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img_info_depth = []

vid = cv2.VideoWriter('projection.mp4', fourcc, 10.0, (width, height))

for (boxes, class_names, image_path), velo_path in \
  zip(return_predictions(images_paths, model), velo_paths):
  velo_points = load_from_bin(velo_path)

  ans, c_, depth = velo3d_2_camera2d_points(velo_points, v_fov=(-24.9, 2.0), h_fov=(-45,45), \
                               vc_path=v2c_filepath, cc_path=c2c_filepath, mode=mode)

  frame = cv2.imread(image_path)
  annotator = Annotator(frame)
  
  avg_depths = np.array([])
  for box in boxes:
    xyxy = box.xyxy[0].cpu().numpy()
    # # top left
    # xmin = xyxy[0]
    # ymin = xyxy[1]
    # # bottom right
    # xmin = xyxy[2]
    # ymin = xyxy[3]
    avg_depth = get_avg_depth(xyxy, ans, depth)
    avg_depths = np.append(avg_depths, avg_depth)

    avg_depth_int = int(avg_depth) if not np.isnan(avg_depth) else 0
    # {model.names[int(box.cls)]} 
    annotator_text = f'est_depth={int(avg_depth_int)}'

    annotator.box_label(box.xyxy[0], annotator_text)
  
  frame = annotator.result()
  cv2_imshow(frame)
  vid.write(img)
vid.release()


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