 -u test -P 1234 -t motor/control/tmc/enable -m on
+mosquitto_pub -h 127.0.0.1 -u test -P 1234 -t motor/control/rpm -m -200
+# стоп:
+mosquitto_pub -h 127.0.0.1 -u test -P 1234 -t motor/control/rpm -m 0
+```
+
+Или откройте `backend_control/gui.py` (`MQTT_BROKER = "192.168.31.225"`).
+
+## 3. Камера RealSense D415
+
+1. USB3 (скорость 5000M в `lsusb -t`).
+2. Камера **сверху** над лентой, **0.5–1.5 м**.
+3. В `config.yaml` задайте `belt_distance_mm` = реальная высота в мм.
+
+```bash
+lsusb | grep -i RealSense
+v4l2-ctl --list-devices
+```
+
+## 4. Запуск vision (Orange PI)
+
+```bash
+cd ~/workdir/vision_classifier
+
+# один кадр без железа
+./run.sh --once --no-mqtt --no-motor
+
+# превью без движения (JPEG обновляются на диске)
+./run.sh --preview --dry-route --no-motor
+# смотреть: debug_frames/live_color.jpg и live_depth.jpg
+
+# полный контур: камера → класс → MQTT → мотор + серво
+PYTHONUNBUFFERED=1 ./run.sh --preview
+# стоп: Ctrl+C (rpm сбросится в 0)
+```
+
+Превью **не открывает окна** (у вас OpenCV headless) — пишет файлы:
+
+- `debug_frames/live_color.jpg`
+- `debug_frames/live_depth.jpg`
+
+Откройте их в Cursor/VS Code или:
+
+```bash
+eog debug_frames/live_color.jpg &
+# или периодически обновлять в браузере/просмотрщике
+```
+
+## 5. Настройка зон под вашу механику
+
+В `config.yaml` → `routing.zones` и `motor`:
+
+```yaml
+motor:
+  enabled: true
+  rpm: -200         # у вас направление ленты — отрицательный RPM
+
+mqtt:
+  broker: "127.0.0.1"   # mosquitto на Orange PI; ESP и SCADA → 192.168.31.225
+
+routing:
+  zones:
+    B: { servo: 0, idle_angle: 0, divert_angle: 0, hold_ms: 500 }
+    C: { servo: 1, idle_angle: 0, divert_angle: 90, hold_ms: 800 }
+    D: { servo: 2, idle_angle: 0, divert_angle: 90, hold_ms: 800 }
+```
+Подставьте **номера каналов PCA9685** и углы, которые уже проверены в SCADA.
+
+Логика ТЗ:
+
+| Класс | Зона | Действие |
+|-------|------|----------|
+| Подходит | B | лента едет, серво idle |
+| Не по габаритам | C | серво C на `divert_angle`, потом idle |
+| Круг (доупаковка) | D | серво D на `divert_angle`, потом idle |
+
+## 6. SCADA параллельно
+
+Можно держать GUI открытым для телеметрии:
+
+```bash
+cd ~/workdir/backend_control
+# в gui.py: MQTT_BROKER = "192.168.31.225"  (или 127.0.0.1 с OPI)
+source testing/bin/activate   # или свой venv
+python gui.py
+```
+
+Vision и SCADA могут работать вместе на одном брокере.
+
+## 7. Docker (опционально)
+
+```bash
+cd ~/workdir/vision_classifier
+sudo docker compose up -d --build
+sudo docker compose logs -f
+```
+
+## 8. Типичные проблемы
+
+| Симптом | Что сделать |
+|---------|-------------|
+| `cv2.imshow` / GTK error | уже исправлено: `--preview` пишет JPEG |
+| `mqtt timed out` | брокер на OPI → `broker: "127.0.0.1"`; ESP → `192.168.31.225` |
+| ESP не реагирует | одна Wi‑Fi сеть, брокер `192.168.31.225:1883`, логин `test`/`1234` |
+| depth valid < 30% | USB3, высота 0.5–1.5 м, не чёрная лента в упор |
+| серво не те | поправьте `routing.zones.*.servo` под SCADA |
+| лента не едет | `motor.enabled: true`, проверьте SCADA rpm вручную |
+
+## 9. Чеклист «всё связано»
+
+1. [ ] `mosquitto` Up (`docker ps`)
+2. [ ] ESP32 в Wi‑Fi, в MQTT Explorer видны `motor/feedback/*`
+3. [ ] Из SCADA крутится шаговик и двигаются серво
+4. [ ] `config.yaml`: `mqtt.broker` = тот же брокер
+5. [ ] `belt_distance_mm` и углы серво подогнаны
+6. [ ] `./run.sh` печатает зону B/C/D и в Explorer появляются `vision/feedback/*`
+7. [ ] При объекте срабатывает нужный серво, лента крутится
--- a/vision_classifier/README.md
+++ b/vision_classifier/README.md
@@ -0,0 +1,61 @@
+# Vision Classifier — трек 3 (RealSense D415 на Orange PI)
+
+## Правила ТЗ (фиксированные)
+
+1. Габариты строго `>10×10×10` и `<450×320×320` мм → иначе **C**
+2. Иначе если `r_in/r_out ≥ 0.8` (вид сверху **или** ≥2 поперечных среза) → **D**
+3. Иначе → **B**
+
+Стабилизация: медиана 12 кадров + голосование ≥2/3 окна → **LOCK**.  
+После LOCK зона не меняется, пока объект не убрали. Без «достройки» круга на коробках.
+
+**Пограничные случаи:** если консенсуса нет `uncertain_after_frames` кадров
+(ratio у порога 0.8, сторона у лимита 450/320) — товар помечается **«неуверенно»**
+и уходит в безопасную зону (`uncertain_fallback_zone: C`), а не в основной поток.
+Все LOCK-решения пишутся в `logs/decisions.jsonl` (метрики для отчёта: зоны,
+габариты, ratio, доля неуверенных).
+
+## Калибровка (обязательно перед замером габаритов!)
+
+Габариты считаются через фокусное `fx/fy`. Дефолт `670` — расчёт по спецификации
+D415 @ 640×480 (старое значение 430 завышало размеры в ~1.56 раза). Уточнить под
+свою камеру по коробке известного размера (рулеткой, высота коробки ≥ 30 мм):
+
+```bash
+.venv/bin/python calibrate.py --length 300 --width 200
+```
+
+Скрипт сам замерит высоту ленты и запишет `fx/fy` + `belt_distance_mm` в `config.yaml`.
+
+## Фоновая карта глубины
+
+Сегментация умеет работать относительно карты фона (а не одной высоты):
+товар не сливается с платформой/бортами накопителя, а предмет, лежащий
+на другом предмете, выделяется отдельно.
+
+- `main.py`: `use_background_map: true` в конфиге — карта снимается при старте
+  (лента должна быть **пустой**);
+- `demo.py`: кнопка **«Авто-высота»** снимает карту фона (уберите объекты);
+  ручное движение ползунка высоты сбрасывает карту.
+
+## Демо
+
+```bash
+cd vision_classifier
+./demo.sh
+```
+
+Браузер: **http://127.0.0.1:8080/** (Ctrl+F5 после перезапуска)
+
+Ползунки сверху: высота ленты, уверенность, мин. высота, порог круга, площадь.  
+**Авто-высота** — калибровка по пустой ленте. Выход: `Ctrl+C`.
+
+Проверка без камеры:
+
+```bash
+.venv/bin/python test_classify.py
+.venv/bin/python test_geometry.py
+```
+
+**Полный запуск / стоп:** [START.md](START.md)  
+Боевой режим (MQTT + шаговик + серво): [INTEGRATION.md](INTEGRATION.md)
--- a/vision_classifier/START.md
+++ b/vision_classifier/START.md
@@ -0,0 +1,140 @@
+# Полный запуск системы (трек 3)
+
+Orange PI **192.168.31.225** · MQTT `test` / `1234` · RPM ленты **отрицательный** (`-200`)
+
+---
+
+## Стоп (сначала, если что-то уже крутится)
+
+```bash
+# 1) убить vision (иначе снова поднимет ленту)
+pkill -f 'main.py' || true
+
+# 2) остановить мотор
+cd ~/workdir/vision_classifier
+.venv/bin/python - <<'PY'
+from paho.mqtt.client import Client, CallbackAPIVersion
+import time
+c = Client(CallbackAPIVersion.VERSION2, client_id='stop')
+c.username_pw_set('test', '1234')
+c.connect('127.0.0.1', 1883, 60)
+c.loop_start(); time.sleep(0.3)
+c.publish('motor/control/rpm', '0', qos=1)
+time.sleep(0.3); c.loop_stop(); c.disconnect()
+print('rpm=0')
+PY
+```
+
+Или `Ctrl+C` в терминале `main.py` — при выходе сам шлёт `rpm=0`.
+
+---
+
+## Чеклист перед стартом
+
+1. **Питание** конвейера / драйвера / ESP32 включено.
+2. **RealSense D415** в USB3 (`lsusb | grep -i RealSense`).
+3. **Mosquitto** на Orange PI:
+   ```bash
+   docker ps | grep mosquitto
+   # должно быть 0.0.0.0:1883
+   ```
+4. **ESP32** в той же сети, в прошивке `MQTT_SERVER = "192.168.31.225"` (уже так).
+5. Лента под камерой **пустая** (пока не стартовали фон/превью).
+
+---
+
+## Запуск — полный контур (камера → B/C/D → MQTT → лента + серво)
+
+```bash
+cd ~/workdir/vision_classifier
+
+# превью JPEG + мотор + серво (рекомендуется)
+PYTHONUNBUFFERED=1 ./run.sh --preview
+```
+
+Что должно появиться в логе:
+
+```
+[camera] RGB: /dev/video4
+[camera] depth OK, valid≈…
+[mqtt] подключено к 127.0.0.1:1883
+```
+
+После старта vision сам включает драйвер и крутит ленту с `motor.rpm: -200` из `config.yaml`.
+
+### Куда смотреть во время работы
+
+| Что | Где |
+|-----|-----|
+| Кадр RGB | `debug_frames/live_color.jpg` |
+| Depth | `debug_frames/live_depth.jpg` |
+| Решения LOCK | stdout + `logs/decisions.jsonl` |
+| MQTT трафик | http://192.168.31.225:3000 (MQTT Explorer) |
+| Зоны vision | топики `vision/feedback/*` |
+
+Хвост логов:
+
+```bash
+tail -f logs/decisions.jsonl
+# или фильтр по LOCK:
+tail -f logs/decisions.jsonl | while read l; do echo "$l" | .venv/bin/python -c "import sys,json; d=json.loads(sys.stdin.read()); print(d.get('ts'), 'LOCK', d.get('zone'), d.get('dims_mm'), d.get('circle_ratio'), d.get('reason',''))"; done
+```
+
+### Зоны
+
+| LOCK | Смысл | Серво (config) |
+|------|--------|----------------|
+| **B** | подходит | servo 0 idle |
+| **C** | габариты вне 10…450×320×320 | servo 1 → 90° |
+| **D** | круг `ratio ≥ 0.8` | servo 2 → 90° |
+
+Кладите один объект в поле камеры, ждите строку `LOCK B/C/D`.
+
+---
+
+## Запуск без движения ленты (только зрение)
+
+```bash
+cd ~/workdir/vision_classifier
+PYTHONUNBUFFERED=1 ./run.sh --preview --dry-route --no-motor --no-mqtt
+```
+
+JPEG всё равно обновляются в `debug_frames/`.
+
+---
+
+## Ручной тест ленты (без vision)
+
+```bash
+# нужен mosquitto_pub или python из .venv
+mosquitto_pub -h 127.0.0.1 -u test -P 1234 -t motor/control/driver -m on
+mosquitto_pub -h 127.0.0.1 -u test -P 1234 -t motor/control/tmc/enable -m on
+mosquitto_pub -h 127.0.0.1 -u test -P 1234 -t motor/control/rpm -m -200
+# стоп:
+mosquitto_pub -h 127.0.0.1 -u test -P 1234 -t motor/control/rpm -m 0
+```
+
+---
+
+## SCADA (опционально, параллельно)
+
+```bash
+cd ~/workdir/backend_control
+# MQTT_BROKER = "192.168.31.225" или 127.0.0.1
+python gui.py
+```
+
+---
+
+## Если что-то не едет
+
+| Проблема | Действие |
+|----------|----------|
+| Камера занята | `pkill -f main.py`; `fuser /dev/video0` |
+| MQTT не коннектится | `docker ps \| grep mosquitto`, логин `test`/`1234` |
+| ESP молчит | одна Wi‑Fi сеть, брокер **192.168.31.225:1883** |
+| Лента в другую сторону | в `config.yaml` → `motor.rpm: -200` (минус обязателен) |
+| Ложные LOCK на пустой ленте | уберите мусор/блики; при необходимости поднимите `min_object_height_mm` |
+| Серво не те каналы | `routing.zones` в `config.yaml` |
+
+Подробности сети/топиков: [INTEGRATION.md](INTEGRATION.md). Алгоритм: [README.md](README.md).
--- a/vision_classifier/align_color.py
+++ b/vision_classifier/align_color.py
@@ -0,0 +1,139 @@
+#!/usr/bin/env python3
+"""
+Автоподбор совмещения RGB↔depth для демо (сенсоры D415 разнесены).
+
+Положите на ленту коробку с чёткими краями и запустите:
+  .venv/bin/python align_color.py
+
+Скрипт ищет сдвиг (dx, dy) и масштаб цветного кадра, при которых края
+на RGB совпадают с краями на карте глубины, и пишет результат в config.yaml.
+"""
+
+from __future__ import annotations
+
+import argparse
+import re
+import sys
+import time
+from pathlib import Path
+
+import cv2
+import numpy as np
+import yaml
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+
+from camera import RealSenseV4L2
+from demo_hud import align_color
+
+
+def _edges_depth(depth_mm: np.ndarray) -> np.ndarray:
+    d = depth_mm.astype(np.float32)
+    d = cv2.medianBlur(d.astype(np.uint16), 5).astype(np.float32)
+    valid = d > 0
+    if valid.sum() < 1000:
+        return np.zeros(depth_mm.shape, np.uint8)
+    lo, hi = np.percentile(d[valid], [2, 98])
+    norm = np.clip((d - lo) / max(hi - lo, 1.0) * 255.0, 0, 255).astype(np.uint8)
+    return cv2.Canny(norm, 30, 90)
+
+
+def _edges_color(color_bgr: np.ndarray) -> np.ndarray:
+    gray = cv2.cvtColor(color_bgr, cv2.COLOR_BGR2GRAY)
+    # тёмные сцены: выравниваем контраст перед Canny
+    gray = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8, 8)).apply(gray)
+    gray = cv2.GaussianBlur(gray, (5, 5), 0)
+    return cv2.Canny(gray, 40, 120)
+
+
+def _score(color_edges: np.ndarray, depth_band: np.ndarray, dx: float, dy: float, s: float) -> float:
+    warped = align_color(color_edges[..., None].repeat(3, axis=2), dx, dy, s)[..., 0]
+    return float(np.count_nonzero((warped > 0) & (depth_band > 0)))
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Совмещение RGB и depth")
+    parser.add_argument("-c", "--config", default=str(Path(__file__).with_name("config.yaml")))
+    args = parser.parse_args()
+
+    cfg_path = Path(args.config)
+    cfg = yaml.safe_load(cfg_path.read_text(encoding="utf-8"))
+    cam_cfg = cfg["camera"]
+
+    print("[align] открываю камеру… на ленте должна лежать коробка с чёткими краями")
+    cam = RealSenseV4L2(
+        depth_device=cam_cfg.get("depth_device", "/dev/video0"),
+        color_device=cam_cfg.get("color_device", "/dev/video4"),
+        width=int(cam_cfg.get("width", 640)),
+        height=int(cam_cfg.get("height", 480)),
+        fps=int(cam_cfg.get("fps", 30)),
+        use_color=True,
+    )
+    try:
+        # прогрев RGB: первые кадры бывают пустыми, плюс автоэкспозиция
+        for _ in range(30):
+            cam.read()
+            time.sleep(0.05)
+        depth_acc, color_acc = [], []
+        for _ in range(15):
+            pair = cam.read()
+            if pair is not None and not pair.color_is_depth_preview:
+                depth_acc.append(pair.depth_mm.astype(np.float32))
+                color_acc.append(pair.color_bgr.astype(np.float32))
+            time.sleep(0.06)
+        if len(color_acc) < 3:
+            print("[align] RGB не читается — проверьте use_color/USB")
+            return 1
+        depth = np.median(np.stack(depth_acc), axis=0).astype(np.uint16)
+        color = np.clip(np.mean(np.stack(color_acc), axis=0), 0, 255).astype(np.uint8)
+
+        de = _edges_depth(depth)
+        if np.count_nonzero(de) < 500:
+            print("[align] мало краёв на depth — положите коробку в центр кадра")
+            return 1
+        band = cv2.dilate(de, cv2.getStructuringElement(cv2.MORPH_RECT, (7, 7)))
+        ce = _edges_color(color)
+
+        # грубый перебор → уточнение
+        best = (0.0, 0.0, 1.0)
+        best_s = -1.0
+        for s in np.arange(0.90, 1.16, 0.05):
+            for dx in range(-80, 81, 8):
+                for dy in range(-60, 61, 8):
+                    sc = _score(ce, band, dx, dy, float(s))
+                    if sc > best_s:
+                        best_s, best = sc, (float(dx), float(dy), float(s))
+        bdx, bdy, bs = best
+        for s in np.arange(bs - 0.04, bs + 0.045, 0.01):
+            for dx in np.arange(bdx - 8, bdx + 9, 2):
+                for dy in np.arange(bdy - 8, bdy + 9, 2):
+                    sc = _score(ce, band, float(dx), float(dy), float(s))
+                    if sc > best_s:
+                        best_s, best = sc, (float(dx), float(dy), float(s))
+
+        base = _score(ce, band, 0, 0, 1.0)
+        dx, dy, s = best
+        print(f"[align] лучшее совмещение: dx={dx:.0f} dy={dy:.0f} scale={s:.2f} "
+              f"(совпадение краёв {best_s:.0f} против {base:.0f} без коррекции)")
+
+        text = cfg_path.read_text(encoding="utf-8")
+        text = re.sub(r"(?m)^(\s*color_dx:\s*)-?[\d.]+", rf"\g<1>{dx:.1f}", text)
+        text = re.sub(r"(?m)^(\s*color_dy:\s*)-?[\d.]+", rf"\g<1>{dy:.1f}", text)
+        text = re.sub(r"(?m)^(\s*color_scale:\s*)-?[\d.]+", rf"\g<1>{s:.3f}", text)
+        cfg_path.write_text(text, encoding="utf-8")
+        print(f"[align] записано в {cfg_path}")
+
+        # контрольная картинка
+        out = Path("debug_frames"); out.mkdir(exist_ok=True)
+        from camera import depth_colormap
+        aligned = align_color(color, dx, dy, s)
+        vis = cv2.addWeighted(aligned, 0.6, depth_colormap(depth), 0.4, 0)
+        cv2.imwrite(str(out / "align_check.jpg"), vis)
+        print(f"[align] проверка: debug_frames/align_check.jpg")
+    finally:
+        cam.release()
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
--- a/vision_classifier/calibrate.py
+++ b/vision_classifier/calibrate.py
@@ -0,0 +1,182 @@
+#!/usr/bin/env python3
+"""
+Калибровка камеры для точных габаритов (правила ТЗ: >10×10×10, <450×320×320 мм).
+
+Два шага:
+  1) пустая лента → высота belt_distance_mm;
+  2) коробка известного размера в центре → фокусное fx=fy.
+
+Запуск (пример для коробки 300×200 мм, высотой ≥ 30 мм):
+  .venv/bin/python calibrate.py --length 300 --width 200
+
+Результат пишется прямо в config.yaml (fx, fy, belt_distance_mm).
+"""
+
+from __future__ import annotations
+
+import argparse
+import re
+import sys
+import time
+from pathlib import Path
+
+import cv2
+import numpy as np
+import yaml
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+
+from camera import RealSenseV4L2
+from measure import segment_object
+
+
+def _wait_key(prompt: str) -> None:
+    """Ждёт одиночное нажатие: 1 — продолжить, q — выйти (Enter не нужен)."""
+    print(prompt + " [1 — продолжить, q — выйти]", flush=True)
+
+    if not sys.stdin.isatty():
+        # stdin не терминал (пайп/IDE) — читаем строку
+        line = sys.stdin.readline().strip().lower()
+        if line.startswith("q"):
+            raise KeyboardInterrupt
+        return
+
+    import termios
+    import tty
+
+    fd = sys.stdin.fileno()
+    old = termios.tcgetattr(fd)
+    try:
+        tty.setraw(fd)
+        while True:
+            ch = sys.stdin.read(1)
+            if ch in ("1", "\r", "\n"):  # Enter тоже принимаем на всякий случай
+                return
+            if ch in ("q", "Q", "\x03"):  # q или Ctrl+C
+                raise KeyboardInterrupt
+    finally:
+        termios.tcsetattr(fd, termios.TCSADRAIN, old)
+
+
+def _collect_belt(cam: RealSenseV4L2, samples: int = 25) -> float:
+    vals = []
+    for _ in range(samples):
+        pair = cam.read()
+        if pair is None:
+            time.sleep(0.05)
+            continue
+        d = pair.depth_mm
+        h, w = d.shape
+        roi = d[h // 4 : 3 * h // 4, w // 4 : 3 * w // 4]
+        valid = roi[(roi > 200) & (roi < 4000)]
+        if valid.size > 100:
+            vals.append(float(np.median(valid)))
+        time.sleep(0.04)
+    if not vals:
+        raise RuntimeError("Не вижу ленту: проверьте, что камера на 0.5–1.5 м над поверхностью")
+    return float(np.median(vals))
+
+
+def _collect_focal(
+    cam: RealSenseV4L2,
+    belt_mm: float,
+    known_length_mm: float,
+    known_width_mm: float,
+    samples: int = 40,
+) -> float:
+    """fx=fy по площади minAreaRect в пикселях: f = z * sqrt(S_px / S_mm)."""
+    focals = []
+    for _ in range(samples):
+        pair = cam.read()
+        if pair is None:
+            time.sleep(0.05)
+            continue
+        seg = segment_object(pair.depth_mm, belt_distance_mm=belt_mm, min_area_px=400)
+        if seg is None:
+            time.sleep(0.04)
+            continue
+        mask, contour = seg
+        ys, xs = np.where(mask > 0)
+        z = pair.depth_mm[ys, xs].astype(np.float32)
+        z = z[z > 0]
+        if z.size < 100:
+            continue
+        z_med = float(np.median(z))
+
+        rect = cv2.minAreaRect(contour)
+        pw, ph = rect[1]
+        if pw < 10 or ph < 10:
+            continue
+        f = z_med * float(np.sqrt((pw * ph) / (known_length_mm * known_width_mm)))
+        focals.append(f)
+        time.sleep(0.04)
+    if len(focals) < 10:
+        raise RuntimeError(
+            f"Стабильно вижу коробку только в {len(focals)} кадрах из {samples}. "
+            "Коробка должна быть высотой ≥ 30 мм и лежать в центре кадра."
+        )
+    return float(np.median(focals))
+
+
+def _patch_config(path: Path, fx: float, belt_mm: float) -> None:
+    text = path.read_text(encoding="utf-8")
+    text = re.sub(r"(?m)^(\s*fx:\s*)[\d.]+", rf"\g<1>{fx:.1f}", text)
+    text = re.sub(r"(?m)^(\s*fy:\s*)[\d.]+", rf"\g<1>{fx:.1f}", text)
+    text = re.sub(r"(?m)^(belt_distance_mm:\s*)[\d.]+", rf"\g<1>{belt_mm:.0f}", text)
+    path.write_text(text, encoding="utf-8")
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Калибровка fx/fy и высоты ленты")
+    parser.add_argument("-c", "--config", default=str(Path(__file__).with_name("config.yaml")))
+    parser.add_argument("--length", type=float, required=True, help="Длина коробки, мм (рулеткой)")
+    parser.add_argument("--width", type=float, required=True, help="Ширина коробки, мм (рулеткой)")
+    parser.add_argument("--yes", action="store_true", help="Не ждать Enter (сцена уже готова на каждом шаге)")
+    args = parser.parse_args()
+
+    cfg_path = Path(args.config)
+    cfg = yaml.safe_load(cfg_path.read_text(encoding="utf-8"))
+    cam_cfg = cfg["camera"]
+
+    print("[calib] открываю RealSense D415…")
+    cam = RealSenseV4L2(
+        depth_device=cam_cfg.get("depth_device", "/dev/video0"),
+        color_device=cam_cfg.get("color_device", "/dev/video4"),
+        width=int(cam_cfg.get("width", 640)),
+        height=int(cam_cfg.get("height", 480)),
+        fps=int(cam_cfg.get("fps", 30)),
+        depth_scale_mm=float(cam_cfg.get("depth_scale_mm", 1.0)),
+        use_color=False,
+    )
+    try:
+        if not args.yes:
+            _wait_key("[calib] Шаг 1/2: УБЕРИТЕ всё с ленты")
+        belt_mm = _collect_belt(cam)
+        print(f"[calib] высота до ленты: {belt_mm:.0f} мм")
+
+        if not args.yes:
+            _wait_key(
+                f"[calib] Шаг 2/2: положите коробку {args.length:.0f}×{args.width:.0f} мм "
+                "в центр кадра"
+            )
+            time.sleep(1.0)
+        fx = _collect_focal(cam, belt_mm, args.length, args.width)
+        old_fx = float(cam_cfg.get("fx", 0))
+        print(f"[calib] фокусное fx=fy: {fx:.1f} (было {old_fx:.1f})")
+        if old_fx > 0:
+            k = fx / old_fx
+            print(f"[calib] габариты со старым fx были завышены/занижены в {k:.2f} раза")
+
+        _patch_config(cfg_path, fx, belt_mm)
+        print(f"[calib] записано в {cfg_path}: fx=fy={fx:.1f}, belt_distance_mm={belt_mm:.0f}")
+        print("[calib] проверьте: .venv/bin/python demo.py — размеры LWH должны совпадать с рулеткой")
+    except KeyboardInterrupt:
+        print("\n[calib] отменено, config.yaml не изменён")
+        return 1
+    finally:
+        cam.release()
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
--- a/vision_classifier/camera.py
+++ b/vision_classifier/camera.py
@@ -0,0 +1,373 @@
+"""Захват Depth (+опционально Color) с Intel RealSense D415 через V4L2/ffmpeg.
+
+Классификация по ТЗ опирается на depth (габариты + круг в сечении).
+RGB у D415 через сырой V4L2 часто пустой без librealsense —
+тогда для превью используется colorize(depth).
+"""
+
+from __future__ import annotations
+
+import shutil
+import subprocess
+import threading
+import time
+from dataclasses import dataclass
+from typing import Optional, Union
+
+import cv2
+import numpy as np
+
+
+@dataclass
+class FramePair:
+    color_bgr: np.ndarray
+    depth_mm: np.ndarray  # uint16, миллиметры
+    timestamp_ms: float
+    color_is_depth_preview: bool = False
+
+
+def _device_path(device: Union[str, int]) -> str:
+    if isinstance(device, int) or str(device).isdigit():
+        return f"/dev/video{int(device)}"
+    return str(device)
+
+
+def _v4l2_index(device: Union[str, int]) -> int:
+    if isinstance(device, int):
+        return device
+    s = str(device).strip()
+    if s.isdigit():
+        return int(s)
+    if "video" in s:
+        return int(s.rsplit("video", 1)[-1])
+    raise ValueError(f"Некорректный V4L2 device: {device}")
+
+
+def find_realsense_color_device(preferred: Union[str, int, None] = None) -> Optional[str]:
+    """Найти RGB-ноду D415 (YUYV). Номера /dev/videoN плавают после переподключения."""
+    import glob
+    import os
+
+    def _formats(path: str) -> str:
+        try:
+            return subprocess.check_output(
+                ["v4l2-ctl", "-d", path, "--list-formats-ext"],
+                stderr=subprocess.DEVNULL,
+                text=True,
+                timeout=2,
+            )
+        except (OSError, subprocess.SubprocessError):
+            return ""
+
+    preferred_path = _device_path(preferred) if preferred is not None else ""
+    scored: list[tuple[int, str]] = []
+    for path in sorted(glob.glob("/dev/video*")):
+        if not os.path.exists(path):
+            continue
+        fmt = _formats(path)
+        if "Z16" in fmt or "'GREY'" in fmt or "Greyscale" in fmt:
+            continue
+        score = 2 if ("YUYV" in fmt or "MJPG" in fmt or "Motion-JPEG" in fmt) else 0
+        if path == preferred_path:
+            score += 5
+        scored.append((score, path))
+    scored.sort(key=lambda x: (-x[0], x[1]))
+
+    for _, path in scored:
+        try:
+            idx = _v4l2_index(path)
+        except ValueError:
+            continue
+        cap = cv2.VideoCapture(idx, cv2.CAP_V4L2)
+        if not cap.isOpened():
+            continue
+        ok_frame = None
+        for _ in range(12):
+            ok, frame = cap.read()
+            if not ok or frame is None:
+                continue
+            if frame.ndim == 2:
+                break
+            if frame.ndim == 3 and frame.shape[2] == 2:
+                frame = cv2.cvtColor(frame, cv2.COLOR_YUV2BGR_YUY2)
+            if frame.ndim == 3 and float(np.mean(frame)) > 8.0 and float(np.std(frame)) > 5.0:
+                ok_frame = frame
+                break
+        cap.release()
+        if ok_frame is not None:
+            return path
+    return None
+
+
+def fill_depth_holes(depth_mm: np.ndarray, ksize: int = 5) -> np.ndarray:
+    """Простое заполнение дыр в depth."""
+    d = depth_mm.copy()
+    mask = (d > 0).astype(np.uint8) * 255
+    if mask.mean() < 1:
+        return d
+    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (ksize, ksize))
+    closed = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
+    holes = ((closed > 0) & (d == 0)).astype(np.uint8) * 255
+    if holes.any():
+        scale = max(float(d.max()), 1.0)
+        img8 = np.clip(d.astype(np.float32) / scale * 255.0, 0, 255).astype(np.uint8)
+        filled8 = cv2.inpaint(img8, holes, 3, cv2.INPAINT_TELEA)
+        filled = (filled8.astype(np.float32) / 255.0 * scale).astype(np.uint16)
+        d[holes > 0] = filled[holes > 0]
+    med = cv2.medianBlur(d, 3)
+    valid = d > 0
+    d[valid] = med[valid]
+    return d
+
+
+def depth_colormap(depth_mm: np.ndarray, max_mm: Optional[int] = None) -> np.ndarray:
+    valid = depth_mm[(depth_mm > 0) & (depth_mm < 10000)]
+    if max_mm is None:
+        max_mm = int(np.percentile(valid, 95)) if valid.size else 2000
+        max_mm = max(max_mm, 500)
+    clipped = np.clip(depth_mm.astype(np.float32), 0, max_mm)
+    norm = np.zeros_like(clipped, dtype=np.uint8)
+    mask = depth_mm > 0
+    norm[mask] = (clipped[mask] / max_mm * 255.0).astype(np.uint8)
+    return cv2.applyColorMap(norm, cv2.COLORMAP_JET)
+
+
+class RealSenseV4L2:
+    """D415: depth=/dev/video0 (Z16 gray16le). Color опционален."""
+
+    def __init__(
+        self,
+        depth_device: Union[str, int] = "/dev/video0",
+        color_device: Union[str, int] = "/dev/video4",
+        width: int = 640,
+        height: int = 480,
+        fps: int = 30,
+        depth_scale_mm: float = 1.0,
+        use_color: bool = True,
+    ) -> None:
+        if shutil.which("ffmpeg") is None:
+            raise RuntimeError("Нужен ffmpeg для чтения depth Z16 с RealSense")
+
+        self.depth_scale_mm = float(depth_scale_mm)
+        self.width = int(width)
+        self.height = int(height)
+        self.fps = int(fps)
+        self.use_color = bool(use_color)
+        self._frame_bytes = self.width * self.height * 2
+        self.color_cap = None
+        self._depth_path = _device_path(depth_device)
+        self._lock = threading.Lock()
+        self._latest: Optional[np.ndarray] = None
+        self._stop = threading.Event()
+        self._ff: Optional[subprocess.Popen] = None
+        self._thread: Optional[threading.Thread] = None
+
+        self._start_depth_worker()
+
+        if self.use_color:
+            found = find_realsense_color_device(color_device)
+            if found is None:
+                print(f"[camera] RGB не найден (искали {color_device}) — в вебе будет colorize(depth)")
+                self.color_cap = None
+            else:
+                if _device_path(found) != _device_path(color_device):
+                    print(f"[camera] RGB: {found} (в конфиге было {color_device})")
+                else:
+                    print(f"[camera] RGB: {found}")
+                color_idx = _v4l2_index(found)
+                self.color_cap = cv2.VideoCapture(color_idx, cv2.CAP_V4L2)
+                if self.color_cap.isOpened():
+                    self.color_cap.set(cv2.CAP_PROP_FRAME_WIDTH, self.width)
+                    self.color_cap.set(cv2.CAP_PROP_FRAME_HEIGHT, self.height)
+                    self.color_cap.set(cv2.CAP_PROP_FPS, self.fps)
+                    self.color_cap.set(cv2.CAP_PROP_CONVERT_RGB, 1)
+                    # прогрев автоэкспозиции — иначе первые кадры чёрные/зелёные
+                    for _ in range(20):
+                        self.color_cap.read()
+                else:
+                    print("[camera] RGB VideoCapture не открылся")
+                    self.color_cap = None
+
+        # Ждём первый кадр
+        deadline = time.time() + 5.0
+        while time.time() < deadline:
+            with self._lock:
+                if self._latest is not None:
+                    break
+            time.sleep(0.05)
+        else:
+            self.release()
+            raise RuntimeError(
+                f"Не удалось читать depth с {self._depth_path}. "
+                "Проверьте USB3, что камера не занята другим процессом."
+            )
+
+        valid_pct = float(((self._latest > 0) & (self._latest < 5000)).mean() * 100)
+        print(f"[camera] depth OK, valid≈{valid_pct:.1f}% (лучше >30%; высота камеры 0.5–1.5 м)")
+
+    def _start_depth_worker(self) -> None:
+        self._ff = subprocess.Popen(
+            [
+                "ffmpeg",
+                "-hide_banner",
+                "-loglevel",
+                "error",
+                "-fflags",
+                "nobuffer",
+                "-flags",
+                "low_delay",
+                "-f",
+                "v4l2",
+                "-video_size",
+                f"{self.width}x{self.height}",
+                "-framerate",
+                str(self.fps),
+                "-pixel_format",
+                "gray16le",
+                "-i",
+                self._depth_path,
+                "-f",
+                "rawvideo",
+                "-pix_fmt",
+                "gray16le",
+                "-",
+            ],
+            stdout=subprocess.PIPE,
+            stderr=subprocess.DEVNULL,
+            bufsize=self._frame_bytes * 8,
+        )
+        self._thread = threading.Thread(target=self._depth_loop, name="rs-depth", daemon=True)
+        self._thread.start()
+
+    def _depth_loop(self) -> None:
+        assert self._ff is not None and self._ff.stdout is not None
+        while not self._stop.is_set():
+            raw = self._ff.stdout.read(self._frame_bytes)
+            if not raw or len(raw) != self._frame_bytes:
+                if self._ff.poll() is not None:
+                    break
+                continue
+            depth = np.frombuffer(raw, dtype="<u2").reshape(self.height, self.width).copy()
+            depth[depth == 65535] = 0
+            if self.depth_scale_mm != 1.0:
+                depth = np.clip(depth.astype(np.float32) * self.depth_scale_mm, 0, 65535).astype(np.uint16)
+            depth = fill_depth_holes(depth)
+            with self._lock:
+                self._latest = depth
+
+    def _read_color(self, depth_mm: np.ndarray) -> tuple[np.ndarray, bool]:
+        if self.color_cap is not None:
+            ok, color = self.color_cap.read()
+            if ok and color is not None:
+                if color.shape[:2] != (self.height, self.width):
+                    color = cv2.resize(color, (self.width, self.height), interpolation=cv2.INTER_LINEAR)
+                if color.ndim == 3 and color.shape[2] == 2:
+                    color = cv2.cvtColor(color, cv2.COLOR_YUV2BGR_YUY2)
+                elif color.ndim == 2:
+                    color = cv2.cvtColor(color, cv2.COLOR_GRAY2BGR)
+                # пустой YUYV-кадр после конвертации — ровный зелёный (mean>5,
+                # но вариации нет) → проверяем и разброс пикселей
+                if float(np.mean(color)) > 5.0 and float(np.std(color)) > 4.0:
+                    return color, False
+        return depth_colormap(depth_mm), True
+
+    def read(self) -> Optional[FramePair]:
+        with self._lock:
+            depth = None if self._latest is None else self._latest.copy()
+        if depth is None:
+            return None
+        color, is_preview = self._read_color(depth)
+        return FramePair(
+            color_bgr=color,
+            depth_mm=depth,
+            timestamp_ms=time.time() * 1000.0,
+            color_is_depth_preview=is_preview,
+        )
+
+    def capture_background(self, samples: int = 15) -> np.ndarray:
+        """Медианная карта глубины пустой сцены (лента + платформы/борта).
+
+        Позволяет сегментировать товар на неровном фоне и не сливать его
+        с накопителем: объект = то, что ближе фона на min_object_height_mm.
+        """
+        frames = []
+        deadline = time.time() + 12.0
+        while len(frames) < samples and time.time() < deadline:
+            pair = self.read()
+            if pair is not None:
+                frames.append(pair.depth_mm.astype(np.float32))
+            time.sleep(0.04)
+        if len(frames) < max(3, samples // 3):
+            raise RuntimeError("Не удалось накопить кадры для фоновой карты")
+        stack = np.stack(frames)
+        stack[stack <= 0] = np.nan
+        bg = np.nanmedian(stack, axis=0)
+        return np.nan_to_num(bg, nan=0.0).astype(np.uint16)
+
+    def capture_background_rgb(self, samples: int = 10) -> Optional[np.ndarray]:
+        """Усреднённый RGB-кадр пустой сцены — для детекции плоских товаров
+        (телефон и т.п.), которые не видны в depth."""
+        frames = []
+        deadline = time.time() + 8.0
+        while len(frames) < samples and time.time() < deadline:
+            pair = self.read()
+            if pair is not None and not pair.color_is_depth_preview:
+                frames.append(pair.color_bgr.astype(np.float32))
+            time.sleep(0.04)
+        if len(frames) < 3:
+            return None
+        return np.clip(np.mean(np.stack(frames), axis=0), 0, 255).astype(np.uint8)
+
+    def estimate_belt_distance_mm(self, samples: int = 30) -> float:
+        vals = []
+        h, w = self.height, self.width
+        rois = [
+            (h // 2 - 40, h // 2 + 40, w // 2 - 60, w // 2 + 60),
+            (h // 3 - 30, h // 3 + 30, w // 3 - 40, w // 3 + 40),
+            (2 * h // 3 - 30, 2 * h // 3 + 30, 2 * w // 3 - 40, 2 * w // 3 + 40),
+            (h // 4, 3 * h // 4, w // 4, 3 * w // 4),
+        ]
+        for _ in range(samples):
+            pair = self.read()
+            if pair is None:
+                time.sleep(0.03)
+                continue
+            for y0, y1, x0, x1 in rois:
+                roi = pair.depth_mm[y0:y1, x0:x1]
+                valid = roi[(roi > 200) & (roi < 4000)]
+                if valid.size >= 50:
+                    vals.append(float(np.median(valid)))
+                    break
+            else:
+                valid = pair.depth_mm[(pair.depth_mm > 200) & (pair.depth_mm < 4000)]
+                if valid.size >= 50:
+                    vals.append(float(np.median(valid)))
+            time.sleep(0.03)
+        if not vals:
+            raise RuntimeError(
+                "Не удалось оценить belt_distance_mm. "
+                "Поставьте камеру на 0.5–1.5 м над лентой (USB3), задайте belt_distance_mm в config.yaml вручную."
+            )
+        return float(np.median(vals))
+
+    def release(self) -> None:
+        self._stop.set()
+        if self.color_cap is not None:
+            self.color_cap.release()
+            self.color_cap = None
+        if self._ff is not None and self._ff.poll() is None:
+            self._ff.terminate()
+            try:
+                self._ff.wait(timeout=2)
+            except subprocess.TimeoutExpired:
+                self._ff.kill()
+            self._ff = None
+        if self._thread is not None:
+            self._thread.join(timeout=2)
+            self._thread = None
+
+    def __enter__(self) -> "RealSenseV4L2":
+        return self
+
+    def __exit__(self, *args) -> None:
+        self.release()
--- a/vision_classifier/classify.py
+++ b/vision_classifier/classify.py
@@ -0,0 +1,147 @@
+"""Классификация строго по правилам ТЗ трека 3."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from enum import Enum
+from typing import Sequence, Tuple
+
+from measure import ObjectMeasurement
+
+
+class Category(str, Enum):
+    SUITABLE = "suitable"      # Подходит для сортировки → B
+    OVERSIZE = "oversize"      # Не подходит по габаритам → C
+    NEED_PACK = "need_pack"    # Не подходит без доупаковки → D
+
+    @property
+    def zone(self) -> str:
+        return {
+            Category.SUITABLE: "B",
+            Category.OVERSIZE: "C",
+            Category.NEED_PACK: "D",
+        }[self]
+
+    @property
+    def ru_label(self) -> str:
+        return {
+            Category.SUITABLE: "Подходит для сортировки",
+            Category.OVERSIZE: "Не подходит для сортировки по габаритам",
+            Category.NEED_PACK: "Не подходит для сортировки без доупаковки",
+        }[self]
+
+    @property
+    def short_label(self) -> str:
+        """Короткая метка для HUD и веб-статуса."""
+        return {
+            Category.SUITABLE: "ГОТОВ К СОРТИРОВКЕ",
+            Category.OVERSIZE: "НЕГАБАРИТ",
+            Category.NEED_PACK: "ТРЕБУЕТ ДОУПАКОВКИ",
+        }[self]
+
+
+@dataclass
+class ClassificationResult:
+    category: Category
+    dims_sorted_mm: Tuple[float, float, float]
+    circle_ratio: float
+    passes_size: bool
+    is_circular: bool
+    reason: str
+
+
+def _sorted_dims(length: float, width: float, height: float) -> Tuple[float, float, float]:
+    a, b, c = sorted([float(length), float(width), float(height)], reverse=True)
+    return a, b, c
+
+
+def check_size(
+    dims_sorted: Sequence[float],
+    min_mm: Sequence[float],
+    max_mm: Sequence[float],
+) -> bool:
+    """
+    ТЗ: габариты строго больше минимума и строго меньше максимума
+    по сопоставленным сторонам после сортировки.
+    """
+    min_s = sorted([float(x) for x in min_mm], reverse=True)
+    max_s = sorted([float(x) for x in max_mm], reverse=True)
+    d = [float(x) for x in dims_sorted]
+    return all(d[i] > min_s[i] for i in range(3)) and all(d[i] < max_s[i] for i in range(3))
+
+
+def classify(
+    measurement: ObjectMeasurement,
+    min_mm: Sequence[float] = (10, 10, 10),
+    max_mm: Sequence[float] = (450, 320, 320),
+    circle_ratio_threshold: float = 0.8,
+) -> ClassificationResult:
+    """
+    Порядок ТЗ:
+    1) габариты → иначе C (приоритет над кругом)
+    2) если r_in/r_out >= 0.8 в любом сечении → D
+    3) иначе → B
+    """
+    dims = _sorted_dims(measurement.length_mm, measurement.width_mm, measurement.height_mm)
+    passes = check_size(dims, min_mm, max_mm)
+    ratio = float(measurement.circle_ratio)
+    circular = ratio >= float(circle_ratio_threshold)
+    clipped = bool(getattr(measurement, "clipped_by_frame", False))
+
+    if not passes or clipped:
+        reason = (
+            "объект обрезан краем кадра → габарит неполный, считаем негабаритом"
+            if clipped and passes
+            else "габариты вне допуска: нужно >10×10×10 и <450×320×320 мм"
+        )
+        if clipped and not passes:
+            reason = "габариты вне допуска (в т.ч. обрезан кадром): нужно >10×10×10 и <450×320×320 мм"
+        return ClassificationResult(
+            category=Category.OVERSIZE,
+            dims_sorted_mm=dims,
+            circle_ratio=ratio,
+            passes_size=False,
+            is_circular=circular,
+            reason=reason,
+        )
+
+    if circular:
+        return ClassificationResult(
+            category=Category.NEED_PACK,
+            dims_sorted_mm=dims,
+            circle_ratio=ratio,
+            passes_size=True,
+            is_circular=True,
+            reason=f"круг в сечении: r_in/r_out={ratio:.3f} >= {circle_ratio_threshold}",
+        )
+
+    return ClassificationResult(
+        category=Category.SUITABLE,
+        dims_sorted_mm=dims,
+        circle_ratio=ratio,
+        passes_size=True,
+        is_circular=False,
+        reason=f"габариты OK, круга нет: r_in/r_out={ratio:.3f} < {circle_ratio_threshold}",
+    )
+
+
+def classify_from_dims(
+    length_mm: float,
+    width_mm: float,
+    height_mm: float,
+    circle_ratio: float,
+    min_mm: Sequence[float] = (10, 10, 10),
+    max_mm: Sequence[float] = (450, 320, 320),
+    circle_ratio_threshold: float = 0.8,
+) -> ClassificationResult:
+    fake = ObjectMeasurement(
+        length_mm=length_mm,
+        width_mm=width_mm,
+        height_mm=height_mm,
+        circle_ratio=circle_ratio,
+        area_px=0,
+        centroid_px=(0, 0),
+        contour=None,  # type: ignore
+        mask=None,  # type: ignore
+    )
+    return classify(fake, min_mm, max_mm, circle_ratio_threshold)
--- a/vision_classifier/collect_log.py
+++ b/vision_classifier/collect_log.py
@@ -0,0 +1,151 @@
+#!/usr/bin/env python3
+"""
+Сбор логов классификации с камеры.
+Кладите предметы по очереди — пишет CSV + печатает сводку.
+
+  .venv/bin/python collect_log.py
+  # Ctrl+C — стоп
+"""
+
+from __future__ import annotations
+
+import csv
+import sys
+import time
+from datetime import datetime
+from pathlib import Path
+
+import yaml
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+
+from camera import RealSenseV4L2
+from measure import measure_object, segment_object
+from stabilize import DecisionStabilizer
+
+
+def main() -> int:
+    cfg = yaml.safe_load(Path("config.yaml").read_text(encoding="utf-8"))
+    cam_cfg = cfg["camera"]
+    cls = cfg["classification"]
+    thr = float(cls.get("circle_ratio_threshold", 0.8))
+
+    out_dir = Path("debug_frames")
+    out_dir.mkdir(exist_ok=True)
+    stamp = datetime.now().strftime("%H%M%S")
+    csv_path = out_dir / f"log_{stamp}.csv"
+
+    cam = RealSenseV4L2(
+        depth_device=cam_cfg.get("depth_device", "/dev/video0"),
+        color_device=cam_cfg.get("color_device", "/dev/video4"),
+        width=int(cam_cfg.get("width", 640)),
+        height=int(cam_cfg.get("height", 480)),
+        fps=int(cam_cfg.get("fps", 30)),
+        depth_scale_mm=float(cam_cfg.get("depth_scale_mm", 1.0)),
+        use_color=False,
+    )
+    belt = float(cfg.get("belt_distance_mm") or 600)
+    print(f"[log] belt={belt:.0f} mm  thr={thr}  → {csv_path}")
+    print("[log] Кладите КРУГ / ПРЯМОУГОЛЬНИК. Ctrl+C — стоп.\n")
+
+    stab = DecisionStabilizer(window=12, confirm_frames=8, lost_frames=12, enter_circle=thr)
+    fx, fy = float(cam_cfg["fx"]), float(cam_cfg["fy"])
+    cx, cy = float(cam_cfg["cx"]), float(cam_cfg["cy"])
+
+    f = csv_path.open("w", newline="", encoding="utf-8")
+    w = csv.writer(f)
+    w.writerow(
+        [
+            "t",
+            "present",
+            "L",
+            "W",
+            "H",
+            "top",
+            "sec",
+            "circle",
+            "raw_zone",
+            "lock",
+            "lock_zone",
+            "conf",
+        ]
+    )
+
+    last_print = 0.0
+    n = 0
+    try:
+        while True:
+            pair = cam.read()
+            if pair is None:
+                time.sleep(0.02)
+                continue
+            n += 1
+            seg = segment_object(
+                pair.depth_mm,
+                belt_distance_mm=belt,
+                belt_tolerance_mm=float(cfg.get("belt_tolerance_mm", 25)),
+                min_object_height_mm=float(cfg.get("min_object_height_mm", 5)),
+                min_area_px=int(cfg.get("min_object_area_px", 400)),
+            )
+            m = None
+            if seg is not None:
+                mask, contour = seg
+                m = measure_object(
+                    pair.depth_mm, mask, contour, belt, fx, fy, cx, cy
+                )
+
+            d = stab.update(
+                m,
+                min_mm=cls.get("min_mm", [10, 10, 10]),
+                max_mm=cls.get("max_mm", [450, 320, 320]),
+            )
+
+            if m is None:
+                raw_zone = "-"
+                row = [time.time(), 0, "", "", "", "", "", "", raw_zone, int(d.locked), "", d.confidence_pct]
+            else:
+                dims = sorted([m.length_mm, m.width_mm, m.height_mm], reverse=True)
+                raw = "C"
+                if all(dims[i] > 10 and dims[i] < [450, 320, 320][i] for i in range(3)):
+                    raw = "D" if m.circle_ratio >= thr else "B"
+                lz = d.result.category.zone if (d.locked and d.result) else ""
+                row = [
+                    time.time(),
+                    1,
+                    round(dims[0], 1),
+                    round(dims[1], 1),
+                    round(dims[2], 1),
+                    round(m.top_ratio, 3),
+                    round(m.section_ratio, 3),
+                    round(m.circle_ratio, 3),
+                    raw,
+                    int(d.locked),
+                    lz,
+                    d.confidence_pct,
+                ]
+            w.writerow(row)
+            if n % 5 == 0:
+                f.flush()
+
+            now = time.time()
+            if now - last_print > 0.45:
+                last_print = now
+                if m is None:
+                    print(f"[{n:05d}] пусто")
+                else:
+                    lz = d.result.category.zone if (d.locked and d.result) else "…"
+                    print(
+                        f"[{n:05d}] raw={row[8]} lock={lz or '—':1s} conf={d.confidence_pct:3d}% | "
+                        f"LWH={row[2]:.0f}×{row[3]:.0f}×{row[4]:.0f} | "
+                        f"top={m.top_ratio:.3f} sec={m.section_ratio:.3f} circ={m.circle_ratio:.3f}"
+                    )
+    except KeyboardInterrupt:
+        print(f"\n[log] сохранено {csv_path}")
+    finally:
+        f.close()
+        cam.release()
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
--- a/vision_classifier/config.yaml
+++ b/vision_classifier/config.yaml
@@ -0,0 +1,110 @@
+# Конфиг алгоритмической части трека 3 (RealSense D415 → классификация → MQTT)
+
+camera:
+  depth_device: /dev/video0
+  color_device: /dev/video4
+  width: 640
+  height: 480
+  fps: 30
+  depth_scale_mm: 1.0
+  # Intrinsics депта D415 @ 640x480 (кроп 4:3 из 1280x720, HFOV 65°): fx=fy≈670.
+  # Старое значение 430 завышало габариты в ~1.56 раза!
+  # Уточнить под свою камеру: .venv/bin/python calibrate.py --length 300 --width 200
+  fx: 564.0
+  fy: 564.0
+  cx: 320.0
+  cy: 240.0
+  # Совмещение RGB с depth в демо (сенсоры D415 разнесены ~55 мм).
+  # Подбор: .venv/bin/python align_color.py (нужен объект с чёткими краями)
+  color_dx: -40.0
+  color_dy: -8.0
+  color_scale: 1.030
+
+# Высота камеры над пустой лентой, мм (оценка по боковым полосам ленты: ~594)
+belt_distance_mm: 594
+belt_tolerance_mm: 25
+min_object_height_mm: 20
+min_object_area_px: 800
+# Игнор краёв кадра (ролики/борта/плата справа), доля от размера кадра
+roi_margin:
+  top: 0.12
+  bottom: 0.02
+  left: 0.05
+  right: 0.12
+# Сколько объектов одновременно искать в кадре
+max_objects_in_frame: 3
+# RGB-картинка в демо (измерения всё равно по depth)
+use_color: true
+
+# Фоновая карта глубины: в main.py при старте; в demo — только кнопка «Авто-высота»
+# false пока тестируем с объектом на ленте (карту снимать только на ПУСТОЙ ленте)
+use_background_map: false
+
+# RGB-поиск плоских товаров (телефон). ВЫКЛ по умолчанию — тени/шум давали ложные C.
+# Включить: true + «Авто-высота» на пустой ленте.
+detect_flat_rgb: false
+rgb_diff_threshold: 35
+
+classification:
+  min_mm: [10, 10, 10]
+  max_mm: [450, 320, 320]
+  circle_ratio_threshold: 0.8
+  # Пограничные случаи: нет консенсуса N кадров (~4 с при 12 fps обработки)
+  # → товар помечается «неуверенно» и уходит в безопасную зону (по умолчанию C).
+  uncertain_after_frames: 45
+  uncertain_fallback_zone: C
+
+# MQTT — тот же брокер, что слушает ESP32 и SCADA (backend_control)
+# На этом Orange PI mosquitto уже слушает :1883 → используйте 127.0.0.1
+# ESP32 в прошивке ждёт 192.168.0.200 — см. INTEGRATION.md
+mqtt:
+  broker: "127.0.0.1"
+  port: 1883
+  user: "test"
+  password: "1234"
+  client_id: "vision_classifier_opi"
+  topic_result: "vision/feedback/category"
+  topic_dims: "vision/feedback/dimensions"
+  topic_circle: "vision/feedback/circle_ratio"
+  topic_debug: "vision/feedback/debug"
+  enabled: true
+
+# Шаговик ленты — те же топики, что SCADA (arduino_code не меняем)
+motor:
+  enabled: true
+  rpm: -200                # скорость ленты; у вас направление — с минусом
+  current_percent: 50
+  microsteps: 16
+  stealthchop: true
+  disable_on_stop: false   # при Ctrl+C только rpm=0, драйвер не гасим
+
+# Серво-селекторы зон B/C/D — подставьте свои каналы/углы
+routing:
+  enabled: true
+  zones:
+    B:  # Подходит для сортировки — пропуск
+      servo: 0
+      idle_angle: 0
+      divert_angle: 0
+      hold_ms: 500
+    C:  # Не подходит по габаритам
+      servo: 1
+      idle_angle: 0
+      divert_angle: 90
+      hold_ms: 800
+    D:  # Без доупаковки (круг)
+      servo: 2
+      idle_angle: 0
+      divert_angle: 90
+      hold_ms: 800
+  cooldown_ms: 1500
+
+runtime:
+  show_preview: false
+  save_debug_frames: false
+  debug_dir: "debug_frames"
+  # JSONL-журнал всех LOCK-решений (метрики для отчёта)
+  decisions_log: "logs/decisions.jsonl"
+  preview_every_n: 3
+  process_every_n: 1
+  confirm_frames: 8
--- a/vision_classifier/demo.py
+++ b/vision_classifier/demo.py
@@ -0,0 +1,863 @@
+#!/usr/bin/env python3
+"""
+Демо-режим хакатона с ползунками в браузере:
+  • высота до ленты (belt_distance_mm)
+  • порог уверенности (сколько кадров подряд одно и то же решение)
+  • мин. высота объекта, порог круга
+
+Без MQTT / мотора / серво.
+"""
+
+from __future__ import annotations
+
+import argparse
+import base64
+import json
+import sys
+import threading
+import time
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from pathlib import Path
+from typing import Any, Dict, Optional
+from urllib.parse import parse_qs, urlparse
+
+import cv2
+import numpy as np
+import yaml
+
+from camera import RealSenseV4L2
+from classify import Category, ClassificationResult
+from demo_hud import ContourSmoother, align_color, build_demo_frame
+from journal import append_decision
+from measure import (
+    is_plausible_measurement,
+    measure_flat_object,
+    measure_object,
+    merge_overlapping_measurements,
+    segment_objects,
+    segment_rgb_objects,
+)
+from stabilize import DecisionStabilizer
+from tracker import MultiObjectTracker, slot_key
+
+ZONE_TO_CATEGORY = {
+    "B": Category.SUITABLE,
+    "C": Category.OVERSIZE,
+    "D": Category.NEED_PACK,
+}
+
+
+HTML = r"""<!DOCTYPE html>
+<html lang="ru">
+<head>
+<meta charset="utf-8"/>
+<meta name="viewport" content="width=device-width, initial-scale=1"/>
+<title>Трек 3 — демо</title>
+<style>
+  :root {
+    --bg:#111114; --card:#1c1c22; --line:#33333c; --txt:#f2f2f4;
+    --muted:#a0a0ab; --acc:#2dd4bf; --b:#22c55e; --c:#ef4444; --d:#f59e0b;
+  }
+  * { box-sizing:border-box; }
+  body { margin:0; background:var(--bg); color:var(--txt); font-family:system-ui,-apple-system,sans-serif; }
+  .top {
+    position:sticky; top:0; z-index:20;
+    background:var(--card); border-bottom:2px solid var(--acc);
+    padding:12px 16px 14px; box-shadow:0 8px 24px rgba(0,0,0,.45);
+  }
+  .top h1 { margin:0 0 4px; font-size:17px; }
+  .top .sub { margin:0 0 12px; color:var(--muted); font-size:12px; }
+  .sliders {
+    display:grid;
+    grid-template-columns:repeat(auto-fit, minmax(220px, 1fr));
+    gap:12px 18px;
+  }
+  .sliders label {
+    display:flex; justify-content:space-between; align-items:baseline;
+    font-size:12px; margin-bottom:4px; color:var(--muted);
+  }
+  .sliders label b { color:var(--acc); font-size:14px; font-variant-numeric:tabular-nums; }
+  input[type=range] { width:100%; height:28px; accent-color:var(--acc); cursor:pointer; }
+  .actions { display:flex; flex-wrap:wrap; gap:8px; margin-top:12px; align-items:center; }
+  button {
+    border:0; border-radius:8px; padding:10px 14px; font-weight:700; cursor:pointer;
+    background:var(--acc); color:#042f2e;
+  }
+  button.sec { background:#2a2a32; color:var(--txt); }
+  #st {
+    flex:1; min-width:200px; padding:10px 12px; border-radius:8px;
+    background:#121218; border:1px solid var(--line); font-size:13px; line-height:1.45;
+  }
+  #st .zoneB { color:var(--b); font-weight:800; font-size:18px; }
+  #st .zoneC { color:var(--c); font-weight:800; font-size:18px; }
+  #st .zoneD { color:var(--d); font-weight:800; font-size:18px; }
+  .main {
+    display:flex; gap:12px; padding:12px; max-width:1400px;
+    margin:0 auto; align-items:flex-start;
+  }
+  .stage { flex:1; min-width:0; }
+  .stage img {
+    width:100%; height:auto; display:block;
+    border-radius:10px; border:1px solid var(--line); background:#000;
+  }
+  .side { width:320px; flex-shrink:0; display:flex; flex-direction:column; gap:10px; }
+  .side h3 {
+    margin:0; font-size:12px; text-transform:uppercase; letter-spacing:.08em;
+    color:var(--muted);
+  }
+  .card {
+    background:var(--card); border:1px solid var(--line); border-radius:10px;
+    padding:10px; font-size:13px; line-height:1.5;
+  }
+  .card img {
+    width:100%; height:auto; display:block; border-radius:6px;
+    background:#000; margin-bottom:8px;
+  }
+  .card .hd { font-weight:800; font-size:14px; }
+  .card .mut { color:var(--muted); font-size:12px; }
+  #feed { display:flex; flex-direction:column; gap:8px; overflow-y:auto; max-height:60vh; }
+  .fitem {
+    display:flex; gap:8px; background:var(--card); border:1px solid var(--line);
+    border-radius:10px; padding:8px; font-size:12px; line-height:1.45;
+  }
+  .fitem img {
+    width:86px; height:64px; object-fit:cover; border-radius:6px;
+    background:#000; flex-shrink:0;
+  }
+  .fitem .hd { font-weight:800; font-size:13px; }
+  .fitem .mut { color:var(--muted); }
+  .zB { color:var(--b); } .zC { color:var(--c); } .zD { color:var(--d); }
+  .zU { color:#f97316; }
+  @media (max-width:900px) {
+    .main { flex-direction:column; }
+    .side { width:100%; }
+  }
+</style>
+</head>
+<body>
+  <div class="top">
+    <h1>Трек 3 — демо классификации (B / C / D)</h1>
+    <p class="sub">Ползунки СВЕРХУ (отдельная панель). Картинка только камера. Выход: Ctrl+C в терминале. Обновите страницу Ctrl+F5.</p>
+    <div class="sliders">
+      <div>
+        <label>Высота до ленты, мм <b id="v_belt">600</b></label>
+        <input id="belt" type="range" min="300" max="2000" step="5" value="600"/>
+      </div>
+      <div>
+        <label>Порог уверенности, % <b id="v_conf">75</b></label>
+        <input id="conf" type="range" min="10" max="100" step="5" value="75"/>
+      </div>
+      <div>
+        <label>Мин. высота объекта, мм <b id="v_hmin">8</b></label>
+        <input id="hmin" type="range" min="2" max="80" step="1" value="8"/>
+      </div>
+      <div>
+        <label>Порог «круг» <b id="v_circ">0.80</b></label>
+        <input id="circ" type="range" min="0.50" max="0.95" step="0.01" value="0.80"/>
+      </div>
+      <div>
+        <label>Мин. площадь, px <b id="v_area">800</b></label>
+        <input id="area" type="range" min="100" max="5000" step="50" value="800"/>
+      </div>
+    </div>
+    <div class="actions">
+      <div id="st">Загрузка…</div>
+      <button type="button" id="auto">Авто-высота</button>
+      <button type="button" class="sec" id="reset">Сброс</button>
+    </div>
+  </div>
+  <div class="main">
+    <div class="stage">
+      <img id="f" src="/frame.jpg?t=0" alt="camera"/>
+    </div>
+    <aside class="side">
+      <h3>Текущий объект</h3>
+      <div id="live"><div class="card mut">объектов нет</div></div>
+      <h3>Лента</h3>
+      <div id="feed"><div class="card mut">пока пусто</div></div>
+    </aside>
+  </div>
+<script>
+  const img = document.getElementById('f');
+  const ids = ['belt','conf','hmin','circ','area'];
+  const defaults = { belt:600, conf:75, hmin:8, circ:0.80, area:800 };
+  let dragging = false;
+
+  function syncLabels() {
+    v_belt.textContent = belt.value;
+    v_conf.textContent = conf.value;
+    v_hmin.textContent = hmin.value;
+    v_circ.textContent = Number(circ.value).toFixed(2);
+    v_area.textContent = area.value;
+  }
+
+  async function pushParams() {
+    syncLabels();
+    await fetch('/api/params', {
+      method:'POST',
+      headers:{'Content-Type':'application/json'},
+      body: JSON.stringify({
+        belt_mm: Number(belt.value),
+        confidence_pct: Number(conf.value),
+        min_object_height_mm: Number(hmin.value),
+        circle_threshold: Number(circ.value),
+        min_area_px: Number(area.value),
+      }),
+    });
+  }
+
+  async function pullStatus() {
+    try {
+      const s = await (await fetch('/api/status')).json();
+      let zoneHtml = '<span style="color:#888">объектов нет</span>';
+      if (s.objects && s.objects.length) {
+        zoneHtml = s.objects.map(o => {
+          const dims = o.dims ? (o.dims.map(x => Math.round(x)).join('×') + ' мм') : '';
+          const extra = ' · ' + dims + ' · круг ' + (o.ratio ?? '—');
+          if (o.locked && o.uncertain)
+            return '<span style="color:#f97316;font-weight:800">#' + o.id + ' НЕУВЕРЕННО → ' + o.label + '</span>' + extra;
+          if (o.locked)
+            return '<span class="zone' + o.zone + '">#' + o.id + ' ' + o.label + ' ✓</span>' + extra;
+          return '<span style="color:#38bdf8">#' + o.id + ' анализ… ' + o.conf + '%</span>' + extra;
+        }).join('<br/>');
+      }
+      const stt = s.stats || {};
+      const statsLine = 'Итого: <b style="color:#22c55e">ГОТОВ ' + (stt.B || 0) +
+        '</b> · <b style="color:#ef4444">НЕГАБАРИТ ' + (stt.C || 0) +
+        '</b> · <b style="color:#f59e0b">ДОУПАКОВКА ' + (stt.D || 0) + '</b>' +
+        (stt.uncertain ? ' · неуверенно ' + stt.uncertain : '');
+      st.innerHTML = zoneHtml + '<br/>' + statsLine + '<br/>высота <b>' + s.belt_mm + '</b> мм';
+      renderLive(s.objects || []);
+      if (s.feed_seq !== window.__feedSeq) {
+        window.__feedSeq = s.feed_seq;
+        refreshFeed(s.feed || null);
+      }
+      if (!window.__inited && !dragging) {
+        belt.value = s.belt_mm;
+        conf.value = s.confidence_pct;
+        hmin.value = s.min_object_height_mm;
+        circ.value = s.circle_threshold;
+        area.value = s.min_area_px;
+        syncLabels();
+        window.__inited = true;
+      }
+    } catch (e) { st.textContent = 'Нет связи с demo.py — перезапустите ./demo.sh'; }
+  }
+
+  function zcls(o) {
+    if (o.uncertain) return 'zU';
+    return o.zone ? ('z' + o.zone) : '';
+  }
+  function dimsStr(d) {
+    return d ? d.map(x => Math.round(x)).join('×') + ' мм' : '';
+  }
+
+  function objSig(o) {
+    return o.id + '|' + (o.locked ? 'L' : 'P') + '|' + o.conf + '|' + (o.zone || '') +
+      '|' + (o.label || '') + '|' + (o.dims || []).map(x => Math.round(x)).join(',');
+  }
+
+  function renderLive(objs) {
+    const box = document.getElementById('live');
+    const sig = objs.map(objSig).join(';');
+    if (sig === window.__liveSig) return;
+    window.__liveSig = sig;
+    if (!objs.length) {
+      box.innerHTML = '<div class="card mut">объектов нет</div>';
+      return;
+    }
+    box.innerHTML = objs.map(o => {
+      const img = (o.locked && o.crop) ? '<img src="data:image/jpeg;base64,' + o.crop + '"/>' : '';
+      const head = o.locked
+        ? '<span class="hd ' + zcls(o) + '">#' + o.id + ' ' + (o.uncertain ? 'НЕУВЕРЕННО → ' : '') + o.label + (o.zone ? ' · зона ' + o.zone : '') + '</span>'
+        : '<span class="hd" style="color:#38bdf8">#' + o.id + ' анализ… ' + o.conf + '%</span>';
+      const reason = o.reason ? '<div class="mut">' + o.reason + '</div>' : '';
+      return '<div class="card">' + img + head +
+        '<div>' + dimsStr(o.dims) + ' · круг ' + (o.ratio ?? '—') + '</div>' + reason + '</div>';
+    }).join('');
+  }
+
+  function refreshFeed(items) {
+    const box = document.getElementById('feed');
+    if (!window.__feedKeys) window.__feedKeys = new Set();
+    if (!items || !items.length) {
+      if (!window.__feedKeys.size) box.innerHTML = '<div class="card mut">пока пусто</div>';
+      return;
+    }
+    if (window.__feedKeys.size === 0) box.innerHTML = '';
+    for (const it of items.slice().reverse()) {
+      const key = it.slot || ('#' + it.id);
+      if (window.__feedKeys.has(key)) continue;
+      window.__feedKeys.add(key);
+      const img = it.crop ? '<img src="data:image/jpeg;base64,' + it.crop + '"/>' : '<img/>';
+      const el = document.createElement('div');
+      el.className = 'fitem';
+      el.dataset.slot = key;
+      el.innerHTML = img + '<div>' +
+        '<div class="hd ' + zcls(it) + '">#' + it.id + ' ' + (it.uncertain ? 'НЕУВЕР → ' : '') + 'зона ' + it.zone + '</div>' +
+        '<div>' + it.label + '</div>' +
+        '<div class="mut">' + dimsStr(it.dims) + ' · круг ' + it.ratio + ' · ' + it.time + '</div>' +
+        '</div>';
+      box.insertBefore(el, box.firstChild);
+    }
+  }
+
+  ids.forEach(id => {
+    const el = document.getElementById(id);
+    el.addEventListener('pointerdown', () => { dragging = true; });
+    el.addEventListener('pointerup', () => { dragging = false; pushParams(); });
+    el.addEventListener('input', () => { syncLabels(); pushParams(); });
+  });
+
+  document.getElementById('auto').onclick = async () => {
+    st.textContent = 'Калибровка… уберите объекты с ленты';
+    const s = await (await fetch('/api/autocalib', {method:'POST'})).json();
+    if (s.ok) {
+      belt.value = Math.round(s.belt_mm);
+      syncLabels();
+      await pushParams();
+    } else st.textContent = 'Ошибка: ' + (s.error || '');
+  };
+  document.getElementById('reset').onclick = () => {
+    belt.value = defaults.belt; conf.value = defaults.conf;
+    hmin.value = defaults.hmin; circ.value = defaults.circ; area.value = defaults.area;
+    syncLabels(); pushParams();
+  };
+
+  setInterval(() => { img.src = '/frame.jpg?t=' + Date.now(); }, 280);
+  setInterval(pullStatus, 350);
+  pullStatus();
+</script>
+</body>
+</html>
+"""
+
+
+class Params:
+    def __init__(self) -> None:
+        self.lock = threading.Lock()
+        self.belt_mm: float = 800.0
+        self.confidence_pct: int = 75  # порог фиксации
+        self.min_object_height_mm: float = 8.0
+        self.circle_threshold: float = 0.80
+        self.min_area_px: int = 400
+        # runtime status
+        self.confidence_now: int = 0
+        self.zone: Optional[str] = None
+        self.locked: bool = False
+        self.uncertain: bool = False
+        self.circle_ratio: Optional[float] = None
+        self.dims: Optional[tuple] = None
+        self.reason: str = ""
+        self.objects: list = []       # [{id, zone, label, dims, ratio, locked, uncertain, conf, crop}]
+        self.stats: dict = {}         # счётчики за сессию
+        self.feed: list = []          # лента LOCK-событий (новые в конце)
+        self.feed_seq: int = 0        # версия ленты — клиент тянет только при изменении
+        self.feed_slots: set = set()  # slot_key — один товар = одна карточка в ленте
+        self.crop_cache: dict = {}    # track_id → base64, фиксируется при LOCK
+        self.jpeg: bytes = b""
+        self.last_print: str = ""
+        self.cam: Any = None
+        self.request_autocalib: bool = False
+        self.autocalib_result: Optional[Dict[str, Any]] = None
+        self.background: Optional[np.ndarray] = None  # карта глубины пустой сцены
+        self.color_background: Optional[np.ndarray] = None  # RGB пустой сцены (плоские товары)
+
+
+STATE = Params()
+
+
+def make_handler() -> type:
+    class Handler(BaseHTTPRequestHandler):
+        def log_message(self, fmt: str, *args) -> None:
+            return
+
+        def _json(self, code: int, obj: Dict[str, Any]) -> None:
+            body = json.dumps(obj, ensure_ascii=False).encode("utf-8")
+            self.send_response(code)
+            self.send_header("Content-Type", "application/json; charset=utf-8")
+            self.send_header("Cache-Control", "no-store")
+            self.send_header("Content-Length", str(len(body)))
+            self.end_headers()
+            self.wfile.write(body)
+
+        def do_GET(self) -> None:
+            path = urlparse(self.path).path
+            if path.startswith("/frame.jpg"):
+                with STATE.lock:
+                    data = STATE.jpeg
+                if not data:
+                    self.send_error(503, "no frame yet")
+                    return
+                self.send_response(200)
+                self.send_header("Content-Type", "image/jpeg")
+                self.send_header("Cache-Control", "no-store")
+                self.send_header("Content-Length", str(len(data)))
+                self.end_headers()
+                self.wfile.write(data)
+            elif path == "/api/status":
+                with STATE.lock:
+                    self._json(
+                        200,
+                        {
+                            "belt_mm": round(STATE.belt_mm),
+                            "confidence_pct": STATE.confidence_pct,
+                            "confidence_now": STATE.confidence_now,
+                            "min_object_height_mm": STATE.min_object_height_mm,
+                            "circle_threshold": STATE.circle_threshold,
+                            "min_area_px": STATE.min_area_px,
+                            "zone": STATE.zone,
+                            "locked": STATE.locked,
+                            "uncertain": STATE.uncertain,
+                            "circle_ratio": STATE.circle_ratio,
+                            "dims": STATE.dims,
+                            "reason": STATE.reason,
+                            "objects": STATE.objects,
+                            "stats": STATE.stats,
+                            "feed_seq": STATE.feed_seq,
+                            "feed": STATE.feed,
+                        },
+                    )
+            elif path == "/api/feed":
+                with STATE.lock:
+                    self._json(200, {"seq": STATE.feed_seq, "items": STATE.feed})
+            else:
+                body = HTML.encode("utf-8")
+                self.send_response(200)
+                self.send_header("Content-Type", "text/html; charset=utf-8")
+                self.send_header("Content-Length", str(len(body)))
+                self.end_headers()
+                self.wfile.write(body)
+
+        def do_POST(self) -> None:
+            path = urlparse(self.path).path
+            length = int(self.headers.get("Content-Length", 0))
+            raw = self.rfile.read(length) if length else b"{}"
+            try:
+                data = json.loads(raw.decode("utf-8") or "{}")
+            except json.JSONDecodeError:
+                data = {}
+
+            if path == "/api/params":
+                with STATE.lock:
+                    if "belt_mm" in data:
+                        new_belt = float(np.clip(float(data["belt_mm"]), 200, 3000))
+                        # ручная правка высоты → фоновая карта устарела
+                        if abs(new_belt - STATE.belt_mm) > 2.0:
+                            STATE.background = None
+                        STATE.belt_mm = new_belt
+                    if "confidence_pct" in data:
+                        STATE.confidence_pct = int(np.clip(int(data["confidence_pct"]), 10, 100))
+                    if "min_object_height_mm" in data:
+                        STATE.min_object_height_mm = float(np.clip(float(data["min_object_height_mm"]), 1, 200))
+                    if "circle_threshold" in data:
+                        STATE.circle_threshold = float(np.clip(float(data["circle_threshold"]), 0.4, 0.99))
+                    if "min_area_px" in data:
+                        STATE.min_area_px = int(np.clip(int(data["min_area_px"]), 50, 20000))
+                self._json(200, {"ok": True})
+            elif path == "/api/autocalib":
+                with STATE.lock:
+                    STATE.request_autocalib = True
+                    STATE.autocalib_result = None
+                # ждём результат от цикла камеры
+                for _ in range(80):
+                    time.sleep(0.1)
+                    with STATE.lock:
+                        if STATE.autocalib_result is not None:
+                            self._json(200, STATE.autocalib_result)
+                            return
+                self._json(500, {"ok": False, "error": "timeout"})
+            else:
+                self.send_error(404)
+
+    return Handler
+
+
+def load_config(path: Path) -> Dict[str, Any]:
+    with open(path, "r", encoding="utf-8") as f:
+        return yaml.safe_load(f)
+
+
+def frames_needed(confidence_pct: int) -> int:
+    # 10% → 5, 100% → 12 кадров одной зоны после прогрева окна
+    return max(5, int(round(5 + (confidence_pct / 100.0) * 7)))
+
+
+def crop_b64(img: np.ndarray, contour: np.ndarray, pad: int = 14, max_w: int = 260) -> Optional[str]:
+    """Кроп объекта по bounding box контура → JPEG base64 для веб-панели."""
+    x, y, w, h = cv2.boundingRect(contour)
+    H, W = img.shape[:2]
+    x0, y0 = max(0, x - pad), max(0, y - pad)
+    x1, y1 = min(W, x + w + pad), min(H, y + h + pad)
+    if x1 - x0 < 4 or y1 - y0 < 4:
+        return None
+    crop = img[y0:y1, x0:x1]
+    if crop.shape[1] > max_w:
+        s = max_w / crop.shape[1]
+        crop = cv2.resize(crop, (max_w, max(1, int(crop.shape[0] * s))))
+    ok, buf = cv2.imencode(".jpg", crop, [int(cv2.IMWRITE_JPEG_QUALITY), 78])
+    return base64.b64encode(buf.tobytes()).decode("ascii") if ok else None
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Демо классификации с ползунками")
+    parser.add_argument("-c", "--config", default=str(Path(__file__).with_name("config.yaml")))
+    parser.add_argument("--host", default="0.0.0.0")
+    parser.add_argument("--port", type=int, default=8080)
+    args = parser.parse_args()
+
+    cfg = load_config(Path(args.config))
+    cam_cfg = cfg["camera"]
+    cls_cfg = cfg["classification"]
+    min_mm = cls_cfg.get("min_mm", [10, 10, 10])
+    max_mm = cls_cfg.get("max_mm", [450, 320, 320])
+
+    out_dir = Path(cfg.get("runtime", {}).get("debug_dir", "debug_frames"))
+    out_dir.mkdir(parents=True, exist_ok=True)
+    out_jpg = out_dir / "demo_live.jpg"
+
+    print("[demo] открываю RealSense D415…")
+    cam = RealSenseV4L2(
+        depth_device=cam_cfg.get("depth_device", "/dev/video0"),
+        color_device=cam_cfg.get("color_device", "/dev/video4"),
+        width=int(cam_cfg.get("width", 640)),
+        height=int(cam_cfg.get("height", 480)),
+        fps=int(cam_cfg.get("fps", 30)),
+        depth_scale_mm=float(cam_cfg.get("depth_scale_mm", 1.0)),
+        use_color=bool(cfg.get("use_color", False)),
+    )
+    STATE.cam = cam
+
+    belt0 = float(cfg.get("belt_distance_mm") or 0)
+    if belt0 <= 0:
+        print("[demo] калибровка ленты — уберите объекты…")
+        belt0 = cam.estimate_belt_distance_mm()
+    with STATE.lock:
+        STATE.belt_mm = belt0
+        STATE.circle_threshold = float(cls_cfg.get("circle_ratio_threshold", 0.8))
+        STATE.min_object_height_mm = float(cfg.get("min_object_height_mm", 8))
+        STATE.min_area_px = int(cfg.get("min_object_area_px", 400))
+        STATE.confidence_pct = 75
+    print(f"[demo] belt_distance_mm = {belt0:.0f}")
+    max_objects = int(cfg.get("max_objects_in_frame", 3))
+    detect_flat_rgb = bool(cfg.get("detect_flat_rgb", False))
+    print(f"[demo] max_objects={max_objects}, flat_rgb={'ON' if detect_flat_rgb else 'OFF'}")
+    print("[demo] фоновая карта: кнопка «Авто-высота» на пустой ленте")
+
+    server = ThreadingHTTPServer((args.host, args.port), make_handler())
+    threading.Thread(target=server.serve_forever, daemon=True).start()
+    print(f"[demo] браузер → http://127.0.0.1:{args.port}/")
+    print("[demo] ползунки СВЕРХУ страницы (не на картинке)")
+    print("[demo] зона только после LOCK (медиана 12 кадров + голосование)")
+    print("[demo] Ctrl+C — выход\n")
+
+    fx, fy = float(cam_cfg["fx"]), float(cam_cfg["fy"])
+    cx, cy = float(cam_cfg["cx"]), float(cam_cfg["cy"])
+    fallback_zone = str(cls_cfg.get("uncertain_fallback_zone", "C")).upper()
+    thr0 = float(cls_cfg.get("circle_ratio_threshold", 0.8))
+    settings = {"confirm": frames_needed(75), "circ": thr0}
+
+    def make_stabilizer() -> DecisionStabilizer:
+        return DecisionStabilizer(
+            window=12,
+            confirm_frames=settings["confirm"],
+            lost_frames=12,
+            enter_circle=settings["circ"],
+            exit_circle=settings["circ"] - 0.08,
+            uncertain_after=int(cls_cfg.get("uncertain_after_frames", 45)),
+            fallback=ZONE_TO_CATEGORY.get(fallback_zone, Category.OVERSIZE),
+        )
+
+    # lost_frames=30 ≈ 1.5–2 с: глянцевые/тёмные предметы (мышка) дают
+    # кратковременные выпадения depth — трек не должен умирать от них
+    tracker = MultiObjectTracker(make_stabilizer, max_dist_px=120, lost_frames=30)
+    contour_smoother = ContourSmoother(alpha=0.3)
+    color_align = (
+        float(cam_cfg.get("color_dx", 0.0)),
+        float(cam_cfg.get("color_dy", 0.0)),
+        float(cam_cfg.get("color_scale", 1.0)),
+    )
+    decisions_log = Path(cfg.get("runtime", {}).get("decisions_log", "logs/decisions.jsonl"))
+    frame_i = 0
+    last_conf_setting = 75
+    last_circ = thr0
+
+    try:
+        while True:
+            # автокалибровка по запросу из UI
+            with STATE.lock:
+                need_auto = STATE.request_autocalib
+                if need_auto:
+                    STATE.request_autocalib = False
+            if need_auto:
+                try:
+                    print("[demo] автокалибровка: снимаю фоновую карту (сцена должна быть пустой)…")
+                    bg = cam.capture_background(samples=15)
+                    color_bg = cam.capture_background_rgb(samples=10)
+                    h, w = bg.shape
+                    center = bg[h // 4 : 3 * h // 4, w // 4 : 3 * w // 4].astype(np.float32)
+                    center = center[(center > 200) & (center < 4000)]
+                    new_belt = float(np.median(center)) if center.size > 100 else cam.estimate_belt_distance_mm(samples=10)
+                    with STATE.lock:
+                        STATE.belt_mm = new_belt
+                        STATE.background = bg
+                        STATE.color_background = color_bg
+                        STATE.autocalib_result = {"ok": True, "belt_mm": new_belt}
+                    tracker.reset()
+                    rgb_tag = "RGB-фон есть" if color_bg is not None else "RGB-фон недоступен"
+                    print(f"[demo] высота = {new_belt:.0f} mm, фоновая карта активна, {rgb_tag}")
+                except Exception as exc:
+                    with STATE.lock:
+                        STATE.autocalib_result = {"ok": False, "error": str(exc)}
+
+            pair = cam.read()
+            if pair is None:
+                time.sleep(0.02)
+                continue
+            frame_i += 1
+
+            with STATE.lock:
+                belt_mm = STATE.belt_mm
+                conf_pct = STATE.confidence_pct
+                hmin = STATE.min_object_height_mm
+                circ_thr = STATE.circle_threshold
+                min_area = STATE.min_area_px
+                background = STATE.background
+                color_background = STATE.color_background
+
+            if conf_pct != last_conf_setting:
+                settings["confirm"] = frames_needed(conf_pct)
+                tracker.reset()
+                last_conf_setting = conf_pct
+            if abs(circ_thr - last_circ) > 1e-6:
+                settings["circ"] = float(circ_thr)
+                tracker.reset()
+                last_circ = circ_thr
+
+            # несколько объектов в кадре → трекер с ID
+            measurements = []
+            depth_union = None
+            seg_n = 0
+            for mask, contour in segment_objects(
+                pair.depth_mm,
+                belt_distance_mm=belt_mm,
+                belt_tolerance_mm=float(cfg.get("belt_tolerance_mm", 25)),
+                min_object_height_mm=hmin,
+                min_area_px=min_area,
+                background_mm=background,
+                max_objects=max_objects,
+            ):
+                seg_n += 1
+                depth_union = mask if depth_union is None else cv2.bitwise_or(depth_union, mask)
+                m = measure_object(
+                    pair.depth_mm,
+                    mask,
+                    contour,
+                    belt_distance_mm=belt_mm,
+                    fx=fx,
+                    fy=fy,
+                    cx=cx,
+                    cy=cy,
+                    background_mm=background,
+                    min_object_height_mm=hmin,
+                )
+                if m is not None and is_plausible_measurement(m):
+                    measurements.append(m)
+
+            # плоские товары — только если detect_flat_rgb: true (иначе тени → ложные C)
+            if (
+                detect_flat_rgb
+                and color_background is not None
+                and not pair.color_is_depth_preview
+            ):
+                for mask, contour in segment_rgb_objects(
+                    pair.color_bgr,
+                    color_background,
+                    min_area_px=min_area,
+                    diff_threshold=int(cfg.get("rgb_diff_threshold", 35)),
+                    max_objects=max(0, max_objects - len(measurements)),
+                    exclude_mask=depth_union,
+                ):
+                    m = measure_flat_object(
+                        pair.depth_mm,
+                        mask,
+                        contour,
+                        belt_distance_mm=belt_mm,
+                        fx=fx,
+                        fy=fy,
+                        cx=cx,
+                        cy=cy,
+                        background_mm=background,
+                        color_bgr=pair.color_bgr,
+                        color_bg_bgr=color_background,
+                    )
+                    if m is not None and is_plausible_measurement(m):
+                        measurements.append(m)
+
+            measurements = merge_overlapping_measurements(measurements, overlap_thr=0.5)
+            tracks, events = tracker.update(measurements, min_mm=min_mm, max_mm=max_mm)
+
+            rgb_available = not pair.color_is_depth_preview
+            if rgb_available and float(np.std(pair.color_bgr)) > 4.0:
+                base_img = pair.color_bgr
+                if base_img.shape[:2] != pair.depth_mm.shape[:2]:
+                    base_img = cv2.resize(base_img, (pair.depth_mm.shape[1], pair.depth_mm.shape[0]))
+                base_img = align_color(base_img, *color_align)
+            else:
+                # без живого RGB — colorize(depth), иначе веб был бы чёрным
+                from camera import depth_colormap
+                base_img = depth_colormap(pair.depth_mm)
+                rgb_available = False
+
+            crops: Dict[int, Optional[str]] = {}
+            for tr in tracks:
+                if tr.measurement is not None:
+                    crops[tr.track_id] = crop_b64(base_img, tr.measurement.contour)
+
+            crop_updates: Dict[int, str] = {}
+            feed_add = []
+            for ev in events:
+                r = ev.decision.result
+                tag = "UNCERTAIN→" if ev.decision.uncertain else "LOCK "
+                print(
+                    f"[demo] #{ev.track_id} {tag}{r.category.zone} | {r.category.short_label} | "
+                    f"LWH={tuple(round(x, 1) for x in r.dims_sorted_mm)} | circle={r.circle_ratio:.3f}"
+                )
+                append_decision(
+                    decisions_log, r,
+                    uncertain=ev.decision.uncertain, source="demo", track_id=ev.track_id,
+                )
+                L, W, H = r.dims_sorted_mm
+                tr_ev = next((t for t in tracks if t.track_id == ev.track_id), None)
+                cx, cy = (tr_ev.centroid if tr_ev else (0, 0))
+                sk = slot_key(cx, cy, L, W, H, r.category.zone)
+                crop = crops.get(ev.track_id)
+                if crop:
+                    crop_updates[ev.track_id] = crop
+                feed_add.append({
+                    "slot": sk,
+                    "id": ev.track_id,
+                    "time": time.strftime("%H:%M:%S"),
+                    "zone": r.category.zone,
+                    "label": r.category.short_label,
+                    "dims": [round(x, 1) for x in r.dims_sorted_mm],
+                    "ratio": round(r.circle_ratio, 3),
+                    "uncertain": bool(ev.decision.uncertain),
+                    "crop": crop,
+                })
+
+            with STATE.lock:
+                STATE.crop_cache.update(crop_updates)
+                crop_cache = dict(STATE.crop_cache)
+
+            # статус для веба: список объектов + «главный» (первый залоченный)
+            objects_json = []
+            primary = None
+            for tr in tracks:
+                d = tr.decision
+                m = tr.measurement
+                if d is None or m is None:
+                    continue
+                is_locked = bool(d.locked and d.result is not None)
+                if is_locked:
+                    obj = {
+                        "id": tr.track_id,
+                        "locked": True,
+                        "uncertain": bool(d.uncertain),
+                        "conf": 100,
+                        "zone": d.result.category.zone,
+                        "label": d.result.category.short_label,
+                        "dims": [round(x, 1) for x in d.result.dims_sorted_mm],
+                        "ratio": round(d.result.circle_ratio, 3),
+                        "reason": d.result.reason,
+                        "crop": crop_cache.get(tr.track_id),
+                    }
+                else:
+                    obj = {
+                        "id": tr.track_id,
+                        "locked": False,
+                        "uncertain": False,
+                        "conf": d.confidence_pct,
+                        "zone": None,
+                        "label": "анализ…",
+                        "dims": [round(m.length_mm, 1), round(m.width_mm, 1), round(m.height_mm, 1)],
+                        "ratio": round(m.circle_ratio, 3),
+                        "reason": "",
+                        "crop": None,
+                    }
+                objects_json.append(obj)
+                if primary is None or (obj["locked"] and not primary["locked"]):
+                    primary = obj
+
+            with STATE.lock:
+                STATE.objects = objects_json
+                STATE.stats = dict(tracker.stats)
+                if feed_add:
+                    fresh = [it for it in feed_add if it["slot"] not in STATE.feed_slots]
+                    for it in fresh:
+                        STATE.feed_slots.add(it["slot"])
+                    if fresh:
+                        STATE.feed.extend(fresh)
+                        STATE.feed = STATE.feed[-20:]
+                        STATE.feed_seq += 1
+                if primary is not None:
+                    STATE.confidence_now = primary["conf"]
+                    STATE.locked = primary["locked"]
+                    STATE.uncertain = primary["uncertain"]
+                    STATE.zone = primary["zone"]
+                    STATE.circle_ratio = primary["ratio"]
+                    STATE.dims = tuple(primary["dims"])
+                    STATE.reason = primary["reason"] or (
+                        f"накопление {primary['conf']}% → ждём LOCK" if not primary["locked"] else ""
+                    )
+                else:
+                    STATE.confidence_now = 0
+                    STATE.locked = False
+                    STATE.uncertain = False
+                    STATE.zone = None
+                    STATE.circle_ratio = None
+                    STATE.dims = None
+                    STATE.reason = ""
+
+            hud = build_demo_frame(
+                base_img,
+                pair.depth_mm,
+                tracks,
+                belt_mm,
+                stats=tracker.stats,
+                confidence_pct=conf_pct,
+                rgb_available=rgb_available,
+                background_active=background is not None,
+                color_align=(0.0, 0.0, 1.0),
+                contour_smoother=contour_smoother,
+            )
+            ok, buf = cv2.imencode(".jpg", hud, [int(cv2.IMWRITE_JPEG_QUALITY), 80])
+            if ok:
+                jpeg = buf.tobytes()
+                with STATE.lock:
+                    STATE.jpeg = jpeg
+                if frame_i % 3 == 0:
+                    out_jpg.write_bytes(jpeg)
+
+            if seg_n > len(measurements) and STATE.last_print != "seg_drop":
+                print(f"[demo] depth: контуров {seg_n}, измерено {len(measurements)} "
+                      f"(часть отфильтрована: низкая высота < {hmin:.0f} мм или шум)")
+                STATE.last_print = "seg_drop"
+            elif not tracks and STATE.last_print != "empty":
+                print("[demo] объектов нет")
+                STATE.last_print = "empty"
+            elif tracks and STATE.last_print in ("seg_drop", "empty"):
+                STATE.last_print = ""
+
+            time.sleep(0.03)
+    except KeyboardInterrupt:
+        print("\n[demo] stop")
+    finally:
+        server.shutdown()
+        cam.release()
+    return 0
+
+
+if __name__ == "__main__":
+    sys.path.insert(0, str(Path(__file__).resolve().parent))
+    raise SystemExit(main())
--- a/vision_classifier/demo.sh
+++ b/vision_classifier/demo.sh
@@ -0,0 +1,14 @@
+#!/usr/bin/env bash
+set -euo pipefail
+DIR="$(cd "$(dirname "$0")" && pwd)"
+cd "$DIR"
+
+if [[ ! -d .venv ]]; then
+  python3 -m venv .venv
+  .venv/bin/pip install -U pip
+  .venv/bin/pip install -r requirements.txt
+fi
+
+echo "Демо классификации (без моторов/серво)"
+echo "Браузер: http://127.0.0.1:8080/"
+exec .venv/bin/python demo.py "$@"
--- a/vision_classifier/demo_hud.py
+++ b/vision_classifier/demo_hud.py
@@ -0,0 +1,302 @@
+"""HUD демо: RGB-подложка + depth, несколько объектов с ID, кириллица через PIL."""
+
+from __future__ import annotations
+
+from functools import lru_cache
+from typing import Dict, List, Optional, Tuple
+
+import cv2
+import numpy as np
+from PIL import Image, ImageDraw, ImageFont
+
+ZONE_COLOR = {  # BGR
+    "B": (40, 180, 40),
+    "C": (40, 40, 220),
+    "D": (0, 165, 255),
+}
+UNCERTAIN_COLOR = (0, 130, 250)  # оранжевый
+PENDING_COLOR = (0, 255, 255)    # жёлтый — идёт накопление
+
+_FONT_CANDIDATES = [
+    "/usr/share/fonts/noto/NotoSans-Bold.ttf",
+    "/usr/share/fonts/noto/NotoSans-Regular.ttf",
+    "/usr/share/fonts/TTF/DejaVuSans-Bold.ttf",
+    "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf",
+]
+
+
+@lru_cache(maxsize=8)
+def _font(size: int) -> ImageFont.FreeTypeFont:
+    for path in _FONT_CANDIDATES:
+        try:
+            return ImageFont.truetype(path, size)
+        except OSError:
+            continue
+    return ImageFont.load_default()
+
+
+def _draw_texts(
+    img_bgr: np.ndarray,
+    texts: List[Tuple[int, int, str, Tuple[int, int, int], int]],
+) -> np.ndarray:
+    """texts: (x, y, строка, цвет BGR, размер). Кириллица через PIL."""
+    if not texts:
+        return img_bgr
+    pil = Image.fromarray(cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB))
+    draw = ImageDraw.Draw(pil)
+    for x, y, s, bgr, size in texts:
+        rgb = (bgr[2], bgr[1], bgr[0])
+        draw.text((x, y), s, font=_font(size), fill=rgb, stroke_width=2, stroke_fill=(0, 0, 0))
+    return cv2.cvtColor(np.array(pil), cv2.COLOR_RGB2BGR)
+
+
+class DepthSmoother:
+    """Временное сглаживание depth только для отображения (не для измерений)."""
+
+    def __init__(self, alpha: float = 0.25) -> None:
+        self.alpha = float(alpha)
+        self._acc: Optional[np.ndarray] = None
+
+    def update(self, depth_mm: np.ndarray) -> np.ndarray:
+        d = depth_mm.astype(np.float32)
+        if self._acc is None or self._acc.shape != d.shape:
+            self._acc = d.copy()
+        valid = d > 0
+        self._acc[valid] = (1.0 - self.alpha) * self._acc[valid] + self.alpha * d[valid]
+        out = self._acc.astype(np.uint16)
+        out[~valid & (self._acc <= 0)] = 0
+        return out
+
+
+class ContourSmoother:
+    """Стабильная окантовка: EMA маски по каждому треку + аппроксимация контура,
+    плюс «примагничивание» контура к краям объекта на RGB (снимает остаточный
+    параллакс depth↔color и распухание depth-маски).
+
+    Только для отрисовки — измерения идут по сырому контуру.
+    """
+
+    def __init__(self, alpha: float = 0.3, snap_alpha: float = 0.35) -> None:
+        self.alpha = float(alpha)
+        self.snap_alpha = float(snap_alpha)
+        self._acc: Dict[int, np.ndarray] = {}
+        self._snap: Dict[int, Tuple[float, float, float]] = {}  # tid -> (dx, dy, shrink)
+
+    def smooth(
+        self, track_id: int, mask: np.ndarray, edge_img: Optional[np.ndarray] = None
+    ) -> Optional[np.ndarray]:
+        m = mask.astype(np.float32) / 255.0
+        acc = self._acc.get(track_id)
+        if acc is None or acc.shape != m.shape:
+            acc = m.copy()
+        else:
+            acc = (1.0 - self.alpha) * acc + self.alpha * m
+        self._acc[track_id] = acc
+
+        soft = cv2.GaussianBlur((acc * 255.0).astype(np.uint8), (11, 11), 0)
+        _, binm = cv2.threshold(soft, 127, 255, cv2.THRESH_BINARY)
+        contours, _ = cv2.findContours(binm, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+        if not contours:
+            return None
+        contour = max(contours, key=cv2.contourArea)
+
+        pts = contour.reshape(-1, 2).astype(np.float32)
+        if edge_img is not None and pts.shape[0] >= 8:
+            pts = self._snap_to_edges(track_id, pts, edge_img)
+
+        contour = pts.reshape(-1, 1, 2).astype(np.int32)
+        eps = 0.008 * cv2.arcLength(contour, True)
+        return cv2.approxPolyDP(contour, eps, True)
+
+    def _snap_to_edges(
+        self, track_id: int, pts: np.ndarray, edge: np.ndarray
+    ) -> np.ndarray:
+        """Локальный поиск сдвига (±14 px) и поджатия контура, при которых под
+        контуром максимум RGB-краёв. Найденная поправка сглаживается по времени."""
+        H, W = edge.shape[:2]
+        xs, ys = pts[:, 0], pts[:, 1]
+
+        def score(dx: float, dy: float, f: float, c: np.ndarray) -> float:
+            x = np.clip((c[0] + f * (xs - c[0]) + dx).astype(np.int32), 0, W - 1)
+            y = np.clip((c[1] + f * (ys - c[1]) + dy).astype(np.int32), 0, H - 1)
+            return float(edge[y, x].mean()) - 0.6 * float(np.hypot(dx, dy))
+
+        c = pts.mean(axis=0)
+        best_dx, best_dy, best_s = 0.0, 0.0, score(0, 0, 1.0, c)
+        for dy in range(-14, 15, 2):
+            for dx in range(-14, 15, 2):
+                s = score(dx, dy, 1.0, c)
+                if s > best_s:
+                    best_s, best_dx, best_dy = s, float(dx), float(dy)
+        best_f = 1.0
+        # только сдвиг и лёгкое РАСШИРЕНИЕ — поджатие (f<1) отрезало часть объекта
+        for f in (1.0, 1.04, 1.08):
+            s = score(best_dx, best_dy, f, c)
+            if s > best_s:
+                best_s, best_f = s, f
+
+        prev = self._snap.get(track_id, (0.0, 0.0, 1.0))
+        a = self.snap_alpha
+        sm = (
+            (1 - a) * prev[0] + a * best_dx,
+            (1 - a) * prev[1] + a * best_dy,
+            max(1.0, (1 - a) * prev[2] + a * best_f),
+        )
+        self._snap[track_id] = sm
+        out = pts.copy()
+        out[:, 0] = c[0] + sm[2] * (xs - c[0]) + sm[0]
+        out[:, 1] = c[1] + sm[2] * (ys - c[1]) + sm[1]
+        return out
+
+    def drop_missing(self, alive_ids: set) -> None:
+        for tid in list(self._acc.keys()):
+            if tid not in alive_ids:
+                del self._acc[tid]
+                self._snap.pop(tid, None)
+
+
+def align_color(color_bgr: np.ndarray, dx: float, dy: float, scale: float) -> np.ndarray:
+    """Совмещение RGB с depth: сдвиг+масштаб (у D415 сенсоры разнесены)."""
+    if abs(dx) < 0.5 and abs(dy) < 0.5 and abs(scale - 1.0) < 1e-3:
+        return color_bgr
+    h, w = color_bgr.shape[:2]
+    M = np.float32([
+        [scale, 0, dx + (1.0 - scale) * w / 2.0],
+        [0, scale, dy + (1.0 - scale) * h / 2.0],
+    ])
+    return cv2.warpAffine(color_bgr, M, (w, h), flags=cv2.INTER_LINEAR)
+
+
+def build_demo_frame(
+    color_bgr: np.ndarray,
+    depth_mm: np.ndarray,
+    tracks: list,  # List[tracker.Track]
+    belt_mm: float,
+    stats: Optional[Dict[str, int]] = None,
+    confidence_pct: int = 75,
+    rgb_available: bool = False,
+    background_active: bool = False,
+    color_align: Tuple[float, float, float] = (0.0, 0.0, 1.0),
+    contour_smoother: Optional[ContourSmoother] = None,
+) -> np.ndarray:
+    from camera import depth_colormap
+
+    # RGB для веба; если цвет недоступен — colorize(depth), НЕ чёрный экран
+    if rgb_available and color_bgr is not None and float(np.std(color_bgr)) > 4.0:
+        base = color_bgr
+        if base.shape[:2] != depth_mm.shape[:2]:
+            base = cv2.resize(base, (depth_mm.shape[1], depth_mm.shape[0]))
+        base = align_color(base, color_align[0], color_align[1], color_align[2])
+        view = base.copy()
+        rgb_ok = True
+    else:
+        view = depth_colormap(depth_mm)
+        view = cv2.medianBlur(view, 3)
+        base = view
+        rgb_ok = False
+    h, w = view.shape[:2]
+
+    # мягкое поле RGB-краёв для «примагничивания» контуров
+    edge_field: Optional[np.ndarray] = None
+    if rgb_ok and contour_smoother is not None and tracks:
+        gray = cv2.cvtColor(base, cv2.COLOR_BGR2GRAY)
+        gray = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8, 8)).apply(gray)
+        edge_field = cv2.Canny(cv2.GaussianBlur(gray, (5, 5), 0), 40, 120)
+        edge_field = cv2.GaussianBlur(edge_field, (13, 13), 0)
+
+    texts: List[Tuple[int, int, str, Tuple[int, int, int], int]] = []
+    max_conf_pending = 0
+    all_locked = bool(tracks)
+    alive_ids = set()
+
+    for tr in tracks:
+        m = tr.measurement
+        d = tr.decision
+        if m is None or d is None:
+            continue
+        alive_ids.add(tr.track_id)
+        locked = d.locked and d.result is not None
+        if locked:
+            color = UNCERTAIN_COLOR if d.uncertain else ZONE_COLOR.get(d.result.category.zone, PENDING_COLOR)
+        else:
+            color = PENDING_COLOR
+            all_locked = False
+            max_conf_pending = max(max_conf_pending, d.confidence_pct)
+
+        # bbox / класс — по сырому контуру измерения; сглаживание только для окантовки «анализ»
+        raw_contour = m.contour
+        draw_contour = raw_contour
+        if not locked and contour_smoother is not None:
+            sm = contour_smoother.smooth(tr.track_id, m.mask, edge_img=edge_field)
+            if sm is not None:
+                draw_contour = sm
+        if locked:
+            bx, by, bw, bh = cv2.boundingRect(raw_contour)
+            # небольшой запас, чтобы рамка не обрезала края
+            pad = 4
+            bx, by = max(0, bx - pad), max(0, by - pad)
+            bw = min(w - bx, bw + 2 * pad)
+            bh = min(h - by, bh + 2 * pad)
+            cv2.rectangle(view, (bx, by), (bx + bw, by + bh), color, 2, lineType=cv2.LINE_AA)
+            cl = max(8, min(bw, bh) // 5)
+            for px, py, sx, sy in ((bx, by, 1, 1), (bx + bw, by, -1, 1),
+                                   (bx, by + bh, 1, -1), (bx + bw, by + bh, -1, -1)):
+                cv2.line(view, (px, py), (px + sx * cl, py), color, 4, lineType=cv2.LINE_AA)
+                cv2.line(view, (px, py), (px, py + sy * cl), color, 4, lineType=cv2.LINE_AA)
+            contour = raw_contour
+        else:
+            cv2.drawContours(view, [draw_contour], -1, color, 2, lineType=cv2.LINE_AA)
+            contour = draw_contour
+        ccx, ccy = contour.reshape(-1, 2).mean(axis=0)
+        cv2.circle(view, (int(ccx), int(ccy)), 4, (0, 0, 255), -1, lineType=cv2.LINE_AA)
+
+        x0, y0, _, _ = cv2.boundingRect(contour)
+        tx = int(np.clip(x0, 4, w - 220))
+        ty = int(np.clip(y0 - 46, 4, h - 46))
+        if locked:
+            label = d.result.category.short_label
+            if d.uncertain:
+                label = "НЕУВЕРЕННО → " + label
+            texts.append((tx, ty, f"#{tr.track_id} {label}", color, 20))
+        else:
+            texts.append((tx, ty, f"#{tr.track_id} анализ… {d.confidence_pct}%", color, 20))
+        dims = d.result.dims_sorted_mm if (locked and d.result) else (m.length_mm, m.width_mm, m.height_mm)
+        ratio = d.result.circle_ratio if (locked and d.result) else m.circle_ratio
+        src = " · RGB" if getattr(m, "source", "depth") == "rgb" else ""
+        texts.append(
+            (tx, ty + 24, f"{dims[0]:.0f}×{dims[1]:.0f}×{dims[2]:.0f} мм · круг {ratio:.2f}{src}", (235, 235, 235), 15)
+        )
+
+    if contour_smoother is not None:
+        contour_smoother.drop_missing(alive_ids)
+
+    view = _draw_texts(view, texts)
+
+    # надписи — в отдельной полосе НАД кадром, чтобы не закрывать камеру
+    top_bar = np.full((36, w, 3), 18, np.uint8)
+    st = stats or {}
+    stats_line = (
+        f"ГОТОВ {st.get('B', 0)} · НЕГАБАРИТ {st.get('C', 0)} · ДОУПАК {st.get('D', 0)}"
+        + (f" · неувер. {st['uncertain']}" if st.get("uncertain") else "")
+    )
+    bg_tag = " · фон:карта" if background_active else ""
+    left = "объектов нет" if not tracks else f"объектов: {len(alive_ids)}"
+    top_texts = [
+        (10, 6, left, (150, 150, 255) if not tracks else (200, 230, 200), 17),
+        (max(200, w - 440), 8, f"{stats_line} | h={belt_mm:.0f}мм{bg_tag}", (200, 230, 200), 14),
+    ]
+    top_bar = _draw_texts(top_bar, top_texts)
+    view = np.vstack([top_bar, view])
+    h = view.shape[0]
+
+    # прогресс уверенности внизу
+    bar_y = h - 8
+    cv2.rectangle(view, (0, bar_y), (w, h), (40, 40, 40), -1)
+    conf_show = 100 if (all_locked and tracks) else max_conf_pending
+    fill = int(w * min(1.0, conf_show / 100.0))
+    col = (40, 200, 40) if (all_locked and tracks) else (0, 200, 255)
+    cv2.rectangle(view, (0, bar_y), (fill, h), col, -1)
+    thr = int(w * confidence_pct / 100.0)
+    cv2.line(view, (thr, bar_y), (thr, h), (255, 255, 255), 1)
+
+    return view
--- a/vision_classifier/docker-compose.yml
+++ b/vision_classifier/docker-compose.yml
@@ -0,0 +1,23 @@
+services:
+  vision:
+    build: .
+    container_name: realsense_vision
+    restart: unless-stopped
+    network_mode: host
+    privileged: true
+    devices:
+      - /dev/video0:/dev/video0
+      - /dev/video1:/dev/video1
+      - /dev/video2:/dev/video2
+      - /dev/video3:/dev/video3
+      - /dev/video4:/dev/video4
+      - /dev/video5:/dev/video5
+    volumes:
+      - ./config.yaml:/app/config.yaml:ro
+      - ./debug_frames:/app/debug_frames
+    group_add:
+      - video
+    environment:
+      - QT_X11_NO_MITSHM=1
+    # Без GUI в контейнере по умолчанию; превью — через native run
+    command: ["python", "main.py", "-c", "config.yaml"]
--- a/vision_classifier/journal.py
+++ b/vision_classifier/journal.py
@@ -0,0 +1,47 @@
+"""JSONL-журнал решений классификатора — метрики для отчёта и защиты.
+
+Каждая строка — одно зафиксированное решение (LOCK):
+время, зона, габариты, circle_ratio, флаг «неуверенно», причина.
+
+Анализ (корректность, доля неуверенных, распределение зон):
+  .venv/bin/python -c "
+  import json;
+  rows=[json.loads(l) for l in open('logs/decisions.jsonl')];
+  from collections import Counter;
+  print(Counter(r['zone'] for r in rows));
+  print('uncertain:', sum(r['uncertain'] for r in rows), '/', len(rows))"
+"""
+
+from __future__ import annotations
+
+import json
+import time
+from pathlib import Path
+
+from classify import ClassificationResult
+
+
+def append_decision(
+    path: str | Path,
+    result: ClassificationResult,
+    uncertain: bool = False,
+    source: str = "main",
+    track_id: int | None = None,
+) -> None:
+    entry = {
+        "track_id": track_id,
+        "ts": time.strftime("%Y-%m-%dT%H:%M:%S"),
+        "ts_ms": int(time.time() * 1000),
+        "zone": result.category.zone,
+        "category": result.category.value,
+        "label_ru": result.category.ru_label,
+        "dims_mm": [round(float(x), 1) for x in result.dims_sorted_mm],
+        "circle_ratio": round(float(result.circle_ratio), 4),
+        "uncertain": bool(uncertain),
+        "reason": result.reason,
+        "source": source,
+    }
+    p = Path(path)
+    p.parent.mkdir(parents=True, exist_ok=True)
+    with open(p, "a", encoding="utf-8") as f:
+        f.write(json.dumps(entry, ensure_ascii=False) + "\n")
--- a/vision_classifier/logs/decisions.jsonl
+++ b/vision_classifier/logs/decisions.jsonl
@@ -0,0 +1,742 @@
+{"ts": "2026-07-28T17:10:28", "ts_ms": 1785247828677, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [253.7, 116.5, 114.1], "circle_ratio": 0.5161, "uncertain": false, "reason": "не круг: med=0.516 sec=0.435 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:29", "ts_ms": 1785247829097, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:29", "ts_ms": 1785247829149, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:29", "ts_ms": 1785247829363, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:29", "ts_ms": 1785247829417, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:29", "ts_ms": 1785247829740, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:29", "ts_ms": 1785247829964, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:30", "ts_ms": 1785247830018, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:30", "ts_ms": 1785247830070, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:30", "ts_ms": 1785247830126, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:30", "ts_ms": 1785247830287, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:30", "ts_ms": 1785247830341, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:30", "ts_ms": 1785247830397, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:30", "ts_ms": 1785247830553, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:30", "ts_ms": 1785247830816, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:30", "ts_ms": 1785247830867, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
+{"ts": "2026-07-28T17:10:31", "ts_ms": 1785247831023, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [113.9, 71.1, 27.0], "circle_ratio": 0.6216, "uncertain": false, "reason": "не круг: med=0.622 sec=0.458 strong=0% < 0.8", "source": "demo"}
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+{"track_id": null, "ts": "2026-08-02T23:54:53", "ts_ms": 1785689693104, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [80.1, 29.2, 21.5], "circle_ratio": 0.4371, "uncertain": false, "reason": "не круг: med=0.437 sec=0.327 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:06:08", "ts_ms": 1785690368310, "zone": "C", "category": "oversize", "label_ru": "Не подходит для сортировки по габаритам", "dims_mm": [500.0, 240.0, 105.8], "circle_ratio": 0.3071, "uncertain": false, "reason": "объект обрезан краем кадра → габарит неполный, считаем негабаритом", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:46:18", "ts_ms": 1785692778248, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [75.3, 55.6, 53.0], "circle_ratio": 0.6405, "uncertain": false, "reason": "не круг: med=0.641 sec=0.399 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:46:25", "ts_ms": 1785692785439, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [77.1, 70.0, 54.4], "circle_ratio": 0.6187, "uncertain": false, "reason": "не круг: med=0.619 sec=0.438 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:46:29", "ts_ms": 1785692789873, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [76.9, 71.5, 25.9], "circle_ratio": 0.3387, "uncertain": false, "reason": "не круг: med=0.339 sec=0.108 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:46:46", "ts_ms": 1785692806035, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [119.5, 56.8, 47.9], "circle_ratio": 0.6865, "uncertain": false, "reason": "не круг: med=0.686 sec=0.212 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:46:47", "ts_ms": 1785692807010, "zone": "D", "category": "need_pack", "label_ru": "Не подходит для сортировки без доупаковки", "dims_mm": [169.0, 68.6, 65.3], "circle_ratio": 0.8745, "uncertain": false, "reason": "круг: med=0.874 p75=0.899 top=0.874 sec=0.405 strong=8% >= 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:46:49", "ts_ms": 1785692809570, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [126.0, 48.6, 34.2], "circle_ratio": 0.6214, "uncertain": false, "reason": "не круг: med=0.621 sec=0.243 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:46:52", "ts_ms": 1785692812625, "zone": "C", "category": "oversize", "label_ru": "Не подходит для сортировки по габаритам", "dims_mm": [500.0, 204.4, 97.0], "circle_ratio": 0.5, "uncertain": false, "reason": "габариты вне допуска: нужно >10×10×10 и <450×320×320 мм", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:46:53", "ts_ms": 1785692813095, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [285.5, 204.4, 97.0], "circle_ratio": 0.6026, "uncertain": false, "reason": "не круг: med=0.603 sec=0.185 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:46:57", "ts_ms": 1785692817697, "zone": "D", "category": "need_pack", "label_ru": "Не подходит для сортировки без доупаковки", "dims_mm": [207.0, 204.5, 60.5], "circle_ratio": 0.9458, "uncertain": false, "reason": "круг: med=0.946 p75=0.952 top=0.946 sec=0.155 strong=0% >= 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:47:00", "ts_ms": 1785692820148, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [204.8, 120.8, 70.0], "circle_ratio": 0.5863, "uncertain": false, "reason": "не круг: med=0.586 sec=0.345 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:48:01", "ts_ms": 1785692881972, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [132.0, 59.4, 51.6], "circle_ratio": 0.6828, "uncertain": false, "reason": "не круг: med=0.683 sec=0.295 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:48:02", "ts_ms": 1785692882612, "zone": "D", "category": "need_pack", "label_ru": "Не подходит для сортировки без доупаковки", "dims_mm": [168.0, 70.4, 66.4], "circle_ratio": 0.8631, "uncertain": false, "reason": "круг: med=0.863 p75=0.876 top=0.855 sec=0.735 strong=42% >= 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:48:05", "ts_ms": 1785692885397, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [142.5, 48.4, 29.5], "circle_ratio": 0.5428, "uncertain": false, "reason": "не круг: med=0.543 sec=0.270 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:48:09", "ts_ms": 1785692889600, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [76.5, 71.5, 57.9], "circle_ratio": 0.6528, "uncertain": false, "reason": "не круг: med=0.653 sec=0.452 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:49:06", "ts_ms": 1785692946351, "zone": "C", "category": "oversize", "label_ru": "Не подходит для сортировки по габаритам", "dims_mm": [500.0, 117.0, 45.2], "circle_ratio": 0.1306, "uncertain": false, "reason": "объект обрезан краем кадра → габарит неполный, считаем негабаритом", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:49:45", "ts_ms": 1785692985263, "zone": "C", "category": "oversize", "label_ru": "Не подходит для сортировки по габаритам", "dims_mm": [500.0, 190.5, 161.5], "circle_ratio": 0.4301, "uncertain": false, "reason": "объект обрезан краем кадра → габарит неполный, считаем негабаритом", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:50:18", "ts_ms": 1785693018054, "zone": "C", "category": "oversize", "label_ru": "Не подходит для сортировки по габаритам", "dims_mm": [500.0, 113.5, 43.9], "circle_ratio": 0.1363, "uncertain": false, "reason": "объект обрезан краем кадра → габарит неполный, считаем негабаритом", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:50:25", "ts_ms": 1785693025762, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [86.5, 75.3, 72.0], "circle_ratio": 0.6856, "uncertain": false, "reason": "не круг: med=0.686 sec=0.363 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:50:45", "ts_ms": 1785693045940, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [55.0, 49.2, 26.3], "circle_ratio": 0.5988, "uncertain": false, "reason": "не круг: med=0.599 sec=0.221 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:50:47", "ts_ms": 1785693047050, "zone": "D", "category": "need_pack", "label_ru": "Не подходит для сортировки без доупаковки", "dims_mm": [81.0, 50.1, 48.4], "circle_ratio": 0.8419, "uncertain": false, "reason": "круг: med=0.842 p75=0.855 top=0.842 sec=0.528 strong=0% >= 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:50:51", "ts_ms": 1785693051014, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [125.0, 55.1, 46.2], "circle_ratio": 0.6391, "uncertain": false, "reason": "не круг: med=0.639 sec=0.331 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:50:51", "ts_ms": 1785693051992, "zone": "D", "category": "need_pack", "label_ru": "Не подходит для сортировки без доупаковки", "dims_mm": [179.0, 48.6, 47.1], "circle_ratio": 0.9012, "uncertain": false, "reason": "круг: med=0.901 p75=0.909 top=0.901 sec=0.515 strong=0% >= 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:50:54", "ts_ms": 1785693054037, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [158.5, 50.1, 46.1], "circle_ratio": 0.5833, "uncertain": false, "reason": "не круг: med=0.583 sec=0.326 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:50:57", "ts_ms": 1785693057600, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [172.9, 61.0, 54.8], "circle_ratio": 0.4696, "uncertain": false, "reason": "не круг: med=0.470 sec=0.470 strong=0% < 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:50:59", "ts_ms": 1785693059249, "zone": "D", "category": "need_pack", "label_ru": "Не подходит для сортировки без доупаковки", "dims_mm": [205.8, 205.0, 61.0], "circle_ratio": 0.9515, "uncertain": false, "reason": "круг: med=0.952 p75=0.952 top=0.952 sec=0.187 strong=0% >= 0.8", "source": "main"}
+{"track_id": null, "ts": "2026-08-03T00:51:01", "ts_ms": 1785693061632, "zone": "B", "category": "suitable", "label_ru": "Подходит для сортировки", "dims_mm": [205.3, 117.9, 70.0], "circle_ratio": 0.5758, "uncertain": false, "reason": "не круг: med=0.576 sec=0.329 strong=0% < 0.8", "source": "main"}
--- a/vision_classifier/main.py
+++ b/vision_classifier/main.py
@@ -0,0 +1,320 @@
+#!/usr/bin/env python3
+"""
+Алгоритмическая часть трека 3: Intel RealSense D415 на Orange PI.
+
+Пайплайн:
+  depth+color → сегментация объекта на ленте → габариты L×W×H + circle_ratio
+  → классификация (B/C/D) → MQTT → сервоприводы Arduino (без правок arduino_code).
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+import time
+from pathlib import Path
+from typing import Any, Dict, Optional
+
+import cv2
+import yaml
+
+from camera import RealSenseV4L2, depth_colormap
+from classify import Category, ClassificationResult
+from journal import append_decision
+from measure import measure_flat_object, measure_object, segment_objects, segment_rgb_objects, is_plausible_measurement
+from mqtt_bridge import MqttBridge
+from stabilize import DecisionStabilizer
+
+ZONE_TO_CATEGORY = {
+    "B": Category.SUITABLE,
+    "C": Category.OVERSIZE,
+    "D": Category.NEED_PACK,
+}
+
+
+def load_config(path: Path) -> Dict[str, Any]:
+    with open(path, "r", encoding="utf-8") as f:
+        return yaml.safe_load(f)
+
+
+def draw_overlay(
+    color_bgr,
+    depth_mm,
+    measurement,
+    result: Optional[ClassificationResult],
+    belt_mm: float,
+):
+    vis = color_bgr.copy()
+    depth_vis = depth_colormap(depth_mm)
+    if measurement is not None:
+        cv2.drawContours(vis, [measurement.contour], -1, (0, 255, 0), 2)
+        cx, cy = measurement.centroid_px
+        cv2.circle(vis, (cx, cy), 4, (0, 0, 255), -1)
+        lines = [
+            f"L={measurement.length_mm:.0f} W={measurement.width_mm:.0f} H={measurement.height_mm:.0f} mm",
+            f"circle_ratio={measurement.circle_ratio:.3f}",
+        ]
+        if result is not None:
+            lines.append(f"{result.category.zone}: {result.category.ru_label}")
+        y = 24
+        for line in lines:
+            cv2.putText(vis, line, (10, y), cv2.FONT_HERSHEY_SIMPLEX, 0.55, (20, 20, 20), 3, cv2.LINE_AA)
+            cv2.putText(vis, line, (10, y), cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 255, 255), 1, cv2.LINE_AA)
+            y += 22
+    cv2.putText(
+        vis,
+        f"belt={belt_mm:.0f}mm",
+        (10, vis.shape[0] - 12),
+        cv2.FONT_HERSHEY_SIMPLEX,
+        0.5,
+        (200, 200, 200),
+        1,
+        cv2.LINE_AA,
+    )
+    return vis, depth_vis
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="RealSense D415 classifier for hackathon track 3")
+    parser.add_argument(
+        "-c",
+        "--config",
+        default=str(Path(__file__).with_name("config.yaml")),
+        help="Путь к config.yaml",
+    )
+    parser.add_argument("--once", action="store_true", help="Один кадр и выход")
+    parser.add_argument("--no-mqtt", action="store_true", help="Не публиковать в MQTT")
+    parser.add_argument(
+        "--preview",
+        action="store_true",
+        help="Живое превью в debug_frames/live_*.jpg (без GTK-окон)",
+    )
+    parser.add_argument("--dry-route", action="store_true", help="Не двигать серво")
+    parser.add_argument("--no-motor", action="store_true", help="Не включать шаговик ленты")
+    args = parser.parse_args()
+
+    cfg = load_config(Path(args.config))
+    cam_cfg = cfg["camera"]
+    cls_cfg = cfg["classification"]
+    rt = cfg.get("runtime", {})
+    mqtt_cfg = dict(cfg.get("mqtt", {}))
+    routing_cfg = dict(cfg.get("routing", {}))
+    motor_cfg = dict(cfg.get("motor", {}))
+    if args.no_mqtt:
+        mqtt_cfg["enabled"] = False
+    if args.dry_route:
+        routing_cfg["enabled"] = False
+    if args.no_motor:
+        motor_cfg["enabled"] = False
+    mqtt_cfg["_routing"] = routing_cfg
+    mqtt_cfg["_motor"] = motor_cfg
+
+    show_preview = args.preview or bool(rt.get("show_preview", False))
+    save_debug = bool(rt.get("save_debug_frames", False)) or show_preview
+    debug_dir = Path(rt.get("debug_dir", "debug_frames"))
+    if save_debug or show_preview:
+        debug_dir.mkdir(parents=True, exist_ok=True)
+    live_color = debug_dir / "live_color.jpg"
+    live_depth = debug_dir / "live_depth.jpg"
+    preview_every = max(1, int(rt.get("preview_every_n", 3)))
+
+    print("[vision] открываю RealSense D415…")
+    cam = RealSenseV4L2(
+        depth_device=cam_cfg.get("depth_device", "/dev/video0"),
+        color_device=cam_cfg.get("color_device", "/dev/video4"),
+        width=int(cam_cfg.get("width", 640)),
+        height=int(cam_cfg.get("height", 480)),
+        fps=int(cam_cfg.get("fps", 30)),
+        depth_scale_mm=float(cam_cfg.get("depth_scale_mm", 1.0)),
+        use_color=bool(cfg.get("use_color", False)),
+    )
+
+    belt_mm = float(cfg.get("belt_distance_mm") or 0)
+    if belt_mm <= 0:
+        print("[vision] калибровка плоскости ленты (уберите объекты)…")
+        belt_mm = cam.estimate_belt_distance_mm()
+        print(f"[vision] belt_distance_mm ≈ {belt_mm:.1f}")
+    else:
+        print(f"[vision] belt_distance_mm из конфига: {belt_mm:.1f}")
+
+    background = None
+    color_background = None
+    if bool(cfg.get("use_background_map", False)):
+        print("[vision] снимаю фоновую карту сцены — лента должна быть ПУСТОЙ…")
+        try:
+            background = cam.capture_background(samples=15)
+            print("[vision] фоновая карта активна (сегментация относительно фона)")
+        except RuntimeError as exc:
+            print(f"[vision] фоновая карта не снята ({exc}), работаю по скалярной высоте")
+        color_background = cam.capture_background_rgb(samples=10)
+        if color_background is not None:
+            print("[vision] RGB-фон снят — плоские товары (телефон) будут детектироваться")
+
+    bridge = MqttBridge(mqtt_cfg)
+    print(f"[vision] MQTT: {'OK' if bridge.connected else 'offline/disabled'}")
+    if bridge.connected:
+        bridge.start_conveyor()
+    if show_preview:
+        print(f"[vision] превью → {live_color} и {live_depth} (обновляются на лету)")
+        print("[vision] откройте файлы в IDE/файловом менеджере или: eog debug_frames/live_color.jpg")
+
+    confirm_need = int(rt.get("confirm_frames", 8))
+    process_every_n = max(1, int(rt.get("process_every_n", 1)))
+    frame_i = 0
+    thr = float(cls_cfg.get("circle_ratio_threshold", 0.8))
+    fallback_zone = str(cls_cfg.get("uncertain_fallback_zone", "C")).upper()
+    stabilizer = DecisionStabilizer(
+        window=12,
+        confirm_frames=confirm_need,
+        lost_frames=12,
+        enter_circle=thr,
+        exit_circle=thr - 0.08,
+        uncertain_after=int(cls_cfg.get("uncertain_after_frames", 45)),
+        fallback=ZONE_TO_CATEGORY.get(fallback_zone, Category.OVERSIZE),
+    )
+    last_routed_zone: Optional[str] = None
+    decisions_log = Path(rt.get("decisions_log", "logs/decisions.jsonl"))
+
+    fx, fy = float(cam_cfg["fx"]), float(cam_cfg["fy"])
+    cx, cy = float(cam_cfg["cx"]), float(cam_cfg["cy"])
+
+    try:
+        while True:
+            pair = cam.read()
+            if pair is None:
+                print("[vision] нет кадра", file=sys.stderr)
+                time.sleep(0.05)
+                continue
+
+            frame_i += 1
+            measurement = None
+            result = None
+
+            if frame_i % process_every_n == 0:
+                candidates = segment_objects(
+                    pair.depth_mm,
+                    belt_distance_mm=belt_mm,
+                    belt_tolerance_mm=float(cfg.get("belt_tolerance_mm", 25)),
+                    min_object_height_mm=float(cfg.get("min_object_height_mm", 5)),
+                    min_area_px=int(cfg.get("min_object_area_px", 800)),
+                    background_mm=background,
+                    max_objects=int(cfg.get("max_objects_in_frame", 3)),
+                    roi_margin=cfg.get("roi_margin"),
+                )
+                seg = None
+                best = None  # (score, mask, contour, measurement)
+                for mask, contour in candidates:
+                    m_try = measure_object(
+                        pair.depth_mm,
+                        mask,
+                        contour,
+                        belt_distance_mm=belt_mm,
+                        fx=fx,
+                        fy=fy,
+                        cx=cx,
+                        cy=cy,
+                        background_mm=background,
+                        min_object_height_mm=float(cfg.get("min_object_height_mm", 8)),
+                        roi_margin=cfg.get("roi_margin"),
+                    )
+                    if m_try is None or not is_plausible_measurement(m_try):
+                        continue
+                    # приоритет: круглый и более высокий товар над шумом ленты
+                    score = float(m_try.circle_ratio) * 2.0 + min(float(m_try.height_mm), 200.0) / 100.0
+                    if best is None or score > best[0]:
+                        best = (score, mask, contour, m_try)
+                if best is not None:
+                    _, mask, contour, measurement = best
+                    seg = (mask, contour)
+                else:
+                    measurement = None
+
+                # depth ничего не видит → плоский товар (телефон) ищем по RGB
+                if (
+                    measurement is None
+                    and bool(cfg.get("detect_flat_rgb", False))
+                    and color_background is not None
+                    and not pair.color_is_depth_preview
+                ):
+                    rgb_objs = segment_rgb_objects(
+                        pair.color_bgr,
+                        color_background,
+                        min_area_px=int(cfg.get("min_object_area_px", 800)),
+                        diff_threshold=int(cfg.get("rgb_diff_threshold", 35)),
+                        max_objects=1,
+                        exclude_mask=seg[0] if seg is not None else None,
+                    )
+                    if rgb_objs:
+                        mask, contour = rgb_objs[0]
+                        measurement = measure_flat_object(
+                            pair.depth_mm,
+                            mask,
+                            contour,
+                            belt_distance_mm=belt_mm,
+                            fx=fx,
+                            fy=fy,
+                            cx=cx,
+                            cy=cy,
+                            background_mm=background,
+                            color_bgr=pair.color_bgr,
+                            color_bg_bgr=color_background,
+                        )
+
+                if measurement is not None and not is_plausible_measurement(measurement):
+                    measurement = None
+
+                decision = stabilizer.update(
+                    measurement,
+                    min_mm=cls_cfg.get("min_mm", [10, 10, 10]),
+                    max_mm=cls_cfg.get("max_mm", [450, 320, 320]),
+                )
+                if decision.locked and decision.result is not None:
+                    result = decision.result
+                    zone = result.category.zone
+                    if zone != last_routed_zone:
+                        tag = "UNCERTAIN→" if decision.uncertain else "LOCK "
+                        print(
+                            f"[vision] {tag}{zone} | {result.category.ru_label} | "
+                            f"dims={result.dims_sorted_mm} | ratio={result.circle_ratio:.3f} | {result.reason}"
+                        )
+                        append_decision(decisions_log, result, uncertain=decision.uncertain, source="main")
+                        bridge.publish_result(result)
+                        bridge.route(result.category)
+                        last_routed_zone = zone
+                elif not decision.present:
+                    last_routed_zone = None
+
+            if show_preview or save_debug:
+                vis, depth_vis = draw_overlay(pair.color_bgr, pair.depth_mm, measurement, result, belt_mm)
+                if save_debug and result is not None and not show_preview:
+                    out = debug_dir / f"frame_{frame_i:06d}_{result.category.value}.jpg"
+                    cv2.imwrite(str(out), vis)
+                # headless OpenCV: пишем JPEG вместо cv2.imshow
+                if show_preview and frame_i % preview_every == 0:
+                    cv2.imwrite(str(live_color), vis)
+                    cv2.imwrite(str(live_depth), depth_vis)
+
+            if args.once:
+                if result is not None:
+                    print(result)
+                if show_preview:
+                    vis, depth_vis = draw_overlay(pair.color_bgr, pair.depth_mm, measurement, result, belt_mm)
+                    cv2.imwrite(str(live_color), vis)
+                    cv2.imwrite(str(live_depth), depth_vis)
+                    print(f"[vision] кадр сохранён: {live_color}")
+                break
+
+    except KeyboardInterrupt:
+        print("\n[vision] stop")
+    finally:
+        bridge.close()
+        cam.release()
+
+    return 0
+
+
+if __name__ == "__main__":
+    # Чтобы импорты работали и как пакет, и как скрипт
+    sys.path.insert(0, str(Path(__file__).resolve().parent))
+    raise SystemExit(main())
--- a/vision_classifier/measure.py
+++ b/vision_classifier/measure.py
@@ -0,0 +1,719 @@
+"""Сегментация и измерение по ТЗ трека 3 — без эвристик «подкрутки»."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import List, Optional, Tuple
+
+import cv2
+import numpy as np
+
+
+@dataclass
+class ObjectMeasurement:
+    length_mm: float
+    width_mm: float
+    height_mm: float
+    circle_ratio: float  # итог для классификатора: max устойчивых сечений
+    area_px: int
+    centroid_px: Tuple[int, int]
+    contour: np.ndarray
+    mask: np.ndarray
+    top_ratio: float = 0.0  # rin/rout вида сверху
+    section_ratio: float = 0.0  # лучший устойчивый 3D-срез
+    source: str = "depth"  # "depth" | "rgb" (плоский товар, найден по RGB)
+    clipped_by_frame: bool = False  # объект упирается в край кадра → габарит неполный
+
+
+def is_plausible_measurement(
+    m: ObjectMeasurement,
+    min_footprint_mm: float = 15.0,
+) -> bool:
+    """Отсев шума depth/RGB до классификации (не путать с ТЗ-негабаритом).
+
+    Мелкие пятна и «0×0×0 мм» не должны попадать в трекер — иначе
+    check_size(<10 мм) даёт ложный класс C.
+    """
+    L, W, H = float(m.length_mm), float(m.width_mm), float(m.height_mm)
+    if L <= 1.5 or W <= 1.5:
+        return False
+    if int(m.area_px) < 120:
+        return False
+    a, b, c = sorted((L, W, H), reverse=True)
+    if a < min_footprint_mm:
+        return False
+    if c <= 0.5:
+        return False
+    # RGB-шум: нет высоты и крошечное пятно на ленте
+    if getattr(m, "source", "depth") == "rgb" and H < 2.0 and a < 45.0:
+        return False
+    return True
+
+
+def mask_iou(a: np.ndarray, b: np.ndarray) -> float:
+    """Классический IoU масок."""
+    inter = int(np.count_nonzero((a > 0) & (b > 0)))
+    if inter == 0:
+        return 0.0
+    ua = int(np.count_nonzero(a > 0))
+    ub = int(np.count_nonzero(b > 0))
+    return inter / float(ua + ub - inter)
+
+
+def mask_overlap_min(a: np.ndarray, b: np.ndarray) -> float:
+    """Доля пересечения относительно меньшей маски (0..1).
+
+    ≥0.5 ≈ «хотя бы половина одного объекта лежит на другом».
+    Удобнее IoU, когда кусок намного меньше целого.
+    """
+    inter = int(np.count_nonzero((a > 0) & (b > 0)))
+    if inter == 0:
+        return 0.0
+    ua = int(np.count_nonzero(a > 0))
+    ub = int(np.count_nonzero(b > 0))
+    return inter / float(max(1, min(ua, ub)))
+
+
+def merge_overlapping_masks(
+    items: List[Tuple[np.ndarray, np.ndarray]],
+    overlap_thr: float = 0.5,
+    near_gap_px: int = 14,
+) -> List[Tuple[np.ndarray, np.ndarray]]:
+    """Склеить контуры при IoU/пересечении ≥ thr или узкой дыре depth (near_gap)."""
+    if len(items) <= 1:
+        return items
+    items = sorted(items, key=lambda ic: cv2.contourArea(ic[1]), reverse=True)
+    used = [False] * len(items)
+    out: List[Tuple[np.ndarray, np.ndarray]] = []
+
+    def _near(a: np.ndarray, b: np.ndarray) -> bool:
+        xa, ya, wa, ha = cv2.boundingRect(a)
+        xb, yb, wb, hb = cv2.boundingRect(b)
+        g = int(near_gap_px)
+        return not (
+            xa + wa + g < xb or xb + wb + g < xa or ya + ha + g < yb or yb + hb + g < ya
+        )
+
+    for i, (mask_i, _) in enumerate(items):
+        if used[i]:
+            continue
+        merged = mask_i.copy()
+        used[i] = True
+        changed = True
+        while changed:
+            changed = False
+            for j, (mask_j, _) in enumerate(items):
+                if used[j]:
+                    continue
+                hit = (
+                    mask_overlap_min(merged, mask_j) >= overlap_thr
+                    or mask_iou(merged, mask_j) >= overlap_thr
+                    or _near(merged, mask_j)
+                )
+                if hit:
+                    merged = cv2.bitwise_or(merged, mask_j)
+                    used[j] = True
+                    changed = True
+        k = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))
+        merged = cv2.morphologyEx(merged, cv2.MORPH_CLOSE, k, iterations=1)
+        contours, _ = cv2.findContours(merged, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+        if not contours:
+            continue
+        contour = max(contours, key=cv2.contourArea)
+        clean = np.zeros_like(merged)
+        cv2.drawContours(clean, [contour], -1, 255, thickness=-1)
+        out.append((clean, contour))
+    return out
+
+
+def merge_overlapping_measurements(
+    measurements: List[ObjectMeasurement],
+    overlap_thr: float = 0.5,
+) -> List[ObjectMeasurement]:
+    """Склеить измерения с пересекающимися масками (оставить более крупное)."""
+    if len(measurements) <= 1:
+        return measurements
+    ms = sorted(measurements, key=lambda m: m.area_px, reverse=True)
+    kept: List[ObjectMeasurement] = []
+    for m in ms:
+        drop = False
+        for k in kept:
+            if m.mask.shape != k.mask.shape:
+                continue
+            if mask_overlap_min(m.mask, k.mask) >= overlap_thr or mask_iou(m.mask, k.mask) >= overlap_thr:
+                drop = True
+                break
+        if not drop:
+            kept.append(m)
+    return kept
+
+
+def apply_roi_margin(
+    mask: np.ndarray,
+    margin: Optional[dict] = None,
+) -> np.ndarray:
+    """Обнулить края кадра (ролики, борта, плата), доли 0..1 от H/W."""
+    if not margin:
+        return mask
+    h, w = mask.shape[:2]
+    top = int(h * float(margin.get("top", 0)))
+    bottom = int(h * float(margin.get("bottom", 0)))
+    left = int(w * float(margin.get("left", 0)))
+    right = int(w * float(margin.get("right", 0)))
+    out = mask.copy()
+    if top > 0:
+        out[:top, :] = 0
+    if bottom > 0:
+        out[h - bottom :, :] = 0
+    if left > 0:
+        out[:, :left] = 0
+    if right > 0:
+        out[:, w - right :] = 0
+    return out
+
+
+def contour_touches_border(
+    contour: np.ndarray,
+    shape: Tuple[int, ...],
+    margin_px: int = 3,
+    roi_margin: Optional[dict] = None,
+) -> bool:
+    """True если контур упирается в край кадра/ROI — реальный размер может быть больше."""
+    h, w = int(shape[0]), int(shape[1])
+    top = int(h * float((roi_margin or {}).get("top", 0)))
+    bottom = int(h * float((roi_margin or {}).get("bottom", 0)))
+    left = int(w * float((roi_margin or {}).get("left", 0)))
+    right = int(w * float((roi_margin or {}).get("right", 0)))
+    y0, y1 = top + margin_px, h - bottom - 1 - margin_px
+    x0, x1 = left + margin_px, w - right - 1 - margin_px
+    pts = contour.reshape(-1, 2)
+    xs, ys = pts[:, 0], pts[:, 1]
+    return bool(
+        (xs <= x0).any()
+        or (xs >= x1).any()
+        or (ys <= y0).any()
+        or (ys >= y1).any()
+    )
+
+
+def segment_objects(
+    depth_mm: np.ndarray,
+    belt_distance_mm: float,
+    belt_tolerance_mm: float = 25.0,
+    min_object_height_mm: float = 5.0,
+    min_area_px: int = 800,
+    background_mm: Optional[np.ndarray] = None,
+    max_objects: int = 3,
+    roi_margin: Optional[dict] = None,
+) -> List[Tuple[np.ndarray, np.ndarray]]:
+    """Все объекты в кадре (крупнейшие первыми), до max_objects штук.
+
+    Порог высоты — как раньше (строгий): мягкий «ореол» раздувал маску на ленту
+    и ломал габариты/круг → путаница B/C/D.
+    """
+    valid = (depth_mm > 50) & (depth_mm < 5000)
+    hmin = float(min_object_height_mm)
+    if background_mm is not None:
+        bg = background_mm.astype(np.float32)
+        d = depth_mm.astype(np.float32)
+        raised = valid & (bg > 50) & (d < bg - hmin)
+        near_belt_band = d > (bg - 520.0)
+    else:
+        raised = valid & (depth_mm < (belt_distance_mm - hmin))
+        near_belt_band = depth_mm > (belt_distance_mm - 450)
+    mask = (raised & near_belt_band).astype(np.uint8) * 255
+    mask = apply_roi_margin(mask, roi_margin)
+
+    k_open = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
+    k_close = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))
+    mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, k_open, iterations=1)
+    mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, k_close, iterations=2)
+
+    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    frame_area = mask.shape[0] * mask.shape[1]
+    raw: List[Tuple[np.ndarray, np.ndarray]] = []
+    for contour in sorted(contours, key=cv2.contourArea, reverse=True):
+        area = cv2.contourArea(contour)
+        # крупные товары могут занимать почти весь кадр — не отсекать как шум
+        if area < min_area_px or area > frame_area * 0.92:
+            continue
+        clean = np.zeros_like(mask)
+        cv2.drawContours(clean, [contour], -1, 255, thickness=-1)
+        raw.append((clean, contour))
+
+    # только явное пересечение / узкая щель — не склеивать соседние товары
+    merged = merge_overlapping_masks(raw, overlap_thr=0.5, near_gap_px=14)
+    return merged[:max_objects]
+
+
+def segment_object(
+    depth_mm: np.ndarray,
+    belt_distance_mm: float,
+    belt_tolerance_mm: float = 25.0,
+    min_object_height_mm: float = 5.0,
+    min_area_px: int = 800,
+    background_mm: Optional[np.ndarray] = None,
+    roi_margin: Optional[dict] = None,
+) -> Optional[Tuple[np.ndarray, np.ndarray]]:
+    """Крупнейший объект (для main.py/calibrate.py — один товар в накопителе)."""
+    objs = segment_objects(
+        depth_mm,
+        belt_distance_mm,
+        belt_tolerance_mm=belt_tolerance_mm,
+        min_object_height_mm=min_object_height_mm,
+        min_area_px=min_area_px,
+        background_mm=background_mm,
+        max_objects=1,
+        roi_margin=roi_margin,
+    )
+    return objs[0] if objs else None
+
+
+def _pixel_to_xy_mm(
+    u: float, v: float, z_mm: float, fx: float, fy: float, cx: float, cy: float
+) -> Tuple[float, float]:
+    return (u - cx) * z_mm / fx, (v - cy) * z_mm / fy
+
+
+def measure_object(
+    depth_mm: np.ndarray,
+    mask: np.ndarray,
+    contour: np.ndarray,
+    belt_distance_mm: float,
+    fx: float,
+    fy: float,
+    cx: float,
+    cy: float,
+    background_mm: Optional[np.ndarray] = None,
+    min_object_height_mm: float = 5.0,
+    roi_margin: Optional[dict] = None,
+) -> Optional[ObjectMeasurement]:
+    ys, xs = np.where(mask > 0)
+    if xs.size < 50:
+        return None
+
+    z_vals = depth_mm[ys, xs].astype(np.float32)
+    z_vals = z_vals[z_vals > 0]
+    if z_vals.size < 50:
+        return None
+
+    z_med = float(np.median(z_vals))
+    # высота относительно локального фона (платформа/лента под объектом)
+    belt_local = belt_distance_mm
+    if background_mm is not None:
+        bg_vals = background_mm[ys, xs].astype(np.float32)
+        bg_vals = bg_vals[bg_vals > 50]
+        if bg_vals.size >= 50:
+            belt_local = float(np.median(bg_vals))
+    height_mm = max(0.0, belt_local - z_med)
+
+    pts_mm = []
+    for p in contour.reshape(-1, 2):
+        u, v = float(p[0]), float(p[1])
+        x, y = _pixel_to_xy_mm(u, v, z_med, fx, fy, cx, cy)
+        pts_mm.append([x, y])
+    pts_mm = np.asarray(pts_mm, dtype=np.float32)
+    if pts_mm.shape[0] < 5:
+        return None
+
+    rect = cv2.minAreaRect(pts_mm.reshape(-1, 1, 2))
+    rw, rh = rect[1]
+    length_mm = float(max(rw, rh))
+    width_mm = float(min(rw, rh))
+
+    touches_edge = contour_touches_border(contour, mask.shape, roi_margin=roi_margin)
+    # Негабарит «не влезает в кадр» только если реально занимает большую долю FOV.
+    # Лежачая бутылка может чуть касаться ROI — это не повод форсировать 500 мм.
+    span_x = float(xs.max() - xs.min())
+    span_y = float(ys.max() - ys.min())
+    mh = float((roi_margin or {}).get("top", 0.0)) + float((roi_margin or {}).get("bottom", 0.0))
+    mw = float((roi_margin or {}).get("left", 0.0)) + float((roi_margin or {}).get("right", 0.0))
+    usable_w = mask.shape[1] * max(0.5, 1.0 - mw)
+    usable_h = mask.shape[0] * max(0.5, 1.0 - mh)
+    spans_frame = (span_x >= 0.72 * usable_w) or (span_y >= 0.72 * usable_h)
+    clipped = bool(touches_edge and spans_frame)
+
+    # отсев шума ленты / руки на краю (низкий «холм» большой площади → не товар)
+    # но не отсекаем крупные обрезанные объекты — они уйдут в C
+    if not clipped and height_mm < 30.0 and max(length_mm, width_mm) > 150.0:
+        return None
+    # жёсткий пол — иначе складки ленты дают ложный C
+    if height_mm < max(20.0, float(min_object_height_mm)):
+        return None
+    # раньше >520 отбрасывали → ложный B на негабарите в FOV;
+    # оставляем измерение: classify отправит в C (>450)
+    if max(length_mm, width_mm) > 2000.0 and not clipped:
+        return None
+
+    # объект не помещается в кадр → габарит занижен; форсируем > max ТЗ
+    if clipped:
+        length_mm = max(length_mm, 500.0)
+
+    top_ratio = rin_rout(pts_mm)
+    section_ratio = 0.0
+    cloud = _point_cloud(depth_mm, mask, fx, fy, cx, cy)
+    if cloud is not None:
+        section_ratio = robust_section_ratio(cloud)
+
+    # ТЗ: круг в любом сечении. Один шумный 3D-срез не считаем:
+    # D только если top>=0.8 ИЛИ ≥2 среза >=0.8 (внутри robust_section_ratio).
+    circle_ratio = max(top_ratio, section_ratio)
+    if clipped:
+        # обрезанный негабарит не классифицируем по кругу
+        circle_ratio = min(circle_ratio, 0.5)
+
+    m = cv2.moments(contour)
+    if m["m00"] > 0:
+        cx_px = int(m["m10"] / m["m00"])
+        cy_px = int(m["m01"] / m["m00"])
+    else:
+        cx_px, cy_px = int(xs.mean()), int(ys.mean())
+
+    return ObjectMeasurement(
+        length_mm=length_mm,
+        width_mm=width_mm,
+        height_mm=height_mm,
+        circle_ratio=float(circle_ratio),
+        area_px=int(xs.size),
+        centroid_px=(cx_px, cy_px),
+        contour=contour,
+        mask=mask,
+        top_ratio=float(top_ratio),
+        section_ratio=float(section_ratio),
+        clipped_by_frame=bool(clipped),
+    )
+
+
+def segment_rgb_objects(
+    color_bgr: np.ndarray,
+    color_bg_bgr: np.ndarray,
+    min_area_px: int = 800,
+    diff_threshold: int = 35,
+    max_objects: int = 3,
+    exclude_mask: Optional[np.ndarray] = None,
+) -> List[Tuple[np.ndarray, np.ndarray]]:
+    """Плоские товары (телефон и т.п.) по разнице с RGB-фоном пустой ленты.
+
+    exclude_mask — зоны, уже найденные по depth (не дублируем объекты).
+    Тени (пропорциональное затемнение каналов) отбрасываются.
+    """
+    if color_bgr.shape != color_bg_bgr.shape:
+        return []
+    fg = color_bgr.astype(np.float32)
+    bg = color_bg_bgr.astype(np.float32)
+    gray = np.max(np.abs(fg - bg), axis=2).astype(np.uint8)
+    _, m = cv2.threshold(gray, int(diff_threshold), 255, cv2.THRESH_BINARY)
+
+    ratio = (fg + 8.0) / (bg + 8.0)
+    r_med = np.median(ratio, axis=2)
+    r_spread = np.max(ratio, axis=2) - np.min(ratio, axis=2)
+    is_shadow = (r_med < 0.93) & (r_med > 0.38) & (r_spread < 0.14)
+    m[is_shadow] = 0
+
+    k = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))
+    m = cv2.morphologyEx(m, cv2.MORPH_OPEN, k, iterations=1)
+    m = cv2.morphologyEx(m, cv2.MORPH_CLOSE, k, iterations=2)
+
+    if exclude_mask is not None:
+        excl = cv2.dilate(exclude_mask, cv2.getStructuringElement(cv2.MORPH_RECT, (31, 31)))
+        m[excl > 0] = 0
+
+    contours, _ = cv2.findContours(m, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    out: List[Tuple[np.ndarray, np.ndarray]] = []
+    for contour in sorted(contours, key=cv2.contourArea, reverse=True):
+        if cv2.contourArea(contour) < min_area_px or len(out) >= max_objects:
+            break
+        clean = np.zeros_like(m)
+        cv2.drawContours(clean, [contour], -1, 255, thickness=-1)
+        out.append((clean, contour))
+    return out
+
+
+def measure_flat_object(
+    depth_mm: np.ndarray,
+    mask: np.ndarray,
+    contour: np.ndarray,
+    belt_distance_mm: float,
+    fx: float,
+    fy: float,
+    cx: float,
+    cy: float,
+    background_mm: Optional[np.ndarray] = None,
+    color_bgr: Optional[np.ndarray] = None,
+    color_bg_bgr: Optional[np.ndarray] = None,
+) -> Optional[ObjectMeasurement]:
+    """Измерение товара, найденного по RGB: без отсева по минимальной высоте."""
+    ys, xs = np.where(mask > 0)
+    if xs.size < 50:
+        return None
+
+    z_plane = belt_distance_mm
+    if background_mm is not None:
+        bg_vals = background_mm[ys, xs].astype(np.float32)
+        bg_vals = bg_vals[bg_vals > 50]
+        if bg_vals.size >= 50:
+            z_plane = float(np.median(bg_vals))
+
+    z_vals = depth_mm[ys, xs].astype(np.float32)
+    z_vals = z_vals[z_vals > 0]
+    height_mm = max(0.0, z_plane - float(np.median(z_vals))) if z_vals.size >= 50 else 0.0
+
+    pts_mm = []
+    for p in contour.reshape(-1, 2):
+        x, y = _pixel_to_xy_mm(float(p[0]), float(p[1]), z_plane, fx, fy, cx, cy)
+        pts_mm.append([x, y])
+    pts_mm = np.asarray(pts_mm, dtype=np.float32)
+    if pts_mm.shape[0] < 3:
+        return None
+
+    rect = cv2.minAreaRect(pts_mm.reshape(-1, 1, 2))
+    rw, rh = rect[1]
+    length_mm = float(max(rw, rh))
+    width_mm = float(min(rw, rh))
+    if max(length_mm, width_mm) > 520.0 or max(length_mm, width_mm) < 5.0:
+        return None
+
+    top_ratio = rin_rout(pts_mm)
+
+    m = cv2.moments(contour)
+    if m["m00"] > 0:
+        cx_px, cy_px = int(m["m10"] / m["m00"]), int(m["m01"] / m["m00"])
+    else:
+        cx_px, cy_px = int(xs.mean()), int(ys.mean())
+
+    return ObjectMeasurement(
+        length_mm=length_mm,
+        width_mm=width_mm,
+        height_mm=float(height_mm),
+        circle_ratio=float(top_ratio),
+        area_px=int(xs.size),
+        centroid_px=(cx_px, cy_px),
+        contour=contour,
+        mask=mask,
+        top_ratio=float(top_ratio),
+        section_ratio=0.0,
+        source="rgb",
+    )
+
+
+def rin_rout(pts_xy: np.ndarray) -> float:
+    """ТЗ: r_in / r_out по выпуклой оболочке сечения."""
+    pts = np.asarray(pts_xy, dtype=np.float32).reshape(-1, 2)
+    if pts.shape[0] < 3:
+        return 0.0
+
+    hull = cv2.convexHull(pts.reshape(-1, 1, 2))
+    hull_pts = hull.reshape(-1, 2)
+    if hull_pts.shape[0] < 3:
+        return 0.0
+
+    (_center, r_out) = cv2.minEnclosingCircle(hull)
+    r_out = float(r_out)
+    if r_out < 1e-6:
+        return 0.0
+
+    r_in = _inscribed_radius_mm(hull_pts)
+    if r_in <= 0:
+        return 0.0
+    return float(np.clip(r_in / r_out, 0.0, 1.0))
+
+
+def robust_section_ratio(cloud: np.ndarray, thr: float = 0.8) -> float:
+    """
+    Поперечные срезы. Из логов: у круга часто 1–2 среза ≥0.85, иногда медиана падает.
+    - ≥1 срез с score≥0.85 → принимаем (уверенный круг/дуга);
+    - иначе ≥2 среза ≥0.8 → max;
+    - иначе медиана (антишум для коробки).
+    """
+    ratios = _section_ratios_3d(cloud)
+    if not ratios:
+        return 0.0
+    very = [r for r in ratios if r >= 0.85]
+    if very:
+        return float(max(very))
+    strong = [r for r in ratios if r >= thr]
+    if len(strong) >= 2:
+        return float(max(strong))
+    return float(np.median(ratios))
+
+
+def _point_cloud(
+    depth_mm: np.ndarray,
+    mask: np.ndarray,
+    fx: float,
+    fy: float,
+    cx: float,
+    cy: float,
+) -> Optional[np.ndarray]:
+    ys, xs = np.where(mask > 0)
+    if xs.size < 150:
+        return None
+    z = depth_mm[ys, xs].astype(np.float32)
+    ok = (z > 50) & (z < 5000)
+    xs, ys, z = xs[ok], ys[ok], z[ok]
+    if xs.size < 150:
+        return None
+    # детерминированный даунсэмпл (без random)
+    if xs.size > 4000:
+        step = int(np.ceil(xs.size / 4000))
+        xs, ys, z = xs[::step], ys[::step], z[::step]
+    X = (xs.astype(np.float32) - cx) * z / fx
+    Y = (ys.astype(np.float32) - cy) * z / fy
+    return np.column_stack([X, Y, z]).astype(np.float32)
+
+
+def _section_ratios_3d(cloud: np.ndarray) -> List[float]:
+    mean = cloud.mean(axis=0)
+    centered = cloud - mean
+    try:
+        _u, s, vt = np.linalg.svd(centered, full_matrices=False)
+    except np.linalg.LinAlgError:
+        return []
+
+    out: List[float] = []
+    # только вдоль самой длинной оси — поперечные сечения цилиндра/коробки
+    for axis_i in range(min(1, vt.shape[0])):
+        if float(s[axis_i]) < 1e-6:
+            continue
+        axis = vt[axis_i]
+        axis = axis / (np.linalg.norm(axis) + 1e-9)
+        along = centered @ axis
+
+        ref = np.array([0.0, 0.0, 1.0], dtype=np.float32)
+        if abs(float(np.dot(axis, ref))) > 0.9:
+            ref = np.array([1.0, 0.0, 0.0], dtype=np.float32)
+        u = np.cross(axis, ref)
+        u /= np.linalg.norm(u) + 1e-9
+        v = np.cross(axis, u)
+
+        a0, a1 = float(np.percentile(along, 15)), float(np.percentile(along, 85))
+        if a1 - a0 < 10.0:
+            continue
+
+        for t in (0.2, 0.35, 0.5, 0.65, 0.8):
+            ca = a0 + t * (a1 - a0)
+            half = max(4.0, 0.06 * (a1 - a0))
+            band = np.abs(along - ca) <= half
+            if int(band.sum()) < 40:
+                continue
+            pts = centered[band]
+            sec = np.column_stack([pts @ u, pts @ v]).astype(np.float32)
+            out.append(_section_score(sec))
+    return out
+
+
+def _section_score(sec: np.ndarray) -> float:
+    """
+    Чистый rin/rout. Для дуги лежачего цилиндра (depth видит полкруга)
+    допускаем score 0.85 только при жёстком circle-fit:
+    малый residual, почти равные радиусы, покрытие ≥200°, bbox не «палка».
+    Прямоугольное сечение fit не проходит → остаётся rin/rout < 0.8.
+    """
+    direct = rin_rout(sec)
+    if direct >= 0.8:
+        return float(direct)
+
+    fit = _fit_circle_arc(sec)
+    if fit is None:
+        return float(direct)
+    return float(max(direct, 0.85))
+
+
+def _fit_circle_arc(pts: np.ndarray) -> Optional[Tuple[np.ndarray, float]]:
+    pts = np.asarray(pts, dtype=np.float64).reshape(-1, 2)
+    if pts.shape[0] < 35:
+        return None
+
+    c0 = pts.mean(axis=0)
+    x0 = pts - c0
+    try:
+        _u, s, _vt = np.linalg.svd(x0, full_matrices=False)
+    except np.linalg.LinAlgError:
+        return None
+    if s.shape[0] < 2 or float(s[0]) < 1e-6:
+        return None
+    # сечение не должно быть линией
+    if float(s[1] / (s[0] + 1e-9)) < 0.45:
+        return None
+
+    x, y = pts[:, 0], pts[:, 1]
+    A = np.column_stack([2 * x, 2 * y, np.ones_like(x)])
+    b = x * x + y * y
+    try:
+        sol, *_ = np.linalg.lstsq(A, b, rcond=None)
+    except np.linalg.LinAlgError:
+        return None
+    cx_, cy_, c = sol
+    r2 = c + cx_ * cx_ + cy_ * cy_
+    if r2 <= 1.0:
+        return None
+    r = float(np.sqrt(r2))
+    rad = np.sqrt((x - cx_) ** 2 + (y - cy_) ** 2)
+    rel = float(np.sqrt(np.mean((rad - r) ** 2)) / (r + 1e-9))
+    rad_cv = float(rad.std() / (rad.mean() + 1e-9))
+    if rel > 0.04 or rad_cv > 0.04:
+        return None
+
+    bw = float(x.max() - x.min())
+    bh = float(y.max() - y.min())
+    aspect = max(bw, bh) / max(min(bw, bh), 1e-6)
+    # у круга/полукруга bbox близок к квадрату; у прямоугольника 2:1 — нет
+    if aspect > 1.45:
+        return None
+    if r < 0.40 * max(bw, bh) or r > 0.70 * max(bw, bh):
+        return None
+
+    ang = np.arctan2(y - cy_, x - cx_)
+    ang = np.sort(ang)
+    gaps = np.diff(ang)
+    gaps = np.append(gaps, ang[0] + 2 * np.pi - ang[-1])
+    coverage = float(2 * np.pi - gaps.max())
+    if coverage < np.deg2rad(200.0):
+        return None
+
+    return np.array([cx_, cy_], dtype=np.float32), r
+
+
+def _inscribed_radius_mm(pts_xy_mm: np.ndarray, grid: int = 192) -> float:
+    x_min, y_min = pts_xy_mm.min(axis=0)
+    x_max, y_max = pts_xy_mm.max(axis=0)
+    span = max(float(x_max - x_min), float(y_max - y_min), 1.0)
+    pad = 8
+    inner = grid - 2 * pad
+    if inner < 16:
+        return 0.0
+    scale = inner / span
+
+    img = np.zeros((grid, grid), dtype=np.uint8)
+    pts_px = ((pts_xy_mm - np.array([x_min, y_min], dtype=np.float32)) * scale).astype(np.int32)
+    pts_px[:, 0] = np.clip(pts_px[:, 0] + pad, 0, grid - 1)
+    pts_px[:, 1] = np.clip(pts_px[:, 1] + pad, 0, grid - 1)
+    cv2.fillPoly(img, [pts_px], 255)
+    if img.max() == 0 or float((img > 0).mean()) > 0.98:
+        return 0.0
+    dist = cv2.distanceTransform(img, cv2.DIST_L2, 5)
+    return float(dist.max()) / scale
+
+
+def circularity_ratio(pts_xy_mm: np.ndarray) -> float:
+    return rin_rout(pts_xy_mm)
+
+
+# совместимость со старыми вызовами
+def max_section_circle_ratio(
+    depth_mm: np.ndarray,
+    mask: np.ndarray,
+    top_pts_mm: np.ndarray,
+    fx: float,
+    fy: float,
+    cx: float,
+    cy: float,
+) -> float:
+    top = rin_rout(top_pts_mm)
+    cloud = _point_cloud(depth_mm, mask, fx, fy, cx, cy)
+    sec = robust_section_ratio(cloud) if cloud is not None else 0.0
+    return float(max(top, sec))
+
+
+def section_rin_rout(sec: np.ndarray) -> float:
+    return rin_rout(sec)
--- a/vision_classifier/mqtt_bridge.py
+++ b/vision_classifier/mqtt_bridge.py
@@ -0,0 +1,172 @@
+"""MQTT: публикация категории + команды серво/мотору (существующий API Arduino)."""
+
+from __future__ import annotations
+
+import json
+import threading
+import time
+from typing import Any, Dict, Optional
+
+import paho.mqtt.client as mqtt
+
+from classify import Category, ClassificationResult
+
+
+class MqttBridge:
+    def __init__(self, cfg: Dict[str, Any]) -> None:
+        self.cfg = cfg
+        self.enabled = bool(cfg.get("enabled", True))
+        self.routing_cfg = cfg.get("_routing", {})
+        self.motor_cfg = cfg.get("_motor", {})
+        self._last_route_ts = 0.0
+        self._last_category: Optional[str] = None
+
+        self.client = mqtt.Client(
+            mqtt.CallbackAPIVersion.VERSION2,
+            client_id=cfg.get("client_id", "vision_classifier_opi"),
+        )
+        user = cfg.get("user")
+        password = cfg.get("password")
+        if user:
+            self.client.username_pw_set(user, password)
+
+        self._connected = False
+        if self.enabled:
+            try:
+                self.client.connect(cfg["broker"], int(cfg.get("port", 1883)), 30)
+                self.client.loop_start()
+                # короткая проверка
+                time.sleep(0.3)
+                self._connected = True
+                print(f"[mqtt] подключено к {cfg['broker']}:{cfg.get('port', 1883)}")
+            except Exception as exc:
+                print(f"[mqtt] не удалось подключиться: {exc}")
+                self._connected = False
+
+    @property
+    def connected(self) -> bool:
+        return self._connected
+
+    def start_conveyor(self) -> None:
+        """Включить шаговик ленты через уже существующие топики motor/control/*."""
+        m = self.motor_cfg
+        if not m.get("enabled", False):
+            return
+        if not self.enabled or not self._connected:
+            return
+        rpm = int(m.get("rpm", 200))
+        current = int(m.get("current_percent", 50))
+        microsteps = int(m.get("microsteps", 16))
+        self.client.publish("motor/control/driver", "on", qos=1)
+        self.client.publish("motor/control/tmc/enable", "on", qos=1)
+        self.client.publish("motor/control/tmc/current_percent", str(current), qos=1)
+        self.client.publish("motor/control/tmc/microsteps", str(microsteps), qos=1)
+        if m.get("stealthchop", True):
+            self.client.publish("motor/control/tmc/stealthchop", "on", qos=1)
+        self.client.publish("motor/control/rpm", str(rpm), qos=1)
+        print(f"[mqtt] конвейер: driver ON, rpm={rpm}")
+
+    def stop_conveyor(self) -> None:
+        m = self.motor_cfg
+        if not m.get("enabled", False):
+            return
+        if not self.enabled or not self._connected:
+            return
+        self.client.publish("motor/control/rpm", "0", qos=1)
+        if m.get("disable_on_stop", False):
+            self.client.publish("motor/control/driver", "off", qos=1)
+        print("[mqtt] конвейер: rpm=0")
+
+    def publish_result(self, result: ClassificationResult) -> None:
+        if not self.enabled or not self._connected:
+            return
+        l, w, h = result.dims_sorted_mm
+        self.client.publish(
+            self.cfg.get("topic_result", "vision/feedback/category"),
+            result.category.value,
+            qos=1,
+        )
+        self.client.publish(
+            self.cfg.get("topic_dims", "vision/feedback/dimensions"),
+            f"{l:.1f},{w:.1f},{h:.1f}",
+            qos=0,
+        )
+        self.client.publish(
+            self.cfg.get("topic_circle", "vision/feedback/circle_ratio"),
+            f"{result.circle_ratio:.4f}",
+            qos=0,
+        )
+        payload = {
+            "category": result.category.value,
+            "zone": result.category.zone,
+            "label_ru": result.category.ru_label,
+            "dims_mm": [round(l, 1), round(w, 1), round(h, 1)],
+            "circle_ratio": round(result.circle_ratio, 4),
+            "reason": result.reason,
+        }
+        self.client.publish(
+            self.cfg.get("topic_debug", "vision/feedback/debug"),
+            json.dumps(payload, ensure_ascii=False),
+            qos=0,
+        )
+
+    def route(self, category: Category) -> None:
+        """Отправка команды серво через servo/control/{ch}/angle|enable."""
+        routing = self.routing_cfg
+        if not routing.get("enabled", True):
+            return
+        if not self.enabled or not self._connected:
+            return
+
+        now = time.time() * 1000.0
+        cooldown = float(routing.get("cooldown_ms", 1500))
+        if category.value == self._last_category and (now - self._last_route_ts) < cooldown:
+            return
+
+        zones = routing.get("zones", {})
+        zone_key = category.zone
+        zone = zones.get(zone_key)
+        if not zone:
+            return
+
+        for zk, zcfg in zones.items():
+            ch = int(zcfg["servo"])
+            idle = int(zcfg.get("idle_angle", 0))
+            if zk == zone_key:
+                continue
+            self._set_servo(ch, idle, enable=True)
+
+        ch = int(zone["servo"])
+        divert = int(zone.get("divert_angle", 90))
+        idle = int(zone.get("idle_angle", 0))
+        hold_ms = int(zone.get("hold_ms", 800))
+
+        if category == Category.SUITABLE and divert == idle:
+            self._set_servo(ch, idle, enable=True)
+            print(f"[mqtt] зона B — пропуск (servo {ch} idle)")
+        else:
+            self._set_servo(ch, divert, enable=True)
+            print(f"[mqtt] зона {zone_key} — divert servo {ch} → {divert}°")
+
+            def _return_idle(channel: int = ch, angle: int = idle, delay_s: float = hold_ms / 1000.0) -> None:
+                time.sleep(delay_s)
+                self._set_servo(channel, angle, enable=True)
+
+            threading.Thread(target=_return_idle, daemon=True).start()
+
+        self._last_category = category.value
+        self._last_route_ts = now
+
+    def _set_servo(self, channel: int, angle: int, enable: bool = True) -> None:
+        base = f"servo/control/{channel}"
+        self.client.publish(f"{base}/enable", "on" if enable else "off", qos=1)
+        self.client.publish(f"{base}/angle", str(int(angle)), qos=1)
+
+    def close(self) -> None:
+        try:
+            self.stop_conveyor()
+        except Exception:
+            pass
+        if self._connected:
+            self.client.loop_stop()
+            self.client.disconnect()
--- a/vision_classifier/requirements.txt
+++ b/vision_classifier/requirements.txt
@@ -0,0 +1,6 @@
+opencv-python-headless>=4.8
+numpy>=1.24
+paho-mqtt>=2.0
+PyYAML>=6.0
+pillow>=10.0  # кириллица на HUD (demo_hud.py)
+# ffmpeg должен быть в системе (pacman/apt: ffmpeg) — depth Z16 читается через него
--- a/vision_classifier/run.sh
+++ b/vision_classifier/run.sh
@@ -0,0 +1,12 @@
+#!/usr/bin/env bash
+set -euo pipefail
+DIR="$(cd "$(dirname "$0")" && pwd)"
+cd "$DIR"
+
+if [[ ! -d .venv ]]; then
+  python3 -m venv .venv
+  .venv/bin/pip install -U pip
+  .venv/bin/pip install -r requirements.txt
+fi
+
+exec .venv/bin/python main.py "$@"
--- a/vision_classifier/stabilize.py
+++ b/vision_classifier/stabilize.py
@@ -0,0 +1,306 @@
+"""
+Стабильный консенсус по кадрам.
+
+Из логов RealSense: круг даёт sec≈0.82–0.87, но early LOCK на B
+залипал навсегда. Поэтому:
+  • классификация по медиане окна;
+  • LOCK после прогрева;
+  • апгрейд B→D при устойчивом круге (≥ confirm кадров подряд);
+  • D→B и смена зоны после LOCK запрещены (пока объект не исчез).
+"""
+
+from __future__ import annotations
+
+from collections import Counter, deque
+from dataclasses import dataclass
+from typing import Deque, Optional, Sequence
+
+from classify import Category, ClassificationResult, check_size
+from measure import ObjectMeasurement
+
+
+@dataclass
+class StableDecision:
+    result: Optional[ClassificationResult]
+    locked: bool
+    confidence_pct: int
+    ratio_smooth: float
+    present: bool
+    uncertain: bool = False  # LOCK по правилу «нет консенсуса → безопасная зона»
+
+
+class DecisionStabilizer:
+    def __init__(
+        self,
+        window: int = 12,
+        confirm_frames: int = 8,
+        lost_frames: int = 12,
+        enter_circle: float = 0.80,
+        exit_circle: float = 0.72,
+        uncertain_after: int = 45,
+        fallback: Category = Category.OVERSIZE,
+    ) -> None:
+        self.window = max(5, int(window))
+        self.confirm_frames = max(3, int(confirm_frames))
+        self.lost_frames = max(3, int(lost_frames))
+        self.enter_circle = float(enter_circle)
+        self.exit_circle = float(exit_circle)
+        # нет консенсуса за uncertain_after кадров → безопасная зона (ТЗ:
+        # неоднозначные товары не должны идти в основной поток)
+        self.uncertain_after = max(self.window + 5, int(uncertain_after))
+        self.fallback = fallback
+
+        self._ratios: Deque[float] = deque(maxlen=self.window)
+        self._tops: Deque[float] = deque(maxlen=self.window)
+        self._secs: Deque[float] = deque(maxlen=self.window)
+        self._Ls: Deque[float] = deque(maxlen=self.window)
+        self._Ws: Deque[float] = deque(maxlen=self.window)
+        self._Hs: Deque[float] = deque(maxlen=self.window)
+        self._zones: Deque[str] = deque(maxlen=self.window)
+
+        self._pending_zone: Optional[str] = None
+        self._pending_count: int = 0
+        self._upgrade_count: int = 0
+        self._locked: Optional[ClassificationResult] = None
+        self._miss: int = 0
+        self._frames_seen: int = 0
+        self._uncertain_locked: bool = False
+
+    def reset(self) -> None:
+        self._ratios.clear()
+        self._tops.clear()
+        self._secs.clear()
+        self._Ls.clear()
+        self._Ws.clear()
+        self._Hs.clear()
+        self._zones.clear()
+        self._pending_zone = None
+        self._pending_count = 0
+        self._upgrade_count = 0
+        self._locked = None
+        self._miss = 0
+        self._frames_seen = 0
+        self._uncertain_locked = False
+
+    def update(
+        self,
+        measurement: Optional[ObjectMeasurement],
+        min_mm: Sequence[float] = (10, 10, 10),
+        max_mm: Sequence[float] = (450, 320, 320),
+    ) -> StableDecision:
+        if measurement is None:
+            self._miss += 1
+            if self._miss >= self.lost_frames:
+                self.reset()
+                return StableDecision(None, False, 0, 0.0, False)
+            if self._locked is not None:
+                return StableDecision(
+                    self._locked, True, 100, self._locked.circle_ratio, True,
+                    uncertain=self._uncertain_locked,
+                )
+            return StableDecision(None, False, 0, 0.0, False)
+
+        self._miss = 0
+        self._frames_seen += 1
+        self._ratios.append(float(measurement.circle_ratio))
+        self._tops.append(float(getattr(measurement, "top_ratio", measurement.circle_ratio)))
+        self._secs.append(float(getattr(measurement, "section_ratio", 0.0)))
+        self._Ls.append(float(measurement.length_mm))
+        self._Ws.append(float(measurement.width_mm))
+        self._Hs.append(float(measurement.height_mm))
+
+        ratio = _median(self._ratios)
+        top_m = _median(self._tops)
+        sec_m = _median(self._secs)
+        ratio_p75 = _percentile(self._ratios, 75)
+        # устойчивый круг: медиана >= 0.8 ИЛИ (медиана сечений >= 0.8 и ≥ половины окна сильные)
+        sec_strong = (
+            sum(1 for x in self._secs if x >= self.enter_circle) / max(1, len(self._secs))
+        )
+        circular = ratio >= self.enter_circle or (
+            sec_m >= self.enter_circle and sec_strong >= 0.55
+        )
+        ratio_show = max(ratio, sec_m) if circular else ratio
+
+        L, W, H = _median(self._Ls), _median(self._Ws), _median(self._Hs)
+        dims = tuple(sorted([L, W, H], reverse=True))
+        passes = check_size(dims, min_mm, max_mm)
+        clipped = bool(getattr(measurement, "clipped_by_frame", False))
+        if clipped:
+            # неполный габарит из-за края кадра → безопасный негабарит
+            passes = False
+
+        if not passes:
+            instant = ClassificationResult(
+                category=Category.OVERSIZE,
+                dims_sorted_mm=(dims[0], dims[1], dims[2]),
+                circle_ratio=ratio_show,
+                passes_size=False,
+                is_circular=circular,
+                reason=(
+                    "объект обрезан краем кадра → габарит неполный, считаем негабаритом"
+                    if clipped
+                    else "габариты вне допуска: нужно >10×10×10 и <450×320×320 мм"
+                ),
+            )
+        elif circular:
+            instant = ClassificationResult(
+                category=Category.NEED_PACK,
+                dims_sorted_mm=(dims[0], dims[1], dims[2]),
+                circle_ratio=ratio_show,
+                passes_size=True,
+                is_circular=True,
+                reason=(
+                    f"круг: med={ratio:.3f} p75={ratio_p75:.3f} "
+                    f"top={top_m:.3f} sec={sec_m:.3f} strong={sec_strong:.0%} "
+                    f">= {self.enter_circle}"
+                ),
+            )
+        else:
+            instant = ClassificationResult(
+                category=Category.SUITABLE,
+                dims_sorted_mm=(dims[0], dims[1], dims[2]),
+                circle_ratio=ratio_show,
+                passes_size=True,
+                is_circular=False,
+                reason=(
+                    f"не круг: med={ratio:.3f} sec={sec_m:.3f} "
+                    f"strong={sec_strong:.0%} < {self.enter_circle}"
+                ),
+            )
+
+        zone = instant.category.zone
+        self._zones.append(zone)
+
+        # --- уже есть LOCK ---
+        if self._locked is not None:
+            prev = self._locked.category
+            cur = instant.category
+            locked_dims = self._locked.dims_sorted_mm
+
+            # новый объект (габариты сильно сменились) — сброс LOCK и набор заново
+            if _dims_changed(locked_dims, dims, rel=0.28):
+                self._locked = None
+                self._uncertain_locked = False
+                self._pending_zone = zone
+                self._pending_count = 1
+                self._upgrade_count = 0
+                self._frames_seen = 1
+                conf = int(min(99, round(100.0 * 1 / max(1, self.confirm_frames))))
+                return StableDecision(instant, False, conf, ratio_show, True)
+
+            can_upgrade = (
+                (prev == Category.OVERSIZE and cur in (Category.SUITABLE, Category.NEED_PACK))
+                or (prev == Category.SUITABLE and cur == Category.NEED_PACK)
+            )
+            if can_upgrade:
+                self._upgrade_count += 1
+                need_up = max(5, self.confirm_frames // 2)
+                if self._upgrade_count >= need_up:
+                    self._locked = instant
+                    self._upgrade_count = 0
+                    self._uncertain_locked = False  # появился консенсус
+            else:
+                self._upgrade_count = 0
+            return StableDecision(
+                self._locked, True, 100, ratio_show, True,
+                uncertain=self._uncertain_locked,
+            )
+
+        # нет консенсуса слишком долго → «неуверенно», безопасная зона
+        if self._frames_seen >= self.uncertain_after:
+            fallback_result = ClassificationResult(
+                category=self.fallback,
+                dims_sorted_mm=(dims[0], dims[1], dims[2]),
+                circle_ratio=ratio_show,
+                passes_size=passes,
+                is_circular=circular,
+                reason="НЕУВЕРЕННО → безопасная зона: " + self._uncertain_reason(
+                    ratio, dims, min_mm, max_mm
+                ),
+            )
+            self._locked = fallback_result
+            self._uncertain_locked = True
+            return StableDecision(fallback_result, True, 100, ratio_show, True, uncertain=True)
+
+        # прогрев окна
+        if len(self._ratios) < self.window:
+            conf = int(min(99, round(100.0 * len(self._ratios) / self.window)))
+            return StableDecision(instant, False, conf, ratio_show, True)
+
+        votes = Counter(self._zones)
+        winner, win_n = votes.most_common(1)[0]
+        if winner != zone:
+            self._pending_zone = None
+            self._pending_count = 0
+            conf = int(round(100.0 * win_n / len(self._zones)))
+            return StableDecision(instant, False, conf, ratio_show, True)
+
+        need = max(self.confirm_frames, (self.window * 2 + 2) // 3)
+        if zone == self._pending_zone:
+            self._pending_count += 1
+        else:
+            self._pending_zone = zone
+            self._pending_count = 1
+
+        conf = int(min(100, round(100.0 * max(self._pending_count, win_n) / need)))
+        if self._pending_count >= need and win_n >= need:
+            self._locked = instant
+            self._uncertain_locked = False
+            return StableDecision(instant, True, 100, ratio_show, True)
+
+        return StableDecision(instant, False, conf, ratio_show, True)
+
+    def _uncertain_reason(
+        self,
+        ratio: float,
+        dims: Sequence[float],
+        min_mm: Sequence[float],
+        max_mm: Sequence[float],
+    ) -> str:
+        votes = Counter(self._zones)
+        parts = [
+            f"нет консенсуса {self._frames_seen} кадров",
+            "голоса " + " ".join(f"{z}:{n}" for z, n in votes.most_common()),
+        ]
+        if abs(ratio - self.enter_circle) <= 0.06:
+            parts.append(f"ratio {ratio:.3f} у порога {self.enter_circle}")
+        max_s = sorted([float(x) for x in max_mm], reverse=True)
+        min_s = sorted([float(x) for x in min_mm], reverse=True)
+        for d, mx, mn in zip(dims, max_s, min_s):
+            if abs(d - mx) <= 0.05 * mx:
+                parts.append(f"сторона {d:.0f} мм у лимита {mx:.0f}")
+            elif mn > 0 and abs(d - mn) <= max(3.0, 0.3 * mn):
+                parts.append(f"сторона {d:.0f} мм у минимума {mn:.0f}")
+        return "; ".join(parts)
+
+
+def _median(vals: Deque[float]) -> float:
+    return _percentile(vals, 50)
+
+
+def _dims_changed(
+    a: Sequence[float], b: Sequence[float], rel: float = 0.28
+) -> bool:
+    """True если хотя бы одна сторона изменилась больше чем на rel (новый объект)."""
+    if len(a) < 3 or len(b) < 3:
+        return False
+    for x, y in zip(a[:3], b[:3]):
+        base = max(abs(float(x)), abs(float(y)), 1.0)
+        if abs(float(x) - float(y)) / base > rel:
+            return True
+    return False
+
+
+def _percentile(vals: Deque[float], q: float) -> float:
+    arr = sorted(vals)
+    n = len(arr)
+    if n == 0:
+        return 0.0
+    if n == 1:
+        return float(arr[0])
+    pos = (q / 100.0) * (n - 1)
+    lo = int(pos)
+    hi = min(lo + 1, n - 1)
+    frac = pos - lo
+    return float(arr[lo] * (1 - frac) + arr[hi] * frac)
--- a/vision_classifier/test_classify.py
+++ b/vision_classifier/test_classify.py
@@ -0,0 +1,86 @@
+#!/usr/bin/env python3
+"""Юнит-тесты правил классификации (без камеры)."""
+
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+
+from classify import Category, classify_from_dims
+
+
+def test_suitable_box():
+    r = classify_from_dims(120, 80, 40, circle_ratio=0.5)
+    assert r.category == Category.SUITABLE
+    assert r.category.zone == "B"
+
+
+def test_oversize_priority_over_circle():
+    # Большой цилиндр: габариты важнее круга
+    r = classify_from_dims(500, 100, 100, circle_ratio=0.95)
+    assert r.category == Category.OVERSIZE
+    assert r.category.zone == "C"
+
+
+def test_too_small():
+    r = classify_from_dims(5, 5, 5, circle_ratio=0.2)
+    assert r.category == Category.OVERSIZE
+
+
+def test_need_pack_cylinder():
+    r = classify_from_dims(100, 50, 50, circle_ratio=0.85)
+    assert r.category == Category.NEED_PACK
+    assert r.category.zone == "D"
+
+
+def test_lying_bottle_must_be_D_not_B():
+    """ТЗ: круг в ЛЮБОМ сечении. Лежачая бутылка сверху не круг, но сечение круглое."""
+    # имитация: top-view низкий, но итоговый circle_ratio после 3D-срезов высокий
+    r = classify_from_dims(220, 70, 70, circle_ratio=0.86)
+    assert r.category == Category.NEED_PACK
+    assert r.category.zone == "D"
+
+
+def test_border_circle():
+    r = classify_from_dims(100, 50, 50, circle_ratio=0.8)
+    assert r.category == Category.NEED_PACK
+    r2 = classify_from_dims(100, 50, 50, circle_ratio=0.799)
+    assert r2.category == Category.SUITABLE
+
+
+def test_border_dims_strict():
+    """ТЗ: строго больше 10×10×10 и строго меньше 450×320×320."""
+    # ровно на максимуме → C
+    assert classify_from_dims(450, 320, 320, 0.3).category == Category.OVERSIZE
+    # ровно на минимуме → C
+    assert classify_from_dims(10, 10, 10, 0.3).category == Category.OVERSIZE
+    # чуть внутри границ → B
+    assert classify_from_dims(449, 319, 319, 0.3).category == Category.SUITABLE
+    assert classify_from_dims(11, 11, 11, 0.3).category == Category.SUITABLE
+    # 321 мм влезает вдоль оси 450 → B (сопоставление после сортировки)
+    assert classify_from_dims(100, 321, 100, 0.3).category == Category.SUITABLE
+    # а вот две стороны > 320 уже не влезают → C
+    assert classify_from_dims(400, 330, 100, 0.3).category == Category.OVERSIZE
+
+
+def test_dims_order_independent():
+    """Стороны сопоставляются после сортировки — порядок L/W/H не важен."""
+    assert classify_from_dims(319, 449, 318, 0.3).category == Category.SUITABLE
+    assert classify_from_dims(318, 319, 449, 0.3).category == Category.SUITABLE
+    # ровно 320 по строгому правилу «меньше» → C, в любом порядке
+    assert classify_from_dims(320, 449, 319, 0.3).category == Category.OVERSIZE
+    assert classify_from_dims(319, 320, 449, 0.3).category == Category.OVERSIZE
+
+
+if __name__ == "__main__":
+    test_suitable_box()
+    test_oversize_priority_over_circle()
+    test_too_small()
+    test_need_pack_cylinder()
+    test_lying_bottle_must_be_D_not_B()
+    test_border_circle()
+    test_border_dims_strict()
+    test_dims_order_independent()
+    print("OK: all classification tests passed")
--- a/vision_classifier/test_geometry.py
+++ b/vision_classifier/test_geometry.py
@@ -0,0 +1,384 @@
+#!/usr/bin/env python3
+"""Геометрические тесты: прямоугольник → B, круг → D (без камеры)."""
+
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+import numpy as np
+import cv2
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+
+from measure import (
+    ObjectMeasurement,
+    _fit_circle_arc,
+    _section_score,
+    measure_object,
+    rin_rout,
+    section_rin_rout,
+    segment_object,
+)
+from stabilize import DecisionStabilizer
+
+
+def _circle(n=64, r=40.0):
+    a = np.linspace(0, 2 * np.pi, n, endpoint=False)
+    return np.column_stack([50 + r * np.cos(a), 50 + r * np.sin(a)]).astype(np.float32)
+
+
+def _rect(w=150.0, h=90.0, n=20):
+    pts = (
+        [[x, 0] for x in np.linspace(0, w, n)]
+        + [[w, y] for y in np.linspace(0, h, n)]
+        + [[x, h] for x in np.linspace(w, 0, n)]
+        + [[0, y] for y in np.linspace(h, 0, n)]
+    )
+    return np.array(pts, dtype=np.float32)
+
+
+def _round_rect(w=150.0, h=90.0, rad=8.0, n=12, ne=15):
+    pts = []
+    pts += [[x, 0] for x in np.linspace(rad, w - rad, ne)]
+    pts += [[w, y] for y in np.linspace(rad, h - rad, ne)]
+    pts += [[x, h] for x in np.linspace(w - rad, rad, ne)]
+    pts += [[0, y] for y in np.linspace(h - rad, rad, ne)]
+    corners = [
+        (rad, rad, np.pi, 1.5 * np.pi),
+        (w - rad, rad, 1.5 * np.pi, 2 * np.pi),
+        (w - rad, h - rad, 0, 0.5 * np.pi),
+        (rad, h - rad, 0.5 * np.pi, np.pi),
+    ]
+    for cx, cy, a0, a1 in corners:
+        for a in np.linspace(a0, a1, n):
+            pts.append([cx + rad * np.cos(a), cy + rad * np.sin(a)])
+    return np.array(pts, dtype=np.float32)
+
+
+def _arc(span_deg=252.0, r=35.0, n=80):
+    a0 = -np.deg2rad(span_deg) / 2
+    a1 = np.deg2rad(span_deg) / 2
+    a = np.linspace(a0, a1, n)
+    return np.column_stack([50 + r * np.cos(a), 50 + r * np.sin(a)]).astype(np.float32)
+
+
+def test_geometry_ratios():
+    assert rin_rout(_circle()) >= 0.8, "круг сверху должен быть D"
+    assert rin_rout(_rect()) < 0.8, "прямоугольник должен быть B"
+    assert rin_rout(_round_rect()) < 0.8, "скруглённый прямоугольник — B"
+    # квадрат < 0.8 (теоретически ~0.707)
+    sq = np.array([[0, 0], [100, 0], [100, 100], [0, 100]], dtype=np.float32)
+    assert rin_rout(sq) < 0.8
+
+    # дуга цилиндра: fit → 0.85
+    arc = _arc()
+    score = _section_score(arc)
+    assert score >= 0.8, f"дуга цилиндра должна давать >=0.8, got {score}"
+    assert _fit_circle_arc(_rect()) is None, "прямоугольник не должен проходить circle-fit"
+
+
+def test_stabilizer_box_vs_cylinder():
+    dummy = np.zeros((10, 1, 2), np.int32)
+    mask = np.zeros((10, 10), np.uint8)
+
+    # коробка с редкими ложными пиками → LOCK B
+    s = DecisionStabilizer(window=8, confirm_frames=5, enter_circle=0.8)
+    locked_zone = None
+    seq = [0.55, 0.84, 0.56, 0.58, 0.57, 0.59, 0.55, 0.56, 0.58, 0.57, 0.55, 0.56, 0.57, 0.58]
+    for r in seq:
+        m = ObjectMeasurement(120, 80, 40, r, 1000, (1, 1), dummy, mask, top_ratio=r, section_ratio=0.5)
+        d = s.update(m)
+        if d.locked and d.result:
+            locked_zone = d.result.category.zone
+    assert locked_zone == "B", f"коробка должна LOCK B, got {locked_zone}"
+
+    # цилиндр → LOCK D
+    s2 = DecisionStabilizer(window=8, confirm_frames=5, enter_circle=0.8)
+    locked_zone = None
+    for r in [0.90] * 16:
+        m = ObjectMeasurement(100, 50, 50, r, 1000, (1, 1), dummy, mask, top_ratio=r, section_ratio=0.88)
+        d = s2.update(m)
+        if d.locked and d.result:
+            locked_zone = d.result.category.zone
+    assert locked_zone == "D", f"цилиндр должен LOCK D, got {locked_zone}"
+
+    # после LOCK D не прыгаем в B
+    for r in [0.4] * 10:
+        m = ObjectMeasurement(100, 50, 50, r, 1000, (1, 1), dummy, mask, top_ratio=r, section_ratio=0.4)
+        d = s2.update(m)
+        assert d.locked and d.result and d.result.category.zone == "D"
+
+    # early B, then устойчивый круг → апгрейд в D (те же габариты)
+    s3 = DecisionStabilizer(window=8, confirm_frames=6, enter_circle=0.8)
+    for r in [0.55] * 20:
+        m = ObjectMeasurement(100, 50, 50, r, 1000, (1, 1), dummy, mask, top_ratio=r, section_ratio=0.5)
+        d = s3.update(m)
+    assert d.locked and d.result.category.zone == "B"
+    for r in [0.86] * 16:
+        m = ObjectMeasurement(100, 50, 50, r, 1000, (1, 1), dummy, mask, top_ratio=0.72, section_ratio=0.86)
+        d = s3.update(m)
+    assert d.locked and d.result.category.zone == "D", f"ожидали апгрейд B→D, got {d.result.category.zone}"
+
+    # смена объекта круг→коробка по габаритам → новый LOCK B
+    saw_reset = False
+    locked_b = False
+    for r in [0.45] * 25:
+        m = ObjectMeasurement(240, 120, 50, r, 1000, (1, 1), dummy, mask, top_ratio=0.45, section_ratio=0.27)
+        d = s3.update(m)
+        if d.present and not d.locked:
+            saw_reset = True
+        if d.locked and d.result and d.result.category.zone == "B":
+            locked_b = True
+    assert saw_reset, "при смене габаритов должен быть сброс LOCK"
+    assert locked_b, "коробка после смены должна LOCK B"
+
+
+def test_background_map_splits_object_from_platform():
+    """Цилиндр на платформе: скалярная высота сливает их, фоновая карта — нет."""
+    H, W = 480, 640
+    belt = 600
+    bg = np.full((H, W), belt, np.uint16)
+    bg[100:340, 130:470] = belt - 80  # платформа 80 мм — часть фона
+
+    depth = bg.copy()
+    yy, xx = np.ogrid[:H, :W]
+    circ = (yy - 220) ** 2 + (xx - 300) ** 2 <= 70**2
+    depth[circ] = belt - 80 - 60  # круглый предмет 60 мм на платформе
+
+    # старый способ: платформа+цилиндр в одном контуре (большая площадь)
+    seg_old = segment_object(depth, belt_distance_mm=belt, min_area_px=400)
+    assert seg_old is not None
+    area_old = int((seg_old[0] > 0).sum())
+    assert area_old > 240 * 340 * 0.8, "скалярный способ должен захватить платформу"
+
+    # с фоновой картой: только цилиндр
+    seg_bg = segment_object(depth, belt_distance_mm=belt, min_area_px=400, background_mm=bg)
+    assert seg_bg is not None
+    mask, contour = seg_bg
+    area = int((mask > 0).sum())
+    circle_area = np.pi * 70 * 70
+    assert abs(area - circle_area) / circle_area < 0.15, f"площадь {area} vs круг {circle_area:.0f}"
+
+    m = measure_object(
+        depth, mask, contour,
+        belt_distance_mm=belt, fx=670, fy=670, cx=320, cy=240,
+        background_mm=bg,
+    )
+    assert m is not None
+    assert abs(m.height_mm - 60) < 8, f"высота от платформы должна быть ~60, got {m.height_mm:.1f}"
+    assert m.top_ratio >= 0.8, f"вид сверху круг, got {m.top_ratio:.3f}"
+
+
+def test_uncertain_fallback_to_safe_zone():
+    """Нет консенсуса (ratio скачет у порога) → «неуверенно» → безопасная зона C."""
+    from classify import Category
+
+    dummy = np.zeros((10, 1, 2), np.int32)
+    mask = np.zeros((10, 10), np.uint8)
+
+    s = DecisionStabilizer(window=8, confirm_frames=6, uncertain_after=25, fallback=Category.OVERSIZE)
+    seq = ([0.70] * 6 + [0.90] * 6) * 5  # блоками вокруг порога 0.8
+    final = None
+    for i, r in enumerate(seq):
+        m = ObjectMeasurement(100, 50, 50, r, 1000, (1, 1), dummy, mask, top_ratio=r, section_ratio=r)
+        d = s.update(m)
+        if d.locked:
+            final = (i + 1, d)
+            break
+    assert final is not None, "fallback должен сработать"
+    n_frames, d = final
+    assert d.uncertain, "LOCK должен быть помечен как неуверенный"
+    assert d.result is not None and d.result.category.zone == "C"
+    assert "НЕУВЕРЕННО" in d.result.reason
+    assert n_frames <= 30, f"fallback должен сработать около 25 кадров, got {n_frames}"
+
+    # уверенная коробка не должна помечаться «неуверенно»
+    s2 = DecisionStabilizer(window=8, confirm_frames=6, uncertain_after=25)
+    got = None
+    for r in [0.5] * 20:
+        m = ObjectMeasurement(120, 80, 40, r, 1000, (1, 1), dummy, mask, top_ratio=r, section_ratio=r)
+        d2 = s2.update(m)
+        if d2.locked:
+            got = d2
+            break
+    assert got is not None and not got.uncertain
+    assert got.result is not None and got.result.category.zone == "B"
+
+
+def test_tracker_two_objects_ids_and_stats():
+    """Коробка + цилиндр одновременно: два ID, статистика считает каждого один раз."""
+    from tracker import MultiObjectTracker
+
+    dummy = np.zeros((10, 1, 2), np.int32)
+    mask = np.zeros((10, 10), np.uint8)
+
+    def factory():
+        return DecisionStabilizer(window=8, confirm_frames=5, enter_circle=0.8)
+
+    t = MultiObjectTracker(factory, max_dist_px=120, lost_frames=8)
+    all_events = []
+    for _ in range(20):
+        box = ObjectMeasurement(120, 80, 40, 0.55, 1000, (100, 100), dummy, mask,
+                                top_ratio=0.55, section_ratio=0.5)
+        cyl = ObjectMeasurement(100, 50, 50, 0.90, 900, (500, 300), dummy, mask,
+                                top_ratio=0.90, section_ratio=0.88)
+        tracks, events = t.update([box, cyl])
+        all_events.extend(events)
+
+    assert len(tracks) == 2, f"должно быть 2 трека, got {len(tracks)}"
+    ids = sorted(tr.track_id for tr in tracks)
+    assert ids == [1, 2], f"ID должны быть 1 и 2, got {ids}"
+    zones = sorted(ev.decision.result.category.zone for ev in all_events)
+    assert zones == ["B", "D"], f"события LOCK для B и D, got {zones}"
+    assert t.stats["B"] == 1 and t.stats["D"] == 1 and t.stats["total"] == 2
+
+    # объекты убрали → треки умирают (залоченные живут дольше), статистика остаётся
+    for _ in range(40):
+        tracks, _ = t.update([])
+    assert not tracks
+    assert t.stats["total"] == 2
+
+    # тот же товар на том же месте вернулся → без нового LOCK и без роста счётчика
+    events_back = []
+    for _ in range(15):
+        box = ObjectMeasurement(120, 80, 40, 0.55, 1000, (100, 100), dummy, mask,
+                                top_ratio=0.55, section_ratio=0.5)
+        tracks, events = t.update([box])
+        events_back.extend(events)
+    assert not events_back, "повторный захват уже учтённого товара не должен давать LOCK"
+    assert tracks and tracks[0].track_id == 1
+    assert tracks[0].frozen is not None and tracks[0].decision.locked
+    assert t.stats["B"] == 1 and t.stats["total"] == 2
+
+    # новый объект в другом месте получает следующий ID
+    box2 = ObjectMeasurement(200, 100, 60, 0.5, 1200, (300, 200), dummy, mask,
+                             top_ratio=0.5, section_ratio=0.4)
+    for _ in range(20):
+        tracks, events = t.update([box2])
+    assert tracks and any(tr.track_id == 3 for tr in tracks)
+    assert t.stats["B"] == 2 and t.stats["total"] == 3
+
+
+def test_tracker_slot_dedup_same_object():
+    """Тот же товар на том же месте с новым track_id — без повторного LOCK."""
+    from tracker import MultiObjectTracker, slot_key
+
+    dummy = np.zeros((10, 1, 2), np.int32)
+    mask = np.zeros((10, 10), np.uint8)
+
+    def factory():
+        return DecisionStabilizer(window=8, confirm_frames=5, enter_circle=0.8)
+
+    t = MultiObjectTracker(factory, max_dist_px=120, lost_frames=8)
+    box = ObjectMeasurement(120, 80, 40, 0.55, 1000, (100, 100), dummy, mask,
+                            top_ratio=0.55, section_ratio=0.5)
+    all_events = []
+    for _ in range(20):
+        tracks, events = t.update([box])
+        all_events.extend(events)
+    assert all_events, "первый LOCK должен быть"
+    sk = slot_key(100, 100, 120, 80, 40, "B")
+    assert sk in t._seen_slots
+
+    # новый track_id, та же позиция — события нет, счётчик не растёт
+    for _ in range(40):
+        tracks, _ = t.update([])
+    box2 = ObjectMeasurement(118, 82, 41, 0.56, 1000, (102, 98), dummy, mask,
+                             top_ratio=0.56, section_ratio=0.5)
+    extra = []
+    for _ in range(20):
+        tracks, events = t.update([box2])
+        extra.extend(events)
+    assert not extra, "повтор того же слота не должен давать LOCK"
+    assert t.stats["total"] == 1
+
+
+def test_shadow_not_detected_as_object():
+    """Тень на ленте (затемнение без смены цвета) не должна давать RGB-объект."""
+    from measure import segment_rgb_objects
+
+    H, W = 480, 640
+    bg = np.full((H, W, 3), (90, 130, 160), np.uint8)  # коричневая лента BGR
+    color = bg.copy()
+    # мягкая тень: все каналы ×0.55 — типичная тень от коробки
+    color[150:300, 200:420] = (bg[150:300, 200:420].astype(np.float32) * 0.55).astype(np.uint8)
+    objs = segment_rgb_objects(color, bg, min_area_px=400, diff_threshold=35)
+    assert not objs, f"тень не должна детектироваться, got {len(objs)}"
+
+
+def test_merge_overlapping_halves():
+    """Две половины одного объекта с пересечением ≥50% → один контур."""
+    from measure import merge_overlapping_masks, mask_overlap_min
+
+    H, W = 100, 100
+    a = np.zeros((H, W), np.uint8)
+    b = np.zeros((H, W), np.uint8)
+    a[20:60, 20:60] = 255  # 40×40
+    b[20:60, 35:75] = 255  # перекрытие 40×25 = 1000 / 1600 = 0.625
+    assert mask_overlap_min(a, b) >= 0.5
+    ca, _ = cv2.findContours(a, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    cb, _ = cv2.findContours(b, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    merged = merge_overlapping_masks([(a, ca[0]), (b, cb[0])], overlap_thr=0.5)
+    assert len(merged) == 1, f"ожидали 1 объект, got {len(merged)}"
+
+
+def test_noise_measurement_rejected():
+    """Шум 0×0×0 / мелкие RGB-пятна не должны классифицироваться как негабарит."""
+    from measure import ObjectMeasurement, is_plausible_measurement
+
+    dummy = np.zeros((10, 1, 2), np.int32)
+    mask = np.zeros((10, 10), np.uint8)
+    noise = ObjectMeasurement(0.0, 0.0, 0.0, 0.1, 80, (10, 10), dummy, mask, source="rgb")
+    assert not is_plausible_measurement(noise)
+    speckle = ObjectMeasurement(12.0, 8.0, 0.0, 0.2, 500, (50, 50), dummy, mask, source="rgb")
+    assert not is_plausible_measurement(speckle)
+    ok = ObjectMeasurement(110.0, 70.0, 28.0, 0.6, 1200, (100, 100), dummy, mask)
+    assert is_plausible_measurement(ok)
+
+
+def test_flat_phone_via_rgb():
+    """Телефон 8 мм: depth не видит (порог 12 мм), RGB-фон находит → класс C."""
+    from classify import Category, classify
+    from measure import measure_flat_object, segment_rgb_objects
+
+    H, W = 480, 640
+    belt = 534
+    bg_color = np.full((H, W, 3), 120, np.uint8)  # серая лента
+    color = bg_color.copy()
+    x0, y0, pw, ph = 250, 180, 172, 80  # ≈160×75 мм при fx=564, z=534
+    color[y0 : y0 + ph, x0 : x0 + pw] = (30, 30, 30)  # тёмный телефон
+
+    depth = np.full((H, W), belt, np.uint16)
+    depth[y0 : y0 + ph, x0 : x0 + pw] = belt - 8  # всего 8 мм над лентой
+    rng = np.random.default_rng(0)
+    depth = (depth.astype(np.int32) + rng.integers(-3, 4, size=depth.shape)).astype(np.uint16)
+
+    objs = segment_rgb_objects(color, bg_color, min_area_px=400)
+    assert objs, "телефон должен найтись по RGB-фону"
+    mask, contour = objs[0]
+    m = measure_flat_object(
+        depth, mask, contour,
+        belt_distance_mm=belt, fx=564.0, fy=564.0, cx=320, cy=240,
+        background_mm=np.full((H, W), belt, np.uint16),
+    )
+    assert m is not None and m.source == "rgb"
+    assert abs(m.length_mm - 160) < 15, f"длина ~160, got {m.length_mm:.0f}"
+    assert abs(m.width_mm - 75) < 12, f"ширина ~75, got {m.width_mm:.0f}"
+    assert m.height_mm < 12, f"высота должна быть маленькой, got {m.height_mm:.0f}"
+    r = classify(m)
+    assert r.category == Category.OVERSIZE, "тоньше 10 мм → C по ТЗ (меньше минимума)"
+
+
+if __name__ == "__main__":
+    test_geometry_ratios()
+    test_stabilizer_box_vs_cylinder()
+    test_background_map_splits_object_from_platform()
+    test_uncertain_fallback_to_safe_zone()
+    test_tracker_two_objects_ids_and_stats()
+    test_tracker_slot_dedup_same_object()
+    test_noise_measurement_rejected()
+    test_merge_overlapping_halves()
+    test_shadow_not_detected_as_object()
+    test_flat_phone_via_rgb()
+    print("OK: geometry + stabilizer tests passed")
--- a/vision_classifier/tracker.py
+++ b/vision_classifier/tracker.py
@@ -0,0 +1,279 @@
+"""Трекинг нескольких объектов в кадре: ID + статистика зон за сессию.
+
+Сопоставление кадр-к-кадру по ближайшему центроиду. На каждый трек —
+свой DecisionStabilizer. LOCK в ленту/MQTT — один раз на товар: после
+фиксации запоминаем «отпечаток» (центр+габариты); если depth кратковременно
+пропал и объект нашёлся снова рядом — трек возрождается без нового LOCK.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Callable, Dict, List, Optional, Sequence, Tuple
+
+from classify import ClassificationResult
+from measure import ObjectMeasurement
+from stabilize import DecisionStabilizer, StableDecision
+
+
+@dataclass
+class Track:
+    track_id: int
+    stabilizer: DecisionStabilizer
+    centroid: Tuple[int, int]
+    miss: int = 0
+    counted_zone: Optional[str] = None
+    counted_uncertain: bool = False
+    measurement: Optional[ObjectMeasurement] = None
+    decision: Optional[StableDecision] = None
+    reported: bool = False  # уже ушёл в ленту — повторно не пишем
+    frozen: Optional[StableDecision] = None  # снимок первого LOCK (для возрождения)
+
+
+@dataclass
+class LockEvent:
+    track_id: int
+    decision: StableDecision
+
+
+@dataclass
+class _Fingerprint:
+    """Товар уже зафиксирован — не считаем повторно при перезахвате."""
+    track_id: int
+    cx: int
+    cy: int
+    length_mm: float
+    width_mm: float
+    height_mm: float
+    zone: str
+    uncertain: bool
+    result: ClassificationResult
+    age: int = 0  # кадров без детекции
+
+
+def slot_key(cx: int, cy: int, L: float, W: float, H: float, zone: str) -> str:
+    """Стабильный ключ товара на ленте — один физический предмет = одна запись."""
+    a = sorted((L, W, H))
+    return f"{cx // 35}_{cy // 35}_{int(a[0] // 12)}_{int(a[1] // 12)}_{int(a[2] // 8)}_{zone}"
+
+
+class MultiObjectTracker:
+    def __init__(
+        self,
+        stabilizer_factory: Callable[[], DecisionStabilizer],
+        max_dist_px: int = 120,
+        lost_frames: int = 12,
+        fingerprint_ttl: int = 450,  # ~15–20 с помнить «уже учтён»
+    ) -> None:
+        self._factory = stabilizer_factory
+        self.max_dist_px = int(max_dist_px)
+        self.lost_frames = int(lost_frames)
+        self.fingerprint_ttl = int(fingerprint_ttl)
+        self._tracks: Dict[int, Track] = {}
+        self._fps: List[_Fingerprint] = []
+        self._seen_slots: Dict[str, _Fingerprint] = {}  # уже учтённые товары (позиция+габариты)
+        self._next_id = 1
+        self.stats: Dict[str, int] = {"B": 0, "C": 0, "D": 0, "total": 0, "uncertain": 0}
+
+    def reset(self) -> None:
+        self._tracks.clear()
+        self._fps.clear()
+
+    def update(
+        self,
+        measurements: List[ObjectMeasurement],
+        min_mm: Sequence[float] = (10, 10, 10),
+        max_mm: Sequence[float] = (450, 320, 320),
+    ) -> Tuple[List[Track], List[LockEvent]]:
+        free_meas = list(range(len(measurements)))
+        assigned: Dict[int, int] = {}
+        pairs = []
+        for tid, tr in self._tracks.items():
+            for mi in free_meas:
+                m = measurements[mi]
+                d2 = (tr.centroid[0] - m.centroid_px[0]) ** 2 + (tr.centroid[1] - m.centroid_px[1]) ** 2
+                pairs.append((d2, tid, mi))
+        for d2, tid, mi in sorted(pairs):
+            if tid in assigned or mi not in free_meas:
+                continue
+            if d2 > self.max_dist_px**2:
+                continue
+            assigned[tid] = mi
+            free_meas.remove(mi)
+
+        events: List[LockEvent] = []
+
+        for tid in list(self._tracks.keys()):
+            tr = self._tracks[tid]
+            # залоченный трек держим дольше — глянец даёт короткие выпадения depth
+            kill_after = self.lost_frames * 3 if tr.counted_zone is not None else self.lost_frames
+            if tid in assigned:
+                m = measurements[assigned[tid]]
+                tr.centroid = m.centroid_px
+                tr.miss = 0
+                tr.measurement = m
+                tr.decision = tr.stabilizer.update(m, min_mm=min_mm, max_mm=max_mm)
+                # после возрождения стабилизатор ещё «холодный» — держим прошлый LOCK на экране
+                if tr.reported and tr.frozen is not None and not (tr.decision and tr.decision.locked):
+                    tr.decision = tr.frozen
+                self._account(tr, events)
+                if tr.reported:
+                    self._touch_fp(tr)
+            else:
+                tr.miss += 1
+                tr.measurement = None
+                tr.decision = tr.stabilizer.update(None, min_mm=min_mm, max_mm=max_mm)
+                if tr.reported and tr.frozen is not None and not (tr.decision and tr.decision.locked):
+                    tr.decision = tr.frozen
+                if tr.miss >= kill_after:
+                    if tr.reported and tr.frozen is not None and tr.frozen.result is not None:
+                        self._remember(tr)
+                    del self._tracks[tid]
+
+        # старение отпечатков
+        for fp in self._fps:
+            fp.age += 1
+        self._fps = [fp for fp in self._fps if fp.age < self.fingerprint_ttl]
+
+        for mi in free_meas:
+            m = measurements[mi]
+            fp = self._match_fp(m)
+            if fp is not None:
+                # тот же товар вернулся после выпадения depth — без нового LOCK
+                fp.age = 0
+                fp.cx, fp.cy = m.centroid_px
+                frozen = StableDecision(
+                    fp.result, True, 100, fp.result.circle_ratio, True, uncertain=fp.uncertain,
+                )
+                tr = Track(
+                    track_id=fp.track_id,
+                    stabilizer=self._factory(),
+                    centroid=m.centroid_px,
+                    measurement=m,
+                    counted_zone=fp.zone,
+                    counted_uncertain=fp.uncertain,
+                    reported=True,
+                    frozen=frozen,
+                    decision=frozen,
+                )
+                self._tracks[tr.track_id] = tr
+                self._fps = [x for x in self._fps if x.track_id != fp.track_id]
+                continue
+
+            tr = Track(
+                track_id=self._next_id,
+                stabilizer=self._factory(),
+                centroid=m.centroid_px,
+                measurement=m,
+            )
+            self._next_id += 1
+            tr.decision = tr.stabilizer.update(m, min_mm=min_mm, max_mm=max_mm)
+            self._tracks[tr.track_id] = tr
+            self._account(tr, events)
+
+        alive = sorted(self._tracks.values(), key=lambda t: t.track_id)
+        return [t for t in alive if t.measurement is not None or t.miss < (
+            self.lost_frames * 3 if t.counted_zone else self.lost_frames
+        )], events
+
+    def _account(self, tr: Track, events: List[LockEvent]) -> None:
+        d = tr.decision
+        if d is None or not d.locked or d.result is None:
+            return
+        zone = d.result.category.zone
+        L, W, H = d.result.dims_sorted_mm
+        sk = slot_key(tr.centroid[0], tr.centroid[1], L, W, H, zone)
+        if tr.counted_zone is None:
+            if sk in self._seen_slots:
+                # тот же товар уже был в ленте/статистике — только показываем на экране
+                prev = self._seen_slots[sk]
+                tr.counted_zone = prev.zone
+                tr.counted_uncertain = prev.uncertain
+                tr.frozen = StableDecision(
+                    prev.result, True, 100, prev.result.circle_ratio, True, uncertain=prev.uncertain,
+                )
+                tr.reported = True
+                tr.decision = tr.frozen
+                return
+            self.stats[zone] = self.stats.get(zone, 0) + 1
+            self.stats["total"] += 1
+            if d.uncertain:
+                self.stats["uncertain"] += 1
+            tr.counted_zone = zone
+            tr.counted_uncertain = d.uncertain
+            tr.frozen = StableDecision(
+                d.result, True, 100, d.result.circle_ratio, True, uncertain=d.uncertain,
+            )
+            self._seen_slots[sk] = _Fingerprint(
+                track_id=tr.track_id,
+                cx=tr.centroid[0],
+                cy=tr.centroid[1],
+                length_mm=float(L),
+                width_mm=float(W),
+                height_mm=float(H),
+                zone=zone,
+                uncertain=d.uncertain,
+                result=d.result,
+            )
+            if not tr.reported:
+                tr.reported = True
+                events.append(LockEvent(tr.track_id, tr.frozen))
+        elif tr.counted_zone != zone:
+            # смена зоны на экране/в счётчиках — в ленту повторно не пишем
+            self.stats[tr.counted_zone] = max(0, self.stats.get(tr.counted_zone, 0) - 1)
+            self.stats[zone] = self.stats.get(zone, 0) + 1
+            if tr.counted_uncertain and not d.uncertain:
+                self.stats["uncertain"] = max(0, self.stats["uncertain"] - 1)
+                tr.counted_uncertain = d.uncertain
+            tr.counted_zone = zone
+            tr.frozen = StableDecision(
+                d.result, True, 100, d.result.circle_ratio, True, uncertain=d.uncertain,
+            )
+
+    def _remember(self, tr: Track) -> None:
+        assert tr.frozen is not None and tr.frozen.result is not None
+        r = tr.frozen.result
+        L, W, H = r.dims_sorted_mm
+        self._fps = [fp for fp in self._fps if fp.track_id != tr.track_id]
+        self._fps.append(
+            _Fingerprint(
+                track_id=tr.track_id,
+                cx=tr.centroid[0],
+                cy=tr.centroid[1],
+                length_mm=float(L),
+                width_mm=float(W),
+                height_mm=float(H),
+                zone=tr.counted_zone or r.category.zone,
+                uncertain=tr.counted_uncertain,
+                result=r,
+                age=0,
+            )
+        )
+
+    def _touch_fp(self, tr: Track) -> None:
+        for fp in self._fps:
+            if fp.track_id == tr.track_id:
+                fp.age = 0
+                fp.cx, fp.cy = tr.centroid
+
+    def _match_fp(self, m: ObjectMeasurement) -> Optional[_Fingerprint]:
+        best: Optional[_Fingerprint] = None
+        best_d2 = self.max_dist_px**2
+        for fp in self._fps:
+            d2 = (fp.cx - m.centroid_px[0]) ** 2 + (fp.cy - m.centroid_px[1]) ** 2
+            if d2 > best_d2:
+                continue
+            if not _dims_close(fp.length_mm, fp.width_mm, fp.height_mm, m.length_mm, m.width_mm, m.height_mm):
+                continue
+            best, best_d2 = fp, d2
+        return best
+
+
+def _dims_close(L0: float, W0: float, H0: float, L1: float, W1: float, H1: float, tol: float = 0.40) -> bool:
+    """Габариты «похожи» (порядок осей уже отсортирован в classify, здесь — сырые L×W×H)."""
+    a = sorted((L0, W0, H0))
+    b = sorted((L1, W1, H1))
+    for x, y in zip(a, b):
+        if abs(x - y) / max(x, y, 1.0) > tol:
+            return False
+    return True
Author	SHA1	Message	Date
drho1y	8aa0c16359	vision model	2026-08-03 01:26:42 +07:00
drho1y	3f8f3a40ec	minor fix	2026-08-03 01:25:02 +07:00
drho1y	e451b84450	fix: CWE-119	2026-07-16 03:46:24 +03:00
drho1y	988a9ebbf1	fix: minor change schematics	2026-07-16 03:21:17 +03:00
drho1y	4aeec2bee7	Update: gui actulization contol panel	2026-07-16 03:20:26 +03:00
drho1y	3b9fc4c874	New: adding vl53l0x sensor	2026-07-16 03:18:20 +03:00
drho1y	2831c396b9	Update: actualize schematic	2026-07-15 23:47:51 +03:00
drho1y	31ca8bacd4	Update: actual control program	2026-07-15 23:45:56 +03:00
drho1y	ff51eccf22	Update: replace board, add servo driver program	2026-07-15 23:44:36 +03:00
drho1y	50638a11be	final: the end of 3d modelling	2026-07-12 12:47:54 +03:00
drho1y	6b395e083e	update: new models	2026-07-12 01:39:08 +03:00
drho1y	6f57372d30	update: fix model	2026-07-10 03:40:41 +07:00
drho1y	2618bd9a7f	update: create new models	2026-07-09 14:48:40 +07:00
drho1y	f38e3ff273	Update: adding al profile and some models	2026-07-08 20:36:15 +07:00
drho1y	422d438b85	New: 3D models	2026-07-08 05:01:29 +07:00
drho1y	a75d74cab4	New: Create 3D model sptep-drive nema17	2026-07-08 00:39:59 +07:00
drho1y	256dfbe280	fix: minor change schematic	2026-07-08 00:00:37 +07:00
drho1y	00d60d03fb	Update: update specification	2026-07-07 23:57:00 +07:00
drho1y	0a0c5915ca	fix: change pin number, for spare i2c communication	2026-07-07 23:55:54 +07:00
drho1y	fd8be02416	New: adding TOF laser and more servo-drive	2026-07-07 23:54:11 +07:00
drho1y	c62ebaae16	New: adding servo-drive	2026-07-07 21:56:00 +07:00
drho1y	893f881419	fix: update gui interface	2026-07-07 21:54:53 +07:00
drho1y	023e699771	New: adding control servo-drive	2026-07-07 21:54:03 +07:00
drho1y	b69fe70122	Update schematic	2026-07-07 17:25:57 +07:00
drho1y	70bdfc1c5c	minor edit	2026-07-07 17:24:06 +07:00
drho1y	ff49b03be2	Create gui interface for controll step-drive	2026-07-07 17:23:07 +07:00
drho1y	15645f7d25	Switch controlling step driver to serial interface	2026-07-07 05:31:54 +07:00
drho1y	2c4aae9523	delete unused command	2026-07-07 05:31:02 +07:00
drho1y	e546707069	Update to actual schematic	2026-07-07 00:20:54 +07:00
drho1y	5fa88eaa56	update script	2026-07-06 23:12:12 +07:00
drho1y	9c522fb95c	refactoring codebase	2026-07-06 23:11:34 +07:00
drho1y	77997736f1	update script	2026-07-06 21:36:58 +07:00
drho1y	8f43b9f455	adding more mqtt topics	2026-07-06 21:36:09 +07:00
drho1y	6ffc2e606b	adding backend script + test program for microcontroller	2026-07-06 18:25:06 +07:00
drho1y	d09e1a58e5	adding README and gitignore files	2026-07-06 18:24:11 +07:00
drho1y	93dce8e237	Добавил mindmap	2026-07-04 21:16:40 +07:00
drho1y	e923afd4c7	Добавил набросок конвейера, примерный список запчастей. И записал возможные проблемы и решение от ии	2026-07-03 02:39:23 +07:00