Update app.py

app.py

@@ -25,6 +25,9 @@ from transparent_background import Remover
 # rembg (U2Net + IS-Net via ONNX)
 from rembg import new_session, remove as rembg_remove
 
+# withoutBG (4-stage ONNX pipeline)
+from withoutbg import WithoutBG
+
 
 # ----------------------------
 # Utilities
@@ -101,6 +104,7 @@ class Timing:
 class ModelManager:
     def __init__(self):
         self._inspy: Optional[Remover] = None
+        self._withoutbg: Optional[object] = None
         self._torch_models: Dict[str, torch.nn.Module] = {}
         self._torch_model_on_gpu: Optional[str] = None
         self._rembg_sessions: Dict[str, object] = {}
@@ -126,6 +130,11 @@ class ModelManager:
             self._inspy = Remover(jit=False)
         return self._inspy
 
+    def _load_withoutbg(self):
+        if self._withoutbg is None:
+            self._withoutbg = WithoutBG.opensource()
+        return self._withoutbg
+
     def _offload_torch_models_from_gpu(self, keep_name: str):
         if get_device() != "cuda":
             return
@@ -264,6 +273,11 @@ class ModelManager:
             out = rembg_remove(img_rgb, session=sess)
             out = ensure_rgba(out)
 
+        elif model_name == "withoutBG":
+            model = self._load_withoutbg()
+            out = model.remove_background(img_rgb)
+            out = ensure_rgba(out)
+
         else:
             raise ValueError(f"Unknown model: {model_name}")
 
@@ -294,6 +308,7 @@ MODEL_CHOICES = [
     "U2Net",
     "BRIA RMBG 2.0",
     "IS-Net",
+    "withoutBG",
 ]
 
 
@@ -393,6 +408,7 @@ Benchmarked models:
 3. **U2Net** — via rembg/ONNX  
 4. **BRIA RMBG 2.0** — briaai/RMBG-2.0 (requires license acceptance)  
 5. **IS-Net** — isnet-general-use via rembg
+6. **withoutBG** — 4-stage ONNX pipeline (Depth → ISNet → Matting → Refiner)
 
 **Notes**
 - Output is true transparent PNG (RGBA)