Update app.py

app.py

@@ -31,7 +31,6 @@ def preprocess_image(image):
     image = pipeline.preprocess_image(image, resolution=1024)
     return image
 
-@spaces.GPU
 def generate_3d(image, seed=-1,  
                 ss_guidance_strength=3, ss_sampling_steps=50,
                 slat_guidance_strength=3, slat_sampling_steps=6,):
@@ -70,11 +69,9 @@ def generate_3d(image, seed=-1,
     def combine_diagonal(color_np, normal_np):
         # Convert images to numpy arrays
         h, w, c = color_np.shape
-        # Create a boolean mask that is True for pixels where x > y (diagonally)
         mask = np.fromfunction(lambda y, x: x > y, (h, w))
         mask = mask.astype(bool)
         mask = np.stack([mask] * c, axis=-1)
-        # Where mask is True take color, else normal
         combined_np = np.where(mask, color_np, normal_np)
         return Image.fromarray(combined_np)
 
@@ -82,7 +79,6 @@ def generate_3d(image, seed=-1,
     
     # Export mesh
     trimesh_mesh = generated_mesh.to_trimesh(transform_pose=True)
-
     trimesh_mesh.export(mesh_path)
 
     return preview_images, normal_image, mesh_path, mesh_path
@@ -92,17 +88,15 @@ def convert_mesh(mesh_path, export_format):
     if not mesh_path:
         return None
     
-    # Create a temporary file to store the mesh data
     temp_file = tempfile.NamedTemporaryFile(suffix=f".{export_format}", delete=False)
     temp_file_path = temp_file.name
     
     new_mesh_path = mesh_path.replace(".glb", f".{export_format}")
     mesh = trimesh.load_mesh(mesh_path)
-    mesh.export(temp_file_path)  # Export to the temporary file
+    mesh.export(temp_file_path)
     
-    return temp_file_path # Return the path to the temporary file
+    return temp_file_path
 
-# Create the Gradio interface with improved layout
 with gr.Blocks(css="footer {visibility: hidden}") as demo:
     gr.Markdown(
         """
@@ -118,17 +112,17 @@ with gr.Blocks(css="footer {visibility: hidden}") as demo:
     with gr.Row():
         gr.Markdown("""
                     <p align="center">
-                    <a title="Website" href="https://stable-x.github.io/Hi3DGen/" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+                    <a title="Website" href="https://stable-x.github.io/Hi3DGen/" target="_blank">
                         <img src="https://www.obukhov.ai/img/badges/badge-website.svg">
                     </a>
-                    <a title="arXiv" href="https://stable-x.github.io/Hi3DGen/hi3dgen_paper.pdf" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+                    <a title="arXiv" href="https://stable-x.github.io/Hi3DGen/hi3dgen_paper.pdf" target="_blank">
                         <img src="https://www.obukhov.ai/img/badges/badge-pdf.svg">
                     </a>
-                    <a title="Github" href="https://github.com/Stable-X/Hi3DGen" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
-                        <img src="https://img.shields.io/github/stars/Stable-X/Hi3DGen?label=GitHub%20%E2%98%85&logo=github&color=C8C" alt="badge-github-stars">
+                    <a title="Github" href="https://github.com/Stable-X/Hi3DGen" target="_blank">
+                        <img src="https://img.shields.io/github/stars/Stable-X/Hi3DGen?label=GitHub%20%E2%98%85&logo=github&color=C8C">
                     </a>
-                    <a title="Social" href="https://x.com/ychngji6" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
-                        <img src="https://www.obukhov.ai/img/badges/badge-social.svg" alt="social">
+                    <a title="Social" href="https://x.com/ychngji6" target="_blank">
+                        <img src="https://www.obukhov.ai/img/badges/badge-social.svg">
                     </a>
                     </p>
                     """)
@@ -136,7 +130,6 @@ with gr.Blocks(css="footer {visibility: hidden}") as demo:
     with gr.Row():
         with gr.Column(scale=1):
             with gr.Tabs():
-                
                 with gr.Tab("Single Image"):
                     with gr.Row():
                         image_prompt = gr.Image(label="Image Prompt", image_mode="RGBA", type="pil")
@@ -160,11 +153,10 @@ with gr.Blocks(css="footer {visibility: hidden}") as demo:
                 with gr.Row():
                     gen_shape_btn = gr.Button("Generate Shape", size="lg", variant="primary")
                         
-        # Right column - Output
         with gr.Column(scale=1):
             with gr.Tabs():
                 with gr.Tab("Preview"):
-                    output_gallery = gr.Gallery(label="Examples", columns=4, rows=2, object_fit="contain", height="auto",show_label=False)
+                    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 = gr.Model3D(label="3D Model Preview (Each model is approximately 40MB, may take around 1 minute to load)")
@@ -194,8 +186,7 @@ with gr.Blocks(css="footer {visibility: hidden}") as demo:
         lambda: gr.Button(interactive=True),
         outputs=[download_btn],
     )
-    
-    
+
     def update_download_button(mesh_path, export_format):
         if not mesh_path:
             return gr.File.update(value=None, interactive=False)
@@ -223,20 +214,16 @@ with gr.Blocks(css="footer {visibility: hidden}") as demo:
     gr.Markdown(
         """
         **Acknowledgments**: Hi3DGen is built on the shoulders of giants. We would like to express our gratitude to the open-source research community and the developers of these pioneering projects:
-        - **3D Modeling:** Our 3D Model is finetuned from the SOTA open-source 3D foundation model [Trellis](https://github.com/microsoft/TRELLIS) and we draw inspiration from the teams behind [Rodin](https://hyperhuman.deemos.com/rodin), [Tripo](https://www.tripo3d.ai/app/home), and [Dora](https://github.com/Seed3D/Dora).
-        - **Normal Estimation:** Our Normal Estimation Model builds on the leading normal estimation research such as [StableNormal](https://github.com/hugoycj/StableNormal) and [GenPercept](https://github.com/aim-uofa/GenPercept).
-        
-        **Your contributions and collaboration push the boundaries of 3D modeling!**
+        - **3D Modeling:** Our 3D Model is finetuned from the SOTA open-source 3D foundation model [Trellis](https://github.com/microsoft/TRELLIS)
+        - **Normal Estimation:** We build on top of [StableNormal](https://github.com/hugoycj/StableNormal)
         """
     )
 
 if __name__ == "__main__":
-    # Initialize pipeline
+    # 初始化 pipeline，使用 CPU
     pipeline = TrellisImageTo3DPipeline.from_pretrained("Stable-X/trellis-normal-v0-1")
-    pipeline.cuda()
-
-    # Initialize normal predictor
+    
+    # 加载 StableNormal 模型（会自动选择 CPU）
     normal_predictor = torch.hub.load("hugoycj/StableNormal", "StableNormal_turbo", trust_repo=True, yoso_version='yoso-normal-v1-8-1')
     
-    # Launch the app
     demo.launch()