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api.py

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+# Open Source Model Licensed under the Apache License Version 2.0
+# and Other Licenses of the Third-Party Components therein:
+# The below Model in this distribution may have been modified by THL A29 Limited
+# ("Tencent Modifications"). All Tencent Modifications are Copyright (C) 2024 THL A29 Limited.
+
+import os
+import torch
+from PIL import Image
+from fastapi import FastAPI, File, UploadFile, HTTPException
+from fastapi.responses import FileResponse
+from pydantic import BaseModel
+import io
+import tempfile
+
+from hy3dgen.rembg import BackgroundRemover
+from hy3dgen.shapegen import Hunyuan3DDiTFlowMatchingPipeline, FaceReducer, FloaterRemover, DegenerateFaceRemover
+from hy3dgen.text2image import HunyuanDiTPipeline
+
+app = FastAPI(title="Hunyuan3D-2 API")
+
+# Initialize models at startup
+rembg = BackgroundRemover()
+model_path = 'tencent/Hunyuan3D-2'  # Use Hugging Face model path
+t2i = HunyuanDiTPipeline('Tencent-Hunyuan--HunyuanDiT-v1.1-Diffusers-Distilled')
+i23d = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained(model_path)
+
+class TextToImageRequest(BaseModel):
+    prompt: str
+
+@app.post("/image-to-3d/")
+async def image_to_3d(file: UploadFile = File(...)):
+    """Convert an image to 3D model"""
+    try:
+        # Read and process image
+        content = await file.read()
+        image = Image.open(io.BytesIO(content))
+        image = image.resize((1024, 1024))
+        
+        if image.mode == 'RGB':
+            image = rembg(image)
+
+        # Generate mesh
+        mesh = i23d(image=image, num_inference_steps=30, mc_algo='mc',
+                   generator=torch.manual_seed(2025))[0]
+        mesh = FloaterRemover()(mesh)
+        mesh = DegenerateFaceRemover()(mesh)
+        mesh = FaceReducer()(mesh)
+        
+        # Save mesh to temporary file
+        with tempfile.NamedTemporaryFile(suffix='.glb', delete=False) as tmp:
+            mesh.export(tmp.name)
+            return FileResponse(tmp.name, media_type='model/gltf-binary', 
+                             filename='model.glb')
+            
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.post("/text-to-3d/")
+async def text_to_3d(request: TextToImageRequest):
+    """Convert text prompt to 3D model"""
+    try:
+        # Generate image from text
+        image = t2i(request.prompt)
+        image = rembg(image)
+        
+        # Generate mesh
+        mesh = i23d(image, num_inference_steps=30, mc_algo='mc')[0]
+        mesh = FloaterRemover()(mesh)
+        mesh = DegenerateFaceRemover()(mesh)
+        mesh = FaceReducer()(mesh)
+        
+        # Save mesh to temporary file
+        with tempfile.NamedTemporaryFile(suffix='.glb', delete=False) as tmp:
+            mesh.export(tmp.name)
+            return FileResponse(tmp.name, media_type='model/gltf-binary',
+                             filename='model.glb')
+            
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)