update data.py

utils/data.py

@@ -13,6 +13,7 @@ SELECTED_JOINTS = {
 }
 
 
+
 def pad(joints: np.ndarray, num_frames: int = 150) -> np.ndarray:
     '''
     Add padding to the joints.
@@ -161,21 +162,21 @@ def preprocess(
     '''
     inputs = extract_joints(source=source, keypoints_detector=keypoints_detector)
 
-    T = inputs.shape[1]
-    ori_data = inputs
-    for t in range(T - 1):
-        inputs[:, t, :, :] = ori_data[:, t + 1, :, :] - ori_data[:, t, :, :]
-    inputs[:, T - 1, :, :] = 0
+    # T = inputs.shape[1]
+    # ori_data = inputs
+    # for t in range(T - 1):
+    #     inputs[:, t, :, :] = ori_data[:, t + 1, :, :] - ori_data[:, t, :, :]
+    # inputs[:, T - 1, :, :] = 0
 
     if random_choose:
         inputs = random_sample_np(inputs, window_size)
     else:
         inputs = uniform_sample_np(inputs, window_size)
 
-    if normalization:
-        assert inputs.shape[0] == 3
-        inputs[0, :, :, :] = inputs[0, :, :, :] - inputs[0, :, 0, 0].mean(axis=0)
-        inputs[1, :, :, :] = inputs[1, :, :, :] - inputs[1, :, 0, 0].mean(axis=0)
+    # if normalization:
+    #     assert inputs.shape[0] == 3
+    #     inputs[0, :, :, :] = inputs[0, :, :, :] - inputs[0, :, 0, 0].mean(axis=0)
+    #     inputs[1, :, :, :] = inputs[1, :, :, :] - inputs[1, :, 0, 0].mean(axis=0)
 
     return inputs[np.newaxis, :].astype(np.float32)