如何提高 OpenCV cv2.VideoCapture(0).read() 的性能

Fil*_*ppo 6 python video performance opencv video-streaming

我在使用 intel core i7-4510u 的 Kali linux 上运行此脚本:

import cv2
from datetime import datetime
vid_cam = cv2.VideoCapture(0)
vid_cam.set(cv2.CAP_PROP_FPS, 25)
vid_cam.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
vid_cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 360)

lastDate = datetime.now().second
fcount = 0
while(vid_cam.isOpened()):
    if(datetime.now().second>lastDate):
        lastDate = datetime.now().second
        print("Fps: " + str(fcount))
        fcount = 0
    else:
        fcount += 1
    ret, image_frame = vid_cam.read()
    cv2.imshow('frame', image_frame)
    if cv2.waitKey(100) & 0xFF == ord('q'):
        break
vid_cam.release()
cv2.destroyAllWindows()
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如果我运行它,它会打印Fps: 4
如果我检查任务管理器,我的 cpu 大约为 2%
问题可能出在哪里?

nat*_*ncy 2

一个潜在的原因可能是读取帧时的 I/O 延迟。由于cv2.VideoCapture().read()这是一个阻塞操作,因此主程序会停止,直到从相机设备读取帧并返回为止。提高性能的一种方法是生成另一个线程来并行处理抓取帧,不是依赖单个线程按顺序抓取帧。我们可以通过创建一个新线程来提高性能,该线程仅轮询新帧,而主线程则负责处理当前帧。这是多线程框架的片段。

from threading import Thread
import cv2, time

class VideoStreamWidget(object):
    def __init__(self, src=0):
        self.capture = cv2.VideoCapture(src)
        # Start the thread to read frames from the video stream
        self.thread = Thread(target=self.update, args=())
        self.thread.daemon = True
        self.thread.start()

    def update(self):
        # Read the next frame from the stream in a different thread
        while True:
            if self.capture.isOpened():
                (self.status, self.frame) = self.capture.read()
            time.sleep(.01)

    def show_frame(self):
        # Display frames in main program
        cv2.imshow('frame', self.frame)
        key = cv2.waitKey(1)
        if key == ord('q'):
            self.capture.release()
            cv2.destroyAllWindows()
            exit(1)

if __name__ == '__main__':
    video_stream_widget = VideoStreamWidget()
    while True:
        try:
            video_stream_widget.show_frame()
        except AttributeError:
            pass
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