行人检测并跟踪 | 源代码 | Python & OpenCV

采用帧差法初步筛选体积较大的运动目标，若运动目标符合一定条件，则触发基于OpenCV的hog+svm的行人检测和物体跟踪算法对视频内人进行跟踪。

行人检测 | 行人跟踪 | 运动物体检测 & 跟踪 | OpenCV & Python | 源代码

!pip install opencv-python==4.5.5.64
!pip install opencv-contrib-python

def  objection_tracing(image, box):



    (major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')

    if __name__ == '__main__' :
 
    # Set up tracker.
    # Instead of MIL, you can also use
 
        tracker_types = ['BOOSTING', 'MIL','KCF', 'TLD', 'MEDIANFLOW', 'GOTURN', 'MOSSE']
        tracker_type = tracker_types[2]
        print(tracker_type)
        if int(minor_ver) < 0:
            tracker = cv2.Tracker_create(tracker_type)
        else:
            if tracker_type == 'BOOSTING':
                tracker = cv2.TrackerBoosting_create()
            if tracker_type == 'MIL':
                tracker = cv2.TrackerMIL_create()
            if tracker_type == 'KCF':
                tracker = cv2.TrackerKCF_create()
            if tracker_type == 'TLD':
                tracker = cv2.TrackerTLD_create()
            if tracker_type == 'MEDIANFLOW':
                tracker = cv2.TrackerMedianFlow_create()
            if tracker_type == 'GOTURN':
                tracker = cv2.TrackerGOTURN_create()
            if tracker_type == 'MOSSE':
                tracker = cv2.TrackerMOSSE_create()
 

 

    # Read  frame.
        frame = image
     
    # Define an initial bounding box
        bbox = box
 

 
    # Initialize tracker with first frame and bounding box
        ok = tracker.init(frame, bbox)
 
        while True:
        # Read a new frame
            ok, frame = capture.read()
            if not ok:
                break
         
        # Start timer
            timer = cv2.getTickCount()
 
        # Update tracker
            ok, bbox = tracker.update(frame)
 
        # Calculate Frames per second (FPS)
            fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer);
 
        # Draw bounding box
            if ok:
            # Tracking success
                p1 = (int(bbox[0]), int(bbox[1]))
                p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3]))
                cv2.rectangle(frame, p1, p2, (255,0,0), 2, 1)
            else :
            # Tracking failure
                cv2.putText(frame, "Tracking failure detected", (100,80), cv2.FONT_HERSHEY_SIMPLEX, 0.75,(0,0,255),2)
                return
        # Display tracker type on frame
            cv2.putText(frame, tracker_type + " Tracker", (100,20), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50),2);
     
        # Display FPS on frame
            cv2.putText(frame, "FPS : " + str(int(fps)), (100,50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50), 2);
 
        # Display result
            cv2.imshow("person", frame)
 
        # Exit if ESC pressed
            k = cv2.waitKey(1) & 0xff
            if k == 27 : break
    cv2.destroyAllWindows()