opencv-python——如何从代码角度提高摄像头帧率

文章目录

• ​​运行一段opencv-python调用摄像头实现Apriltag识别的程序​​

• ​​基于Intel i7 8th Gen 笔记本​​

• ​​平均执行速度：0.060s/帧​​

• ​​使用多进程，将识别代码放在子进程中执行​​

• ​​平均执行速度：0.048s/帧，提速了20%​​

• ​​基于Jetson Nano​​

• ​​平均执行速度：0.07s/帧​​

运行一段opencv-python调用摄像头实现Apriltag识别的程序

def Aptag_detect(cap):
        # 读取视频帧，ret标志读取的结果，frame为读取到的视频帧图像
    start = time.time()
    ret, frame = cap.read()

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Build a detector for apriltag
    tag_detector = apriltag.Detector()  

    # Perform apriltag detection to get a list of detected apriltag
    tags = tag_detector.detect(gray)

    print("%d apriltags have been detected."%len(tags))

    for tag in tags:
        cv2.circle(frame, tuple(tag.corners[0].astype(int)), 4,(0,0,255), 2) # left-top
        cv2.circle(frame, tuple(tag.corners[1].astype(int)), 4,(0,0,255), 2) # right-top
        cv2.circle(frame, tuple(tag.corners[2].astype(int)), 4,(0,0,255), 2) # right-bottom
        cv2.circle(frame, tuple(tag.corners[3].astype(int)), 4,(0,0,255), 2) # left-bottom
        print("family:",tag.tag_family)
        print("id:", tag.tag_id)
        print("conners:", tag.corners)
        print("homography:", tag.homography)
        
    cv2.imshow("apriltag_test",frame)
    end = time.time()
    time_list.append(end-start)
    avarge = sum(time_list) / len(time_list)
    print("detect:", end-start)
    print("avarge:",avarge)

while 1:
    Aptag_detect(cap)

基于Intel i7 8th Gen 笔记本

平均执行速度：0.060s/帧

使用多进程，将识别代码放在子进程中执行

if __name__ == "__main__":
    cap0 = cv2.VideoCapture(0)
    cap1 = cv2.VideoCapture(1)
    cap2 = cv2.VideoCapture(2)

    while 1:
        start = time.time()
        #cap0_process = multiprocessing.Process(target=Aptag_cap, args=[cap0])
        ret, frame = Aptag_cap(cap0)
        cap1_process = multiprocessing.Process(target=Aptag_only_detect, args=[ret, frame]) #Aptag_cap(cap0)[0], Aptag_cap(cap0)[1]
        #cap0_process.run()
        cap1_process.run()
        end = time.time()
        time_list.append(end-start)
        avarge = sum(time_list) / len(time_list)
        print("all_avarge:",avarge)

平均执行速度：0.048s/帧，提速了20%

基于Jetson Nano

平均执行速度：0.07s/帧