Update app.py

app.py

@@ -1,4 +1,7 @@
 import gradio as gr
+import spaces
+from gradio_litmodel3d import LitModel3D
+
 import os
 import shutil
 os.environ['SPCONV_ALGO'] = 'native'
@@ -12,7 +15,6 @@ from PIL import Image
 from trellis.pipelines import TrellisImageTo3DPipeline
 from trellis.representations import Gaussian, MeshExtractResult
 from trellis.utils import render_utils, postprocessing_utils
-from gradio_litmodel3d import LitModel3D
 
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -89,6 +91,7 @@ def get_seed(randomize_seed: bool, seed: int) -> int:
     """
     return np.random.randint(0, MAX_SEED) if randomize_seed else seed
 
+@spaces.GPU
 def image_to_3d(
     image: Image.Image,
     seed: int,
@@ -123,22 +126,23 @@ def image_to_3d(
     video_path = os.path.join(user_dir, f"{trial_id}.mp4")
     imageio.mimsave(video_path, video, fps=15)
     
-    # Generate full quality GLB
+    # Save full quality GLB
     glb = postprocessing_utils.to_glb(
         outputs['gaussian'][0], 
         outputs['mesh'][0],
         simplify=0.0,  # No simplification
         fill_holes=True,
         fill_holes_max_size=0.04,
-        texture_size=2048,  # Maximum texture resolution
+        texture_size=2048,  # Maximum texture size
         verbose=False
     )
     full_glb_path = os.path.join(user_dir, f"{trial_id}_full.glb")
     glb.export(full_glb_path)
     
     state = pack_state(outputs['gaussian'][0], outputs['mesh'][0], trial_id)
-    return state, video_path, full_glb_path
+    return state, video_path, model_output, full_glb_path
 
+@spaces.GPU
 def extract_glb(
     state: dict,
     mesh_simplify: float,
@@ -159,7 +163,8 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
     gr.Markdown("""
     ## Image to 3D Asset with [TRELLIS](https://trellis3d.github.io/)
     * Upload an image and click "Generate" to create a 3D asset. If the image has alpha channel, it be used as the mask. Otherwise, we use `rembg` to remove the background.
-    * If you find the generated 3D asset satisfactory, click "Extract GLB" to extract the GLB file and download it.
+    * The full-quality GLB will be available immediately after generation.
+    * If you need a reduced size version, use the GLB Extraction Settings below.
     """)
     
     with gr.Row():
@@ -226,7 +231,7 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
     ).then(
         image_to_3d,
         inputs=[image_prompt, seed, ss_guidance_strength, ss_sampling_steps, slat_guidance_strength, slat_sampling_steps],
-        outputs=[output_buf, video_output, download_full],
+        outputs=[output_buf, video_output, model_output, download_full],
     ).then(
         lambda: [gr.Button(interactive=True), gr.Button(interactive=True), gr.Button(interactive=False)],
         outputs=[download_full, extract_glb_btn, download_reduced],
@@ -245,7 +250,7 @@ if __name__ == "__main__":
     pipeline = TrellisImageTo3DPipeline.from_pretrained("JeffreyXiang/TRELLIS-image-large")
     pipeline.cuda()
     try:
-        pipeline.preprocess_image(Image.fromarray(np.zeros((512, 512, 3), dtype=np.uint8)))
+        pipeline.preprocess_image(Image.fromarray(np.zeros((512, 512, 3), dtype=np.uint8)))    # Preload rembg
     except:
         pass
     demo.launch()