这是我定义的函数，当读取电脑摄像头视频流时，会导致前端卡住阻塞。直接放视频没问题，一些rtsp的视频流有时好有时坏。请问如何解决。我了解到可能原因是电脑摄像头有打开时间，然后read读不到就卡死了，如何解决呢
def button_camera_open(self):
if not self.timer_video.isActive():
# 默认使用第一个本地camera
flag1 = self.cap.open(0)
self.cap.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'))
if flag1 == False:
QtWidgets.QMessageBox.warning(
self, u"Warning", u"打开摄像头失败", buttons=QtWidgets.QMessageBox.Ok,
defaultButton=QtWidgets.QMessageBox.Ok)
else:
self.out = cv2.VideoWriter(r'D:\videos\prediction1.avi', cv2.VideoWriter_fourcc(
*'MJPG'), 30, (int(self.cap.get(3)), int(self.cap.get(4))))
self.timer_video.start(100)
#self.pushButton_3.setDisabled(True)
#self.pushButton.setDisabled(True)
self.pushButton.setText(u"关闭摄像头")
else:
self.timer_video.stop()
self.cap.release()
self.out.release()
self.label.clear()
self.init_logo()
#self.pushButton_3.setDisabled(False)
#self.pushButton.setDisabled(False)
self.pushButton.setText(u"摄像头检测"）
def show_video_frame(self):
name_list1 = []
if self.cap.isOpened():
flag1, img1 = self.cap.read()
if flag1:
showimg1 = img1
with torch.no_grad():
img1 = letterbox(img1, new_shape=self.opt.img_size)[0]
img1[0:320,0:640]=[0,0,0]
# Convert
# BGR to RGB, to 3x416x416
img1 = img1[:, :, ::-1].transpose(2, 0, 1)
img1 = np.ascontiguousarray(img1)
img1 = torch.from_numpy(img1).to(self.device)
img1 = img1.half() if self.half else img1.float() # uint8 to fp16/32
img1 /= 255.0 # 0 - 255 to 0.0 - 1.0
if img1.ndimension() == 3:
img1 = img1.unsqueeze(0)
# Inference
pred1 = self.model(img1, augment=self.opt.augment)[0]
# Apply NMS
pred1 = non_max_suppression(pred1, self.opt.conf_thres, self.opt.iou_thres, classes=self.opt.classes,
agnostic=self.opt.agnostic_nms)
# Process detections
for i, det1 in enumerate(pred1): # detections per image
if det1 is not None and len(det1):
# Rescale boxes from img_size to im0 size
det1[:, :4] = scale_boxes(
img1.shape[2:], det1[:, :4], showimg1.shape).round()
# Write results
for *xyxy1, conf1, cls1 in reversed(det1):
label1 = '%s %.2f' % (self.names[int(cls1)], conf1)
name_list1.append(self.names[int(cls1)])
print(label1)
plot_one_box(
xyxy1, showimg1, label=label1, color=self.colors[int(cls1)], line_thickness=2)
self.out.write(showimg1)
show1 = cv2.resize(showimg1, (640, 480))
self.result1 = cv2.cvtColor(show1, cv2.COLOR_BGR2RGB)
showImage1 = QtGui.QImage(self.result1.data, self.result1.shape[1], self.result1.shape[0],
QtGui.QImage.Format_RGB888)
self.label.setPixmap(QtGui.QPixmap.fromImage(showImage1))
else:
self.timer_video.stop()
self.cap.release()
self.out.release()
self.label.clear()
单线程当然卡死呀，你可以用多线程来解决阻塞。创建两个线程，一个用于读取视频帧并将其放入队列中，另一个用于从队列中读取视频帧并进行显示。你参考一下
import threading
import queue
class VideoCaptureThread(threading.Thread):
def __init__(self, cap, frame_queue):
super().__init__()
self.cap = cap
self.frame_queue = frame_queue
self._stop_event = threading.Event()
def run(self):
while not self._stop_event.is_set():
ret, frame = self.cap.read()
if ret:
self.frame_queue.put(frame)
else:
self.stop()
def stop(self):
self._stop_event.set()
class VideoDisplayThread(threading.Thread):
def __init__(self, frame_queue, label):
super().__init__()
self.frame_queue = frame_queue
self.label = label
self._stop_event = threading.Event()
def run(self):
while not self._stop_event.is_set():
try:
frame = self.frame_queue.get(timeout=0.1)
except queue.Empty:
continue
# 进行图片处理
# ...
# 显示图片
# ...
def stop(self):
self._stop_event.set()
在button_camera_open方法中，创建队列和两个线程：
from queue import Queue
self.frame_queue = Queue()
self.capture_thread = VideoCaptureThread(self.cap, self.frame_queue)
self.display_thread = VideoDisplayThread(self.frame_queue, self.label)
self.capture_thread.start()
self.display_thread.start()
在show_video_frame方法中，不再调用cap.read()方法，而是从队列中读取视频帧：
def show_video_frame(self):
name_list1 = []
try:
img1 = self.frame_queue.get(timeout=0.1)
except queue.Empty:
return
# 进行图片处理
# ...
# 显示图片
# ...
在button_camera_close方法中，停止两个线程：
self.capture_thread.stop()
self.display_thread.stop()
最后注意一下队列的缓冲区有限，如果处理图片的速度比读取视频帧的速度慢，则队列可能会被填满，导致读取线程阻塞。你可以在队列中保留最近的几帧视频。