Method __call__

util/formatting.py:204–281

Call function to transform and format common fields in results. Args: results (dict): Result dict contains the data to convert. Returns: dict: The result dict contains the data that is formatted with \ default bundle.

(self, results)

        self.pad_val = pad_val

    def __call__(self, results):
        """Call function to transform and format common fields in results.

        Args:
            results (dict): Result dict contains the data to convert.

        Returns:
            dict: The result dict contains the data that is formatted with \
                default bundle.
        """
        data_keys = [
            'joint_img',  # keypoints2d
            'smplx_joint_img',  #smplx_joint_img, # projected smplx if valid cam_param, else same as keypoints2d
            'joint_cam',  # joint_cam actually not used in any loss, # raw kps3d probably without ra
            'smplx_joint_cam',  # kps3d with body, face, hand ra
            'smplx_pose',
            'smplx_shape',
            'smplx_expr',
            'lhand_bbox_center',
            'lhand_bbox_size',
            'rhand_bbox_center',
            'rhand_bbox_size',
            'face_bbox_center',
            'face_bbox_size',
            'body_bbox_center',
            'body_bbox_size',
            'joint_valid',
            'joint_trunc',
            'smplx_joint_valid',
            'smplx_joint_trunc',
            'smplx_pose_valid',
            'smplx_shape_valid',
            'smplx_expr_valid',
            'is_3D',
            'lhand_bbox_valid',
            'rhand_bbox_valid',
            'face_bbox_valid',
            'body_bbox_valid',
            'body_bbox',
            'lhand_bbox',
            'rhand_bbox',
            'face_bbox',
            'gender',
            'bb2img_trans',
            'img2bb_trans',
            'ann_idx'
        ]
        if 'img' in results:
            img = results['img']
            if self.img_to_float is True and img.dtype == np.uint8:
                # Normally, image is of uint8 type without normalization.
                # At this time, it needs to be forced to be converted to
                # flot32, otherwise the model training and inference
                # will be wrong. Only used for YOLOX currently .
                img = img.astype(np.float32)
            # add default meta keys
            results = self._add_default_meta_keys(results)
            if len(img.shape) < 3: