fix(pipeline): respect pretrained rembg (RMBG-2.0); optional NEAR_REMBG_MODEL

app.py

@@ -179,6 +179,8 @@ def _ensure_models() -> None:
         if PIPELINE is not None:
             return
         device = "cuda" if torch.cuda.is_available() else "cpu"
+        # briaai/RMBG-2.0 is gated: accept the license on the model card, then add HF_TOKEN
+        # (read) in Space Settings -> Secrets. Never commit tokens into git.
         near_id = os.environ.get("NEAR_PRETRAINED", "luh0502/NeAR")
         gp = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained("tencent/Hunyuan3D-2.1")
         gp.to(device)

trellis/pipelines/near_image_to_relightable_3d.py

@@ -95,12 +95,10 @@ class NeARImageToRelightable3DPipeline(Pipeline):
         rembg_spec = args["rembg_model"]
         rembg_name = rembg_spec["name"]
         rembg_kwargs = dict(rembg_spec["args"])
+        env_rembg = os.environ.get("NEAR_REMBG_MODEL")
+        if env_rembg:
+            rembg_kwargs["model_name"] = env_rembg
         rembg_cls = getattr(rembg, rembg_name)
-        # HF model config.json may still point at gated briaai/RMBG-2.0; Space demo uses open BiRefNet.
-        if rembg_name == "BiRefNet":
-            rembg_kwargs["model_name"] = os.environ.get(
-                "NEAR_REMBG_MODEL", "ZhengPeng7/BiRefNet"
-            )
         new_pipeline.rembg_model = rembg_cls(**rembg_kwargs)
         new_pipeline._init_image_cond_model(args["image_cond_model"])
         new_pipeline.hdri_processor = HDRI_Preprocessor(envmap_h=512, envmap_w=1024)