add api endpoint

app.py

@@ -16,7 +16,10 @@ from trellis.representations import Gaussian, MeshExtractResult
 from trellis.utils import render_utils, postprocessing_utils
 
 import logging
-
+from fastapi import FastAPI, File, UploadFile
+from fastapi.responses import JSONResponse, FileResponse
+import io
+import base64
 # Configure logging
 logging.basicConfig(
     level=logging.INFO,
@@ -264,6 +267,67 @@ with gr.Blocks() as demo:
     )
     
 
+# Access FastAPI app from Gradio
+app = gr.routes.App.get_app()
+
+@app.post("/api/image_to_glb")
+async def process_image_endpoint(
+    image: UploadFile = File(...),
+    seed: int = 0,
+    randomize_seed: bool = True,
+    ss_guidance_strength: float = 7.5,
+    ss_sampling_steps: int = 12,
+    slat_guidance_strength: float = 3.0,
+    slat_sampling_steps: int = 12
+):
+    """
+    API Endpoint to process an image and return a GLB file.
+
+    Args:
+        image (UploadFile): The image file.
+        seed (int): Seed for generation.
+        randomize_seed (bool): Whether to randomize the seed.
+        ss_guidance_strength (float): Guidance strength for stage 1.
+        ss_sampling_steps (int): Sampling steps for stage 1.
+        slat_guidance_strength (float): Guidance strength for stage 2.
+        slat_sampling_steps (int): Sampling steps for stage 2.
+
+    Returns:
+        FileResponse: The generated GLB file as a downloadable attachment.
+    """
+    try:
+        # Read and preprocess the image
+        contents = await image.read()
+        pil_image = Image.open(io.BytesIO(contents)).convert("RGBA")
+        trial_id, processed_image = preprocess_image(pil_image)
+        
+        # Generate 3D asset
+        state, video_path = image_to_3d(
+            trial_id, seed, randomize_seed,
+            ss_guidance_strength, ss_sampling_steps,
+            slat_guidance_strength, slat_sampling_steps
+        )
+        
+        # Extract GLB
+        glb_path, _ = extract_glb(state, mesh_simplify=0.95, texture_size=1024)  # You can parametrize these
+        
+        # Ensure the GLB file exists
+        if not os.path.exists(glb_path):
+            logger.error(f"GLB file not found at path: {glb_path}")
+            return JSONResponse(status_code=500, content={"error": "GLB file generation failed."})
+        
+        # Return the GLB file as a downloadable response
+        return FileResponse(
+            path=glb_path,
+            media_type='model/gltf-binary',
+            filename=f"{trial_id}.glb"
+        )
+    
+    except Exception as e:
+        logger.error(f"Error in API endpoint: {e}")
+        return JSONResponse(status_code=500, content={"error": str(e)})
+
+
 # Launch the Gradio app
 if __name__ == "__main__":
     pipeline = TrellisImageTo3DPipeline.from_pretrained("JeffreyXiang/TRELLIS-image-large")