Implement multiprocessing to test two videos simultaneously in opencv for object detection
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 torch
import cv2
import time
from multiprocessing import Process

model = 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] &lt; 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) &amp; 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: &quot;https://github.com/ultralytics/yolov5/archive/master.zip&quot; to /home/com/.cache/torch/hub/master.zip
YOLOv5  2022-6-27 Python-3.9.9 torch-1.11.0+cu102 CPU

Fusing layers... 
YOLOv5s summary: 213 layers, 7023610 parameters, 0 gradients
Adding AutoShape... 


I got it to work by adding torch multiprocessing code.
from torch.multiprocessing import Pool, Process, set_start_method
try:
     set_start_method('spawn', force=True)
except RuntimeError:
    pass

videos = ['videos/video1.mp4', 'videos/video2.mp4']
for i in videos:
    process = Process(target=detectObject, args=(i, str(i)))
    process.start()

I was able to run on multiple videos at once this way.
