add app files

notebooks/app/Predict_video.py

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+import pickle
+import customtkinter as ctk
+import os
+from mtcnn import MTCNN
+from catboost import CatBoostClassifier
+from facenet_pytorch import MTCNN
+from PIL import Image
+import torch
+import cv2
+import time
+from FastMtcnn import FastMTCNN
+import threading
+
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+
+
+class PredictV(ctk.CTkFrame):
+    def __init__(self, master):
+        super().__init__(master)
+        self.counter = 0
+        self.storage_name: str
+        self.grid_columnconfigure(0, weight=1)
+        self.detector = MTCNN()
+        self.catboost_model_usa = CatBoostClassifier()
+        self.catboost_model_usa.load_model("../catboost_usa.cbm")
+        self.fast_mtcnn = FastMTCNN(
+            stride=32,
+            resize=1,
+            margin=14,
+            factor=0.6,
+            keep_all=True,
+            device=device
+        )
+        self.catboost_model_usa.load_model("../catboost_usa.cbm")
+        with open('../model/saved_dictionary.pkl', 'rb') as f:
+            self.name_usa = pickle.load(f)
+        self.label = ctk.CTkLabel(self, text="Video", fg_color="blue", text_color="white")
+        self.label.grid(row=0, column=0, sticky="ew")
+        self.button_start_predict = ctk.CTkButton(self, text="Start predict", command=self.run_detection)
+        self.button_start_predict.grid(row=1, column=0, pady=10, sticky="ew")
+
+    def __open_file_dialog(self):
+        root = ctk.CTk()
+        root.withdraw()
+        file_path = ctk.filedialog.askdirectory(title='Choose image dataset')
+        if file_path != '':
+            root.destroy()
+            self.storage_name = file_path
+            self.iterator = iter(os.listdir(self.storage_name))
+            return file_path
+
+    def run_detection(self):
+        frames = []
+        batch_size = 256
+        cap = cv2.VideoCapture(0)
+        self.image_usa = cv2.resize(cap.read()[1], (1080, 720))
+        while True:
+            frame = cv2.resize(cap.read()[1], (1080, 720))
+            frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            frames.append(frame)
+            im_h = cv2.hconcat([frame, self.image_usa])
+            cv2.imshow("tester", im_h)
+            if cv2.waitKey(1) == 27:
+                break
+
+            if len(frames) >= batch_size:
+                index_usa = self.fast_mtcnn(frames)
+                frames = []
+                def set_image_all(index_usa):
+                    print(index_usa)
+                    for images in os.listdir(
+                            f'C://Users//fatik//PycharmProjects//UfaHack2024//data//actors_usa//{index_usa}'):
+                        self.image_usa = cv2.imread(
+                            os.path.join(f'C://Users//fatik//PycharmProjects//UfaHack2024//data//actors_usa//{index_usa}', images))
+                        self.image_usa = cv2.resize(self.image_usa, (1080, 720))
+                        break
+                    def set_image():
+                        self.image = Image.fromarray(self.image_usa)
+                        self.image_tk = ctk.CTkImage(self.image, size=(self.image.width, self.image.height))
+                        self.label_image = ctk.CTkLabel(self, image=self.image_tk, text=self.name_usa[index_usa], text_color="red")
+                        self.label_image.grid(row=2, column=0, pady=10, sticky="ew")
+                    thread = threading.Thread(target=set_image)
+                    thread.start()
+
+                target1 = threading.Thread(target=set_image_all, args=(index_usa,))
+                target1.start()
+