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							112 lines
						
					
					
						
							3.5 KiB
						
					
					
				
			
		
		
	
	
							112 lines
						
					
					
						
							3.5 KiB
						
					
					
				import numpy as np
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from common.transformations.camera import eon_focal_length, \
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	vp_from_ke, \
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	get_view_frame_from_road_frame, \
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	FULL_FRAME_SIZE
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# segnet
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SEGNET_SIZE = (512, 384)
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segnet_frame_from_camera_frame = np.array([
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  [float(SEGNET_SIZE[0])/FULL_FRAME_SIZE[0],    0.,          ],
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  [     0.,          float(SEGNET_SIZE[1])/FULL_FRAME_SIZE[1]]])
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# model
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MODEL_INPUT_SIZE = (320, 160)
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MODEL_YUV_SIZE = (MODEL_INPUT_SIZE[0], MODEL_INPUT_SIZE[1] * 3 // 2)
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MODEL_CX = MODEL_INPUT_SIZE[0]/2.
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MODEL_CY = 21.
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model_zoom = 1.25
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model_height = 1.22
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# canonical model transform
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model_intrinsics = np.array(
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  [[ eon_focal_length / model_zoom,    0. ,  MODEL_CX],
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   [   0. ,  eon_focal_length / model_zoom,  MODEL_CY],
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   [   0. ,                            0. ,   1.]])
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# BIG model
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BIGMODEL_INPUT_SIZE = (864, 288)
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BIGMODEL_YUV_SIZE = (BIGMODEL_INPUT_SIZE[0], BIGMODEL_INPUT_SIZE[1] * 3 // 2)
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bigmodel_zoom = 1.
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bigmodel_intrinsics = np.array(
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  [[ eon_focal_length / bigmodel_zoom,    0. , 0.5 * BIGMODEL_INPUT_SIZE[0]],
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   [   0. ,  eon_focal_length / bigmodel_zoom,  0.2 * BIGMODEL_INPUT_SIZE[1]],
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   [   0. ,                            0. ,   1.]])
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bigmodel_border = np.array([
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    [0,0,1],
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    [BIGMODEL_INPUT_SIZE[0], 0, 1],
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    [BIGMODEL_INPUT_SIZE[0], BIGMODEL_INPUT_SIZE[1], 1],
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    [0, BIGMODEL_INPUT_SIZE[1], 1],
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])
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model_frame_from_road_frame = np.dot(model_intrinsics,
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  get_view_frame_from_road_frame(0, 0, 0, model_height))
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bigmodel_frame_from_road_frame = np.dot(bigmodel_intrinsics,
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  get_view_frame_from_road_frame(0, 0, 0, model_height))
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model_frame_from_bigmodel_frame = np.dot(model_intrinsics, np.linalg.inv(bigmodel_intrinsics))
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# 'camera from model camera'
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def get_model_height_transform(camera_frame_from_road_frame, height):
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  camera_frame_from_road_ground = np.dot(camera_frame_from_road_frame, np.array([
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      [1, 0, 0],
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      [0, 1, 0],
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      [0, 0, 0],
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      [0, 0, 1],
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  ]))
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  camera_frame_from_road_high = np.dot(camera_frame_from_road_frame, np.array([
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      [1, 0, 0],
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      [0, 1, 0],
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      [0, 0, height - model_height],
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      [0, 0, 1],
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  ]))
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  road_high_from_camera_frame = np.linalg.inv(camera_frame_from_road_high)
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  high_camera_from_low_camera = np.dot(camera_frame_from_road_ground, road_high_from_camera_frame)
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  return high_camera_from_low_camera
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# camera_frame_from_model_frame aka 'warp matrix'
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# was: calibration.h/CalibrationTransform
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def get_camera_frame_from_model_frame(camera_frame_from_road_frame, height):
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  vp = vp_from_ke(camera_frame_from_road_frame)
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  model_camera_from_model_frame = np.array([
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    [model_zoom,         0., vp[0] - MODEL_CX * model_zoom],
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    [        0., model_zoom, vp[1] - MODEL_CY * model_zoom],
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    [        0.,         0.,                            1.],
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  ])
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  # This function is super slow, so skip it if height is very close to canonical
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  # TODO: speed it up!
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  if abs(height - model_height) > 0.001: #
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    camera_from_model_camera = get_model_height_transform(camera_frame_from_road_frame, height)
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  else:
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    camera_from_model_camera = np.eye(3)
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  return np.dot(camera_from_model_camera, model_camera_from_model_frame)
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def get_camera_frame_from_bigmodel_frame(camera_frame_from_road_frame):
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  camera_frame_from_ground = camera_frame_from_road_frame[:, (0, 1, 3)]
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  bigmodel_frame_from_ground = bigmodel_frame_from_road_frame[:, (0, 1, 3)]
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  ground_from_bigmodel_frame = np.linalg.inv(bigmodel_frame_from_ground)
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  camera_frame_from_bigmodel_frame = np.dot(camera_frame_from_ground, ground_from_bigmodel_frame)
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  return camera_frame_from_bigmodel_frame
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