I am implementing an object detection model using a YOLO algorithm with PyTorch and OpenCV. Running my model on a single video works fine. But whenever I am trying to use multiprocessing for testing more videos at once it is freezing. Can you please explain what is wrong with this code ??
import torchimport cv2import timefrom multiprocessing import Processmodel = torch.hub.load('ultralytics/yolov5', 'custom', path='runs/best.pt', force_reload=True)def detectObject(video,name): cap = cv2.VideoCapture(video) while cap.isOpened(): pTime = time.time() ret, img = cap.read() cTime = time.time() fps = str(int(1 / (cTime - pTime))) if img is None: break else: results = model(img) labels = results.xyxyn[0][:, -1].cpu().numpy() cord = results.xyxyn[0][:, :-1].cpu().numpy() n = len(labels) x_shape, y_shape = img.shape[1], img.shape[0] for i in range(n): row = cord[i] # If score is less than 0.3 we avoid making a prediction. if row[4] < 0.3: continue x1 = int(row[0] * x_shape) y1 = int(row[1] * y_shape) x2 = int(row[2] * x_shape) y2 = int(row[3] * y_shape) bgr = (0, 255, 0) # color of the box classes = model.names # Get the name of label index label_font = cv2.FONT_HERSHEY_COMPLEX # Font for the label. cv2.rectangle(img, (x1, y1), (x2, y2), bgr, 2) # Plot the boxes cv2.putText(img, classes[int(labels[i])], (x1, y1), label_font, 2, bgr, 2) cv2.putText(img, f'FPS={fps}', (8, 70), label_font, 3, (100, 255, 0), 3, cv2.LINE_AA) img = cv2.resize(img, (700, 700)) cv2.imshow(name, img) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release()Videos = ['../Dataset/Test1.mp4','../Dataset/Test2.mp4']for i in Videos: process = Process(target=detectObject, args=(i, str(i))) process.start()Every time I run that code it freezes.Here is the output :
Downloading: "https://github.com/ultralytics/yolov5/archive/master.zip" to /home/com/.cache/torch/hub/master.zipYOLOv5 🚀 2022-6-27 Python-3.9.9 torch-1.11.0+cu102 CPUFusing layers... YOLOv5s summary: 213 layers, 7023610 parameters, 0 gradientsAdding AutoShape... 
