fix: Update app

app.py

@@ -42,8 +42,8 @@ def generate_3d(image, seed=-1,
         seed = np.random.randint(0, MAX_SEED)
     
     image = pipeline.preprocess_image(image, resolution=1024)
-    #normal_image = normal_predictor(image, resolution=768, match_input_resolution=True, data_type='object')
-    normal_image = image
+    normal_image = normal_predictor(image, resolution=768, match_input_resolution=True, data_type='object')
+
     outputs = pipeline.run(
         normal_image,
         seed=seed,
@@ -167,7 +167,7 @@ with gr.Blocks(css="footer {visibility: hidden}") as demo:
                     output_gallery = gr.Gallery(label="Examples", columns=4, rows=2, object_fit="contain", height="auto",show_label=False)
                 with gr.Tab("3D Model"):
                     with gr.Column():
-                        model_output = LitModel3D(label="3D Model Preview", exposure=10.0, height=300)
+                        model_output = gr.Model3D(label="3D Model Preview", height=300)
                     with gr.Column():
                         export_format = gr.Dropdown(
                             choices=["obj", "glb", "ply", "stl"],
@@ -222,10 +222,11 @@ with gr.Blocks(css="footer {visibility: hidden}") as demo:
 
 if __name__ == "__main__":
     # Initialize pipeline
-    pipeline = TrellisImageTo3DPipeline.from_pretrained("JeffreyXiang/TRELLIS-image-large")
-    
+    pipeline = TrellisImageTo3DPipeline.from_pretrained("Stable-X/trellis-normal-v0-1")
+    pipeline.cuda()
+
     # Initialize normal predictor
-    # normal_predictor = torch.hub.load("hugoycj/StableNormal", "StableNormal_turbo", trust_repo=True, yoso_version='yoso-normal-v1-8-1')
+    normal_predictor = torch.hub.load("hugoycj/StableNormal", "StableNormal_turbo", trust_repo=True, yoso_version='yoso-normal-v1-8-1')
     
     # Launch the app
     demo.launch()