我正在使用PyTorch和OpenCV的YOLO算法实现一个对象检测模型.在单个视频上运行我的模型效果很好.但是,每当我试图使用多处理同时测试更多视频时,它都会冻结.你能解释一下这个代码有什么问题吗??
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] < 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()
每次我运行代码时,它都会冻结.
Downloading: "https://github.com/ultralytics/yolov5/archive/master.zip" 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...