yolov9直接调用zed相机实现三维测距(python)

04-11 1489阅读

yolov9直接调用zed相机实现三维测距(python)

  • 1. 相关配置
  • 2. 相关代码
    • 2.1 相机设置
    • 2.2 测距模块
    • 2.2 实验结果

      相关链接

      此项目直接调用zed相机实现三维测距,无需标定,相关内容如下:

      1. yolov4直接调用zed相机实现三维测距

      2.yolov5直接调用zed相机实现三维测距(python)

      3. yolov8直接调用zed相机实现三维测距(python)

      4.具体实现效果已在哔哩哔哩发布,点击此链接跳转

      本篇博文工程源码下载(麻烦github给个星星)

      下载链接:https://github.com/up-up-up-up/zed-yolov9

      附:Zed调用YOLOv7测距也已经实现,但是3060笔记本6G显存带不动,在大现存服务器上可以运行,可能是由于YOLOv7网络结构导致的,由于不具备普适性,就不再写相关文章了,有需要的可以仿照这个代码去改写

      1. 相关配置

      python==3.7

      Windows-pycharm

      zed api 具体配置见 (zed api 配置步骤)

      2. 相关代码

      2.1 相机设置

      zed = sl.Camera()
      input_type = sl.InputType()
       if opt.svo is not None:
           input_type.set_from_svo_file(opt.svo)
       # Create a InitParameters object and set configuration parameters
       init_params = sl.InitParameters(input_t=input_type, svo_real_time_mode=True)
       init_params.camera_resolution = sl.RESOLUTION.HD720
       init_params.coordinate_units = sl.UNIT.METER
       init_params.depth_mode = sl.DEPTH_MODE.ULTRA  # QUALITY
       init_params.coordinate_system = sl.COORDINATE_SYSTEM.RIGHT_HANDED_Y_UP
       init_params.depth_maximum_distance = 5
       runtime_params = sl.RuntimeParameters()
       status = zed.open(init_params)
      

      2.2 测距模块

      for *xyxy, conf, cls in reversed(det):
           xywh = (xyxy2xywh(torch.tensor(xyxy).view(1, 4)) / gn).view(-1).tolist()  # normalized xywh
           cent_x = round(xywh[0] * im0.shape[1])
           cent_y = round(xywh[1] * im0.shape[0])
           cent_w = round(xywh[2] * im0.shape[1])
           point_1 = round(cent_x - 0.4 * cent_w)
           point_2 = round(cent_x + 0.4 * cent_w)
           wide_value_1 = point_cloud.get_value(point_1, cent_y)[1]
           wide_value_2 = point_cloud.get_value(point_2, cent_y)[1]
           try:
               wide = round(wide_value_1[0], 4) - round(wide_value_2[0], 4)
               wide = round(abs(wide * 1000))
           except:
               wide = 0.00
               pass
           point_cloud_value = point_cloud.get_value(cent_x, cent_y)[1]
           point_cloud_value = point_cloud_value * -1000.00
           if point_cloud_value[2] > 0.00:
               try:
                   point_cloud_value[0] = round(point_cloud_value[0])
                   point_cloud_value[1] = round(point_cloud_value[1])
                   point_cloud_value[2] = round(point_cloud_value[2])
                   print("x:", point_cloud_value[0], "y:", point_cloud_value[1], "z:",
                         point_cloud_value[2], "W:", wide)
                   txt = 'x:{0} y:{1} z:{2} w:{3}'.format(point_cloud_value[0], point_cloud_value[1],
           point_cloud_value[2], wide)
                   a=point_cloud_value[0]
                   b=point_cloud_value[1]
                   c=point_cloud_value[2]
                   distance = ((a ** 2 + b ** 2 + c ** 2) ** 0.5)
                   # annotator.box_label(xyxy, txt, color=(255, 0, 0))
                   label = f'{names[int(cls)]} {conf:.2f} '
                   label = label + " " +"dis:" +str(distance)
                   annotator.box_label(xyxy, label, color=colors(c, True))
               except:
                   pass
      

      2.2 实验结果

      测距功能

      yolov9直接调用zed相机实现三维测距(python)

      视频展示

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