feat: add bria-rmbg model support

rembg/sessions/__init__.py

@@ -86,3 +86,8 @@ from .u2netp import U2netpSession
 
 sessions_class.append(U2netpSession)
 sessions_names.append(U2netpSession.name())
+
+from .bria_rmbg import BriaRmBgSession
+
+sessions_class.append(BriaRmBgSession)
+sessions_names.append(BriaRmBgSession.name())

rembg/sessions/bria_rmbg.py

@@ -0,0 +1,88 @@
+import os
+from typing import List
+
+import numpy as np
+import pooch
+from PIL import Image
+from PIL.Image import Image as PILImage
+
+from .base import BaseSession
+
+
+class BriaRmBgSession(BaseSession):
+    """
+    This class represents a Bria-rmbg-2.0 session, which is a subclass of BaseSession.
+    """
+
+    def predict(self, img: PILImage, *args, **kwargs) -> List[PILImage]:
+        """
+        Predicts the output masks for the input image using the inner session.
+
+        Parameters:
+            img (PILImage): The input image.
+            *args: Additional positional arguments.
+            **kwargs: Additional keyword arguments.
+
+        Returns:
+            List[PILImage]: The list of output masks.
+        """
+        ort_outs = self.inner_session.run(
+            None,
+            self.normalize(
+                img, (0.485, 0.456, 0.406), (0.229, 0.224, 0.225), (1024, 1024)
+            ),
+        )
+
+        pred = ort_outs[0][:, 0, :, :]
+
+        ma = np.max(pred)
+        mi = np.min(pred)
+
+        pred = (pred - mi) / (ma - mi)
+        pred = np.squeeze(pred)
+
+        mask = Image.fromarray((pred * 255).astype("uint8"), mode="L")
+        mask = mask.resize(img.size, Image.Resampling.LANCZOS)
+
+        return [mask]
+
+    @classmethod
+    def download_models(cls, *args, **kwargs):
+        """
+        Downloads the BRIA-RMBG 2.0 model file from a specific URL and saves it.
+
+        Parameters:
+            *args: Additional positional arguments.
+            **kwargs: Additional keyword arguments.
+
+        Returns:
+            str: The path to the downloaded model file.
+        """
+        fname = f"{cls.name(*args, **kwargs)}.onnx"
+        pooch.retrieve(
+            "https://huggingface.co/briaai/RMBG-2.0/resolve/main/onnx/model.onnx",
+            (
+                None
+                if cls.checksum_disabled(*args, **kwargs)
+                else "sha256:5b486f08200f513f460da46dd701db5fbb47d79b4be4b708a19444bcd4e79958"
+            ),
+            fname=fname,
+            path=cls.u2net_home(*args, **kwargs),
+            progressbar=True,
+        )
+
+        return os.path.join(cls.u2net_home(*args, **kwargs), fname)
+
+    @classmethod
+    def name(cls, *args, **kwargs):
+        """
+        Returns the name of the Bria-rmbg session.
+
+        Parameters:
+            *args: Additional positional arguments.
+            **kwargs: Additional keyword arguments.
+
+        Returns:
+            str: The name of the session.
+        """
+        return "bria-rmbg"