release: consolidate web simulation and real CV prototype

Add cleaned RealSense/OpenCV CV under cv/ with secret-free example
config, MQTT disabled by default, and canonical README coverage for
web + CV relationship without claiming production integration.

Co-authored-by: Cursor <cursoragent@cursor.com>

cv/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())