@@ -272,6 +272,7 @@ def preprocess_single(self,
272272 ),
273273 dtype = np .float32 )
274274 data_info ['lifting_target' ] = np .zeros ((1 , K , 3 ), dtype = np .float32 )
275+ data_info ['factor' ] = np .zeros ((T , ), dtype = np .float32 )
275276 data_info ['lifting_target_visible' ] = np .ones ((1 , K , 1 ),
276277 dtype = np .float32 )
277278 data_info ['camera_param' ] = dict (w = width , h = height )
@@ -299,7 +300,6 @@ def forward(self,
299300 list: A list of data samples, each containing the model's output
300301 results.
301302 """
302-
303303 pose_lift_results = self .model .test_step (inputs )
304304
305305 # Post-processing of pose estimation results
@@ -309,8 +309,16 @@ def forward(self,
309309 pose_lift_res .track_id = pose_est_results_converted [idx ].get (
310310 'track_id' , 1e4 )
311311
312- # Invert x and z values of the keypoints
312+ # align the shape of output keypoints coordinates and scores
313313 keypoints = pose_lift_res .pred_instances .keypoints
314+ keypoint_scores = pose_lift_res .pred_instances .keypoint_scores
315+ if keypoint_scores .ndim == 3 :
316+ pose_lift_results [idx ].pred_instances .keypoint_scores = \
317+ np .squeeze (keypoint_scores , axis = 1 )
318+ if keypoints .ndim == 4 :
319+ keypoints = np .squeeze (keypoints , axis = 1 )
320+
321+ # Invert x and z values of the keypoints
314322 keypoints = keypoints [..., [0 , 2 , 1 ]]
315323 keypoints [..., 0 ] = - keypoints [..., 0 ]
316324 keypoints [..., 2 ] = - keypoints [..., 2 ]
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