Update app.py

app.py

@@ -1,7 +1,7 @@
 """
 SignMotionGPT - HuggingFace Spaces Demo
 Text-to-Sign Language Motion Generation
-
+Uses PyRender for high-quality avatar visualization
 """
 # IMPORTANT: Set OpenGL platform BEFORE any OpenGL imports (for headless rendering)
 import os
@@ -474,40 +474,34 @@ def params_to_vertices(params_seq: np.ndarray) -> tuple:
             # root_pose is separate as global_orient (3 dims)
             body_t = tensor_parts['body_pose']
             L_body = body_t.shape[1]
-            expected_body = num_body_joints * 3  # 21 * 3 = 63
+            expected_no_go = num_body_joints * 3
+            expected_with_go = (num_body_joints + 1) * 3
             
-            if L_body >= expected_body:
-                body_pose_only = body_t[:, :expected_body].contiguous()
+            if L_body == expected_with_go:
+                global_orient = body_t[:, :3].contiguous()
+                body_pose_only = body_t[:, 3:].contiguous()
+            elif L_body == expected_no_go:
+                global_orient = torch.zeros((B, 3), dtype=torch.float32, device=DEVICE)
+                body_pose_only = body_t
             else:
-                # Pad if needed
-                pad_len = expected_body - L_body
-                body_pose_only = F.pad(body_t, (0, pad_len))
+                if L_body > expected_no_go:
+                    global_orient = body_t[:, :3].contiguous()
+                    body_pose_only = body_t[:, 3:].contiguous()
+                else:
+                    body_pose_only = F.pad(body_t, (0, max(0, expected_no_go - L_body)))
+                    global_orient = torch.zeros((B, 3), dtype=torch.float32, device=DEVICE)
             
-            # Call SMPL-X with correct parameter mapping:
-            # - shape -> betas
-            # - root_pose -> global_orient
-            # - lhand_pose/rhand_pose -> left/right_hand_pose
-            # - jaw_pose -> jaw_pose (controls mouth/lower face!)
-            # - cam_trans -> transl
-            # - eye poses set to zero (not in our data format)
             out = smplx_model(
-                betas=tensor_parts['shape'],
-                global_orient=tensor_parts['root_pose'],
-                body_pose=body_pose_only,
-                left_hand_pose=tensor_parts['lhand_pose'],
-                right_hand_pose=tensor_parts['rhand_pose'],
-                expression=tensor_parts['expression'],
-                jaw_pose=tensor_parts['jaw_pose'],
-                leye_pose=torch.zeros((B, 3), dtype=torch.float32, device=DEVICE),
-                reye_pose=torch.zeros((B, 3), dtype=torch.float32, device=DEVICE),
-                transl=tensor_parts['cam_trans'],
-                return_verts=True
+                betas=tensor_parts['betas'], global_orient=global_orient, body_pose=body_pose_only,
+                left_hand_pose=tensor_parts['left_hand_pose'], right_hand_pose=tensor_parts['right_hand_pose'],
+                expression=tensor_parts['expression'], jaw_pose=tensor_parts['jaw_pose'],
+                leye_pose=tensor_parts['eye_pose'], reye_pose=tensor_parts['eye_pose'],
+                transl=tensor_parts['trans'], return_verts=True
             )
             all_verts.append(out.vertices.detach().cpu().numpy())
     
     return np.concatenate(all_verts, axis=0), smplx_model.faces.astype(np.int32)
 
-
 # =====================================================================
 # PyRender Visualization Functions
 # =====================================================================