自学教程：Python使用OPENCV的目标跟踪算法实现自动视频标注效果

import cv2import osimport timefrom lxml import etree #视频路径Vs = cv2.VideoCapture('peaple.avi')#自定义标签Label = {1:"people",2:"car",3:"Camera"}#图片保存路径 ，一定使用要用绝对路径！！imgpath = r"C:/Users/BGT/Desktop/opencv/img"#xml保存路径 ，一定使用要用绝对路径！！xmlpath = r"C:/Users/BGT/Desktop/opencv/xml"#设置视频缩放cv2.namedWindow("frame", 0)#设置视频宽高cv2.resizeWindow("frame", 618, 416) #定义生成xml类class Gen_Annotations:    def __init__(self, json_info):        self.root = etree.Element("annotation")         child1 = etree.SubElement(self.root, "folder")        child1.text = str(json_info["pic_dirname"])         child2 = etree.SubElement(self.root, "filename")        child2.text = str(json_info["filename"])         child3 = etree.SubElement(self.root, "path")        child3.text = str(json_info["pic_path"])         child4 = etree.SubElement(self.root, "source")         child5 = etree.SubElement(child4, "database")        child5.text = "My name is BGT"     def set_size(self, witdh, height, channel):        size = etree.SubElement(self.root, "size")        widthn = etree.SubElement(size, "width")        widthn.text = str(witdh)        heightn = etree.SubElement(size, "height")        heightn.text = str(height)        channeln = etree.SubElement(size, "depth")        channeln.text = str(channel)        segmented = etree.SubElement(self.root, "segmented")        segmented.text = "0"     def savefile(self, filename):        tree = etree.ElementTree(self.root)        tree.write(filename, pretty_print=True, xml_declaration=False, encoding='utf-8')     def add_pic_attr(self, label, x0, y0, x1, y1):        object = etree.SubElement(self.root, "object")        namen = etree.SubElement(object, "name")        namen.text = label        pose = etree.SubElement(object, "pose")        pose.text = "Unspecified"        truncated = etree.SubElement(object, "truncated")        truncated.text = "0"        difficult = etree.SubElement(object, "difficult")        difficult.text = "0"        bndbox = etree.SubElement(object, "bndbox")        xminn = etree.SubElement(bndbox, "xmin")        xminn.text = str(x0)        yminn = etree.SubElement(bndbox, "ymin")        yminn.text = str(y0)        xmaxn = etree.SubElement(bndbox, "xmax")        xmaxn.text = str(x1)        ymaxn = etree.SubElement(bndbox, "ymax")        ymaxn.text = str(y1)  #定义生成xml的方法def voc_opencv_xml(a,b,c,d,e,f,boxes,Label,Label_a,save="1.xml"):    json_info = {}    json_info["pic_dirname"] = a    json_info["pic_path"] = b    json_info["filename"] = c    anno = Gen_Annotations(json_info)     anno.set_size(d, e, f)     for box in range(len(boxes)):        x,y,w,h = [int(v) for v in boxes[box]]        anno.add_pic_attr(Label[Label_a[box]],x,y,x+w,y+h)    anno.savefile(save)  if __name__ == '__main__':    Label_a = []    contents = os.path.split(imgpath)[1]    trackers = cv2.MultiTracker_create()    while True:        Filename_jpg = str(time.time()).split(".")[0] + "_" + str(time.time()).split(".")[1] + ".jpg"        Filename_xml = str(time.time()).split(".")[0] + "_" + str(time.time()).split(".")[1] + ".xml"         path_Filename_jpg = os.path.join(imgpath,Filename_jpg)        path_Filename_xml = os.path.join(xmlpath,Filename_xml)         ret,frame = Vs.read()        if not ret:            break         success,boxes = trackers.update(frame)        if len(boxes)>0:            cv2.imwrite(path_Filename_jpg, frame)            judge = True        else:            judge = False          if success==False:            print("目标丢失")            trackers = cv2.MultiTracker_create()            Label_a = []            judge = False        if judge:            voc_opencv_xml(contents,Filename_jpg,path_Filename_jpg,frame.shape[1],frame.shape[0],frame.shape[2],boxes,Label,Label_a,path_Filename_xml)        if judge:            for box in range(len(boxes)):                x,y,w,h = [int(v) for v in boxes[box]]                cv2.putText(frame, Label[Label_a[box]], (x, y), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 255, 255), 1)                cv2.rectangle(frame,(x,y),(x+w,y+h),(255,0,0),2)          cv2.imshow('frame',frame)         var = cv2.waitKey(30)         if var == ord('s'):            imgzi = cv2.putText(frame, str(Label), (50, 50), cv2.FONT_HERSHEY_TRIPLEX, 1, (0, 255, 0), 2)            cv2.imshow('frame', frame)            var = cv2.waitKey(0)            if var-48<len(Label) or var-48<=len(Label):                Label_a.append(int(var-48))            box = cv2.selectROI("frame", frame, fromCenter=False,showCrosshair=True)            tracker = cv2.TrackerCSRT_create()            trackers.add(tracker,frame,box)        elif var == ord("r"):            trackers = cv2.MultiTracker_create()            Label_a = []        elif var == ord('q'): #退出            break     Vs.release()    cv2.destroyAllWindows()