OpenCV视频流Python多线程处理方法详细分析

1. OpenCV视频流Python多线程处理方法
   在使用OpenCV处理视频流时，使用多线程可以有效提高视频流的处理速度。具体方法如下：

2. 导入所需模块

import cv2
import threading
import time

• 定义视频流线程类

class VideoStreamThread:
    def __init__(self, video_path):
        self.video_path = video_path  # 视频路径
        self.frame = None  # 存放当前帧图像

    def start(self):
        self.stop_flag = False  # 停止标志位
        self.thread = threading.Thread(target=self.run)  # 创建线程
        self.thread.start()  # 启动线程

    def stop(self):
        self.stop_flag = True  # 标志位设为True
        self.thread.join()  # 等待线程结束

    def run(self):
        cap = cv2.VideoCapture(self.video_path)  # 打开视频流
        while not self.stop_flag:
            ret, frame = cap.read()  # 读取当前帧
            if not ret:
                break
            self.frame = frame.copy()  # 将图像复制到frame变量中

        cap.release()  # 释放视频流

• 定义视频处理线程类

class VideoProcessThread:
    def __init__(self, stream):
        self.stream = stream  # 视频流对象

    def start(self):
        self.stop_flag = False  # 停止标志位
        self.thread = threading.Thread(target=self.run)  # 创建线程
        self.thread.start()  # 启动线程

    def stop(self):
        self.stop_flag = True  # 标志位设为True
        self.thread.join()  # 等待线程结束

    def run(self):
        while not self.stop_flag:
            if self.stream.frame is None:
                time.sleep(0.01)
                continue
            # 进行图像处理
            frame = self.stream.frame.copy()
            # todo

• 主程序调用

if __name__ == '__main__':
    video_path = 'test.mp4'
    stream = VideoStreamThread(video_path)
    process = VideoProcessThread(stream)

    stream.start()
    process.start()

    cv2.namedWindow('frame')
    while True:
        if stream.frame is not None:
            cv2.imshow('frame', stream.frame)
            if cv2.waitKey(1) & 0xFF == ord('q'):
                break
    cv2.destroyAllWindows()

    stream.stop()
    process.stop()

1. 示例说明

假设我们需要处理5个视频，可以采用多线程来同时处理多个视频。具体实现方法如下：

• 定义多线程的视频流类

class MultiVideoStream:
    def __init__(self, video_paths):
        self.video_streams = []  # 存放多个VideoStreamThread对象
        for video_path in video_paths:
            self.video_streams.append(VideoStreamThread(video_path))

    def start(self):
        self.stop_flag = False  # 停止标志位
        # 启动所有视频流线程
        for video_stream in self.video_streams:
            video_stream.start()

        self.thread = threading.Thread(target=self.run)  # 创建线程
        self.thread.start()  # 启动线程

    def stop(self):
        self.stop_flag = True  # 停止标志位设为True
        self.thread.join()  # 等待线程结束

        # 释放所有视频流
        for video_stream in self.video_streams:
            video_stream.stop()

    def run(self):
        while not self.stop_flag:
            for video_stream in self.video_streams:
                if video_stream.frame is None:
                    time.sleep(0.01)
                else:
                    # 进行图像处理
                    frame = video_stream.frame.copy()
                    # todo

• 主程序调用

if __name__ == '__main__':
    video_paths = ['test1.mp4', 'test2.mp4', 'test3.mp4', 'test4.mp4', 'test5.mp4']
    multi_stream = MultiVideoStream(video_paths)
    multi_stream.start()

    while True:
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    cv2.destroyAllWindows()
    multi_stream.stop()