【相机+处理】多线程读取实时帧进行图像处理

【相机+处理】多线程读取实时帧进行图像处理

多线程编写相机与后期的图像处理
目的是读取实时帧进行处理
分为两个线程
子线程进行图像的刷新
主进程抓取图像进行处理

rtsp流–最终版–＋锁–继承后重写run方法

import threading
import time
import cv2

# 创建一个线程类
class ImageThread(threading.Thread):
    def __init__(self):
        super(ImageThread, self).__init__()
        self.latest_image = None  # 存储最新的图像
        self.lock = threading.Lock()  # 创建一个锁对象

    def run(self):
        cap = cv2.VideoCapture("rtsp://admin:[email protected]:554/h264/ch33/main/av_stream")  # 打开相机
        while True:
            ret, frame = cap.read()  # 读取相机图像
            if not ret:
                continue
            with self.lock:  # 获取锁
                self.latest_image = frame  # 更新最新的图像
            time.sleep(0.01)  # 线程等待一小段时间

    def get_latest_image(self):
        with self.lock:  # 获取锁
            return self.latest_image  # 返回最新的图像

# 创建一个ImageThread实例，并启动线程
image_thread = ImageThread()
image_thread.start()

# 主进程调用最新的图像
while True:
    latest_image = image_thread.get_latest_image()
    if latest_image is not None:
        cv2.imshow('Latest Image', latest_image)  # 显示最新的图像
    if cv2.waitKey(1) == ord('q'):  # 按下'q'键退出
        break

# 释放资源
cv2.destroyAllWindows()

备注： time.sleep(0.01) # 线程等待一小段时间，这句代码的目的是->"在这一步释放GIL锁",使得其他线程进行执行，直到每一个线程都释放GIL锁后，在逐次往下执行。

RTSP流不加锁版（因为没有锁，所以会有问题–教训版–(继承线程并重写run方法)

# -*- coding: utf-8 -*-

import threading
import time
import cv2

flag = True

# 创建一个线程类
class ImageThread(threading.Thread):
    def __init__(self):
        super(ImageThread, self).__init__()
        self.latest_image = None  # 存储最新的图像

    def run(self):
        cap = cv2.VideoCapture("rtsp://admin:[email protected]:554/h264/ch33/main/av_stream")  # 打开相机
        # cap = cv2.VideoCapture(4)  # 打开相机
        while True:
            ret, frame = cap.read()  # 读取相机图像
            if not ret:
                continue

            self.latest_image = frame  # 更新最新的图像
            time.sleep(0.01)  # 线程等待一小段时间

    def get_latest_image(self):
        return self.latest_image  # 返回最新的图像

# 创建一个ImageThread实例，并启动线程
image_thread = ImageThread()
image_thread.start()

# 主进程调用最新的图像
while True:
    # flag = False
    # time.sleep(2)
    latest_image = image_thread.get_latest_image()

    if latest_image is not None:
        cv2.imshow('Latest Image', latest_image)  # 显示最新的图像
    if cv2.waitKey(1) == ord('q'):  # 按下'q'键退出
        break

# 释放资源
cv2.destroyAllWindows()

直接拉流版 --最直接的 CV 拉流版

import cv2  # 引入CV库
# 创建窗口
cv2.namedWindow('video', cv2.WINDOW_NORMAL)
cv2.resizeWindow('video', 300, 300)  # 设置窗口大小

#   rtsp://admin:[email protected]:554/h264/ch33/main/av_stream
# 获取视频设备
cap = cv2.VideoCapture("rtsp://admin:[email protected]:554/h264/ch33/main/av_stream")
while True:
    # 从摄像头读视频帧
    ret, frame = cap.read()
    # 将视频帧在窗口中显示
    cv2.imshow('video', frame)
    key = cv2.waitKey(27)  # 不能为0，0为等待中断，只能读取到一帧的数据
    if (key & 0xFF == ord('q')):
        break

# 释放资源
cap.release()  # 释放视频资源
cv2.destroyAllWindows()  # 释放窗口资源

无锁–没继承–初始化对象即启动线程

import os
import time
from threading import Thread
import cv2
import numpy as np

class RealsenseCamera(object):
    def __init__(self):

        self.image = None
        # 获取视频设备
        self.capture = cv2.VideoCapture("")
        self.get_img_thread = Thread(target=self.read_camera_img, args=())

    def get_img_thread_start(self):
        self.get_img_thread.daemon = True
        self.get_img_thread.start()
        time.sleep(2)  # 主线程比子线程执行的要快，所以这里要多给子线程点时间
        # self.get_img_thread.join()

    def read_camera_img(self):
        if self.capture.isOpened():
            size = (self.capture.get(cv2.CAP_PROP_FRAME_WIDTH), self.capture.get(cv2.CAP_PROP_FRAME_HEIGHT))  # 读取帧的宽、高
            speed = self.capture.get(cv2.CAP_PROP_FPS)  # 获得帧速
        try:
            while True:
                # Wait for a coherent pair of frames: depth and color
                ret, color_image = self.capture.read()

                if ret is True:
                    self.image = color_image
                else:
                    print("无法拉取到正确的视频流")
                    break
        finally:
            # Stop streaming
            cv2.destroyAllWindows()

    def grab_image(self):
        return self.image


if __name__ == '__main__':
    test = RealsenseCamera()
    test.get_img_thread_start()

    while True:
        color_image = test.grab_image()
        cv2.namedWindow('RealSense', cv2.WINDOW_NORMAL)
        cv2.imshow('RealSense', color_image)
        key = cv2.waitKey(1)
        if key & 0xFF == ord('q'):
            break

realsense版–无锁–没继承–初始化对象即启动线程

import os
import time
from threading import Thread

import cv2
import numpy as np
import pyrealsense2 as rs


class RealsenseCamera(object):
    def __init__(self):
        self.pipeline = rs.pipeline()
        self.config = rs.config()
        self.image = None
        self.config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
        # 这里设置分辨率--档位为官方给定--适用于D435I相机(),所以其他型号的相机可能某些分辨率的档位会不同
        # self.config.enable_stream(rs.stream.color, 320, 180, rs.format.bgr8, 60)

        # self.config.enable_stream(rs.stream.color, 320, 240, rs.format.bgr8, 60)
        # self.config.enable_stream(rs.stream.color, 424, 240, rs.format.bgr8, 60)
        # self.config.enable_stream(rs.stream.color, 640, 360, rs.format.bgr8, 60)
        # self.config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 60)
        # self.config.enable_stream(rs.stream.color, 848, 480, rs.format.bgr8, 60)
        # self.config.enable_stream(rs.stream.color, 960, 540, rs.format.bgr8, 60)
        # self.config.enable_stream(rs.stream.color, 1280, 720, rs.format.bgr8, 30)
        self.config.enable_stream(rs.stream.color, 1920, 1080, rs.format.bgr8, 30)

        self.get_img_thread = Thread(target=self.read_camera_img, args=())


    def get_img_thread_start(self):
        self.get_img_thread.daemon = True
        self.get_img_thread.start()
        time.sleep(2)  # 主线程比子线程执行的要快，所以这里要多给子线程点时间
        # self.get_img_thread.join()


    def read_camera_img(self):
        # Get device product line for setting a supporting resolution
        # pipeline_wrapper = rs.pipeline_wrapper(self.pipeline)
        # pipeline_profile = self.config.resolve(pipeline_wrapper)
        # device = pipeline_profile.get_device()
        # device_product_line = str(device.get_info(rs.camera_info.product_line))
        # print(device_product_line)
        # found_rgb = False
        # for s in device.sensors:
        #     if s.get_info(rs.camera_info.name) == 'RGB Camera':
        #         found_rgb = True
        #         break
        # if not found_rgb:
        #     print("The demo requires Depth camera with Color sensor")
        #     exit(0)

        # Start streaming
        self.pipeline.start(self.config)
        try:
            while True:
                # Wait for a coherent pair of frames: depth and color
                frames = self.pipeline.wait_for_frames()
                depth_frame = frames.get_depth_frame()
                color_frame = frames.get_color_frame()
                depth_image = np.asanyarray(depth_frame.get_data())
                color_image = np.asanyarray(color_frame.get_data())
                if color_image is not None:
                    self.image = color_image
                else:
                    print("color_image is None")
                    continue
        finally:
            # Stop streaming
            self.pipeline.stop()


    def grab_image(self):
        return self.image


if __name__ == '__main__':
    test = RealsenseCamera()
    test.get_img_thread_start()
    f_count = 0
    i = 0
    t1 = time.time()
    while True:
        if f_count > 300:
            t1 = time.time()
            f_count = 0

        color_image = test.grab_image()
        f_count += 1
        fps = int(f_count / (time.time() - t1))
        cv2.putText(color_image, "FPS: %.1f" % (fps), (int(20), int(40)), 0, 5e-3 * 200, (0, 255, 0), 3)
        cv2.namedWindow('RealSense', cv2.WINDOW_NORMAL)
        cv2.imshow('RealSense', color_image)
        key = cv2.waitKey(1)

        if key & 0xFF == ord('q'):
            break
        elif key & 0xFF == ord('c'):
            while f"data_{i}.png" in os.listdir("./"):
                i += 1
            cv2.imwrite(f"./data_{i}.png", color_image)