$ git clone 追踪代码
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$ cd unbox_yolov5_deepsort_counting
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$ python3 -m venv venv
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$ source venv/bin/activate
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$ python -m pip install --upgrade pip
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$ pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 torchaudio===0.7.2 -f https://download.pytorch.org/whl/torch_stable.html
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安装软件包

$ pip install -r requirements.txt
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在 demo.py 文件中，设置要检测的视频文件路径，默认为 './video/test.mp4'

capture = cv2.VideoCapture(‘./video/test.mp4’)

运行程序

python count.py
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demo代码

detector = Detector()

    # 打开视频
    capture = cv2.VideoCapture(VIDEO_PATH)

    while True:
        # 读取每帧图片
        _, im = capture.read()
        if im is None:
            break

        # 缩小尺寸
        im = cv2.resize(im, (width//2, height//2))

        list_bboxs = []
        # 更新跟踪器
        output_image_frame, list_bboxs = objtracker.update(detector, im)
        # 输出图片
        output_image_frame = cv2.add(output_image_frame, color_polygons_image)

        if len(list_bboxs) > 0:
            # ----------------------判断撞线----------------------
            for item_bbox in list_bboxs:
                x1, y1, x2, y2, _, track_id = item_bbox
                # 撞线检测点，(x1，y1)，y方向偏移比例 0.0~1.0
                y1_offset = int(y1 + ((y2 - y1) * 0.6))
                # 撞线的点
                y = y1_offset
                x = x1
                if polygon_mask_blue_and_yellow[y, x] == 1:
                    # 如果撞 蓝polygon
                    if track_id not in list_overlapping_blue_polygon:
                        list_overlapping_blue_polygon.append(track_id)
                    # 判断 黄polygon list里是否有此 track_id
                    # 有此track_id，则认为是 UP (上行)方向
                    if track_id in list_overlapping_yellow_polygon:
                        # 上行+1
                        up_count += 1
                        print('up count:', up_count, ', up id:', list_overlapping_yellow_polygon)
                        # 删除 黄polygon list 中的此id
                        list_overlapping_yellow_polygon.remove(track_id)

                elif polygon_mask_blue_and_yellow[y, x] == 2:
                    # 如果撞 黄polygon
                    if track_id not in list_overlapping_yellow_polygon:
                        list_overlapping_yellow_polygon.append(track_id)
                    # 判断 蓝polygon list 里是否有此 track_id
                    # 有此 track_id，则 认为是 DOWN（下行）方向
                    if track_id in list_overlapping_blue_polygon:
                        # 下行+1
                        down_count += 1
                        print('down count:', down_count, ', down id:', list_overlapping_blue_polygon)
                        # 删除 蓝polygon list 中的此id
                        list_overlapping_blue_polygon.remove(track_id)
            # ----------------------清除无用id----------------------
            list_overlapping_all = list_overlapping_yellow_polygon + list_overlapping_blue_polygon
            for id1 in list_overlapping_all:
                is_found = False
                for _, _, _, _, _, bbox_id in list_bboxs:
                    if bbox_id == id1:
                        is_found = True
                if not is_found:
                    # 如果没找到，删除id
                    if id1 in list_overlapping_yellow_polygon:
                        list_overlapping_yellow_polygon.remove(id1)

                    if id1 in list_overlapping_blue_polygon:
                        list_overlapping_blue_polygon.remove(id1)
            list_overlapping_all.clear()
            # 清空list
            list_bboxs.clear()
        else:
            # 如果图像中没有任何的bbox，则清空list
            list_overlapping_blue_polygon.clear()
            list_overlapping_yellow_polygon.clear()
            
        # 输出计数信息
        text_draw = 'DOWN: ' + str(down_count) + \
                    ' , UP: ' + str(up_count)
        output_image_frame = cv2.putText(img=output_image_frame, text=text_draw,
                                         org=draw_text_postion,
                                         fontFace=font_draw_number,
                                         fontScale=0.75, color=(0, 0, 255), thickness=2)
        cv2.imshow('Counting Demo', output_image_frame)
        cv2.waitKey(1)

    capture.release()
    cv2.destroyAllWindows()

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结果展示

各种追踪 测距 姿态估计 目标检测 计数 测速功能已实现，欢迎交流！
更多项目详见主页！

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