use unregistered input

data/dataset.py

@@ -104,7 +104,7 @@ class Dataset(Dataset):
         else:
             view = torch.eye(3, device=self.device)
 
-        combined = torch.concat((body, mesh_posed[mesh_mask, :]))
+        combined = torch.concat((body, mesh_posed))
         # combined_no_trans = torch.concat((body_no_trans, mesh_posed_no_trans[mesh_mask, :]))
         combined_faces = torch.Tensor(np.concatenate((body_faces, faces + body.shape[0]))).to(self.device)
 

data/preprocess.py

@@ -30,12 +30,11 @@ def generate_frames_file(folder, file_name):
         garment_dir = os.path.join(folder, id)
         if not os.path.isdir(garment_dir):
             continue
-        garments = [f.replace('_registered.pc16','') for f in os.listdir(garment_dir) if f.endswith('_registered.pc16') and not f.startswith('Combined')]
-        assert len(garments) == 1
-        garment = garments[0]
-        verts = readPC2(os.path.join(garment_dir, garment + '_registered.pc16'), True)['V']
-        for i in range(verts.shape[0]):
-            frames.append(Frame(id, i, garment))
+        garments = [f.replace('.obj','') for f in os.listdir(garment_dir) if f.endswith('.obj')]
+        info = loadInfo(os.path.join(garment_dir, 'info'))
+        garments_str = ' '.join(garments)
+        for i in range(info['poses'].shape[1]):
+            frames.append(Frame(id, i, garments_str))
 
     with open(os.path.join(folder, file_name), 'w') as f:
         for i, frame in enumerate(frames):