Update app.py

app.py

@@ -74,7 +74,6 @@ class GenerateRequest(BaseModel):
     simplify: bool = True
     target_face_num: int = DEFAULT_FACE_NUMBER
 
-# Existing Gradio header (unchanged)
 HEADER = """
 # 🌌 PolyGenixAI: Craft 3D Worlds with Cosmic Precision
 ## Unleash Infinite Creativity with AI-Powered 3D Generation by AnvilInteractive Solutions
@@ -158,7 +157,7 @@ HEADER = """
 </style>
 """
 
-# TripoSG and MV-Adapter setup (unchanged)
+# triposg
 from image_process import prepare_image
 from briarmbg import BriaRMBG
 snapshot_download("briaai/RMBG-1.4", local_dir=RMBG_PRETRAINED_MODEL)
@@ -168,6 +167,7 @@ from triposg.pipelines.pipeline_triposg import TripoSGPipeline
 snapshot_download("VAST-AI/TripoSG", local_dir=TRIPOSG_PRETRAINED_MODEL)
 triposg_pipe = TripoSGPipeline.from_pretrained(TRIPOSG_PRETRAINED_MODEL).to(DEVICE, DTYPE)
 
+# mv adapter
 NUM_VIEWS = 6
 from inference_ig2mv_sdxl import prepare_pipeline, preprocess_image, remove_bg
 from mvadapter.utils import get_orthogonal_camera, tensor_to_image, make_image_grid
@@ -197,7 +197,7 @@ transform_image = transforms.Compose(
 remove_bg_fn = lambda x: remove_bg(x, birefnet, transform_image, DEVICE)
 
 if not os.path.exists("checkpoints/RealESRGAN_x2plus.pth"):
-    hf_hub_download("dtarnow/UPscaler", filename="Real FeatherESRGAN_x2plus.pth", local_dir="checkpoints")
+    hf_hub_download("dtarnow/UPscaler", filename="RealESRGAN_x2plus.pth", local_dir="checkpoints")
 if not os.path.exists("checkpoints/big-lama.pt"):
     subprocess.run("wget -P checkpoints/ https://github.com/Sanster/models/releases/download/add_big_lama/big-lama.pt", shell=True, check=True)
 
@@ -253,6 +253,7 @@ def run_full(image: str, req: gr.Request):
     torch.cuda.empty_cache()
 
     height, width = 768, 768
+    # Prepare cameras
     cameras = get_orthogonal_camera(
         elevation_deg=[0, 0, 0, 0, 89.99, -89.99],
         distance=[1.8] * NUM_VIEWS,
@@ -336,6 +337,31 @@ def run_full(image: str, req: gr.Request):
 
     return image_seg, mesh_path, textured_glb_path
 
+# FastAPI endpoint for generating 3D models
+@app.post("/api/generate")
+async def generate_3d_model(request: GenerateRequest, image: UploadFile = File(...), api_key: str = Depends(verify_api_key)):
+    try:
+        # Save uploaded image to temporary directory
+        session_hash = get_random_hex()
+        save_dir = os.path.join(TMP_DIR, session_hash)
+        os.makedirs(save_dir, exist_ok=True)
+        image_path = os.path.join(save_dir, f"input_{get_random_hex()}.png")
+        with open(image_path, "wb") as f:
+            f.write(await image.read())
+
+        # Run the full pipeline
+        image_seg, mesh_path, textured_glb_path = run_full(image_path, req=None)
+
+        # Return the file URL for the textured GLB
+        file_url = f"/files/{session_hash}/{os.path.basename(textured_glb_path)}"
+        return {"file_url": file_url}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+    finally:
+        # Clean up temporary directory
+        if os.path.exists(save_dir):
+            shutil.rmtree(save_dir)
+
 @spaces.GPU()
 @torch.no_grad()
 def run_segmentation(image: str):
@@ -380,6 +406,7 @@ def image_to_3d(
 @torch.no_grad()
 def run_texture(image: Image, mesh_path: str, seed: int, req: gr.Request):
     height, width = 768, 768
+    # Prepare cameras
     cameras = get_orthogonal_camera(
         elevation_deg=[0, 0, 0, 0, 89.99, -89.99],
         distance=[1.8] * NUM_VIEWS,
@@ -464,31 +491,6 @@ def run_texture(image: Image, mesh_path: str, seed: int, req: gr.Request):
 
     return textured_glb_path
 
-# FastAPI endpoint for generating 3D models
-@app.post("/api/generate")
-async def generate_3d_model(request: GenerateRequest, image: UploadFile = File(...), api_key: str = Depends(verify_api_key)):
-    try:
-        # Save uploaded image to temporary directory
-        session_hash = get_random_hex()
-        save_dir = os.path.join(TMP_DIR, session_hash)
-        os.makedirs(save_dir, exist_ok=True)
-        image_path = os.path.join(save_dir, f"input_{get_random_hex()}.png")
-        with open(image_path, "wb") as f:
-            f.write(await image.read())
-
-        # Run the full pipeline
-        image_seg, mesh_path, textured_glb_path = run_full(image_path, req=None)
-
-        # Return the file URL for the textured GLB
-        file_url = f"/files/{session_hash}/{os.path.basename(textured_glb_path)}"
-        return {"file_url": file_url}
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-    finally:
-        # Clean up temporary directory
-        if os.path.exists(save_dir):
-            shutil.rmtree(save_dir)
-
 # Gradio interface (unchanged)
 with gr.Blocks(title="PolyGenixAI", css="body { background-color: #1A1A1A; } .gr-panel { background-color: #2D2D2D; }") as demo:
     gr.Markdown(HEADER)