Update app.py

app.py

@@ -150,12 +150,12 @@ pipeline = pipeline.to(device)
 # load reconstruction model
 print('Loading reconstruction model ...')
 model_ckpt_path = hf_hub_download(repo_id="TencentARC/InstantMesh", filename="instant_mesh_large.ckpt", repo_type="model")
-model = instantiate_from_config(model_config)
+model0 = instantiate_from_config(model_config)
 state_dict = torch.load(model_ckpt_path, map_location='cpu')['state_dict']
 state_dict = {k[14:]: v for k, v in state_dict.items() if k.startswith('lrm_generator.') and 'source_camera' not in k}
-model.load_state_dict(state_dict, strict=True)
+model0.load_state_dict(state_dict, strict=True)
 
-model = model.to(device)
+model0 = model0.to(device)
 
 print('Loading Finished!')
 
@@ -199,10 +199,10 @@ def generate_mvs(input_image, sample_steps, sample_seed):
 # @spaces.GPU
 def make3d(images):
 
-    global model
+    global model0
     if IS_FLEXICUBES:
-        model.init_flexicubes_geometry(device, use_renderer=False)
-    model = model.eval()
+        model0.init_flexicubes_geometry(device, use_renderer=False)
+    model0 = model0.eval()
 
     images = np.asarray(images, dtype=np.float32) / 255.0
     images = torch.from_numpy(images).permute(2, 0, 1).contiguous().float()     # (3, 960, 640)
@@ -223,7 +223,7 @@ def make3d(images):
 
     with torch.no_grad():
         # get triplane
-        planes = model.forward_planes(images, input_cameras)
+        planes = model0.forward_planes(images, input_cameras)
 
         # # get video
         # chunk_size = 20 if IS_FLEXICUBES else 1
@@ -255,7 +255,7 @@ def make3d(images):
         # print(f"Video saved to {video_fpath}")
 
         # get mesh
-        mesh_out = model.extract_mesh(
+        mesh_out = model0.extract_mesh(
             planes,
             use_texture_map=False,
             **infer_config,