87d7376cf534ee003846621bcf5f12bee241f2ab,poem/core/keypoint_utils.py,,randomly_rotate_and_project_3d_to_2d,#Any#Any#Any#Any#Any#Any#Any#,596

Before Change

      [-1.0, 0.0, 0.0],
      [0.0, 1.0, 0.0],
  ])
  default_center = tf.constant([0.0, 0.0, default_camera_z])
  operator = tf.linalg.LinearOperatorFullMatrix(default_rotation_to_camera)
  keypoints_3d = operator.matvec(keypoints_3d) + default_center

  // Project to 2D.

After Change

  if sequential_inputs:
    // Currently we only support sequence-level const depth.
    // TODO(liuti): Support varying depth for a sequence.
    normalized_camera_depths = tf.random.uniform(
        tf.shape(keypoints_3d)[:-3],
        minval=normalized_camera_depth_range[0],
        maxval=normalized_camera_depth_range[1],
        seed=seed)
    normalized_camera_depths = data_utils.recursively_expand_dims(
        normalized_camera_depths, axes=[-1, -1])
  else:
    normalized_camera_depths = tf.random.uniform(
        tf.shape(keypoints_3d)[:-2],
        minval=normalized_camera_depth_range[0],
        maxval=normalized_camera_depth_range[1],
        seed=seed)
    normalized_camera_depths = tf.expand_dims(normalized_camera_depths, axis=-1)

  default_centers = tf.stack([
      tf.zeros_like(normalized_camera_depths),
      tf.zeros_like(normalized_camera_depths),
      normalized_camera_depths,
  ],
                             axis=-1)
  keypoints_3d += default_centers

  // Project to 2D.
  return keypoints_3d[Ellipsis, :-1] / tf.math.maximum(1e-12, keypoints_3d[Ellipsis, -1:])

Instances