def filter_gt_box_outside_range_by_center(gt_boxes, limit_range):
"""remove gtbox outside training range.
this function should be applied after other prep functions
Args:
gt_boxes ([type]): [description]
limit_range ([type]): [description]
"""
gt_box_centers = gt_boxes[:, :2]
bounding_box = box_np_ops.minmax_to_corner_2d(
np.asarray(limit_range)[np.newaxis, ...])
ret = points_in_convex_polygon_jit(gt_box_centers, bounding_box)
return ret.reshape(-1)
def filter_gt_box_outside_range(gt_boxes, limit_range):
"""remove gtbox outside training range.
this function should be applied after other prep functions
Args:
gt_boxes ([type]): [description]
limit_range ([type]): [description]
"""
gt_boxes_bv = box_np_ops.center_to_corner_box2d(
gt_boxes[:, [0, 1]], gt_boxes[:, [3, 3 + 1]], gt_boxes[:, 6])
bounding_box = box_np_ops.minmax_to_corner_2d(
np.asarray(limit_range)[np.newaxis, ...])
ret = points_in_convex_polygon_jit(
gt_boxes_bv.reshape(-1, 2), bounding_box)
return np.any(ret.reshape(-1, 4), axis=1)
ret[i, j] = True # collision.
return ret
def global_translate_(gt_boxes, points, noise_translate_std):
"""
Apply global translation to gt_boxes and points.
"""
if not isinstance(noise_translate_std, (list, tuple, np.ndarray)):
noise_translate_std = np.array(
[noise_translate_std, noise_translate_std, noise_translate_std])
if all([e == 0 for e in noise_translate_std]):
return gt_boxes, points
noise_translate = np.array([
np.random.normal(0, noise_translate_std[0], 1),
np.random.normal(0, noise_translate_std[1], 1),
np.random.normal(0, noise_translate_std[0], 1)
]).T
points[:, :3] += noise_translate
gt_boxes[:, :3] += noise_translate
if __name__ == "__main__":
bboxes = np.array([[0.0, 0.0, 0.5, 0.5], [0.2, 0.2, 0.6, 0.6],
[0.7, 0.7, 0.9, 0.9], [0.55, 0.55, 0.8, 0.8]])
bbox_corners = box_np_ops.minmax_to_corner_2d(bboxes)
print(bbox_corners.shape)
print(box_collision_test(bbox_corners, bbox_corners))
