model support from hf

app.py

@@ -19,9 +19,10 @@ NUM_PROCESSES = 1
 CROP = False
 SCORE_THRESHOLD = 0.8
 MAX_PARTS = 5  # TODO: we can replace this by having a slider and a single image visualization component rather than multiple components
+HF_MODEL_PATH = {"repo_id": "3dlg-hcvc/opdmulti-motion-state-rgb-model", "filename": "pytorch_model.pth"}
 ARGS = SimpleNamespace(
     config_file="configs/coco/instance-segmentation/swin/opd_v1_real.yaml",
-    model={"repo_id": "3dlg-hcvc/opdmulti-motion-state-rgb-model", "filename": "pytorch_model.pth"},
+    model=None,
     input_format="RGB",
     output=".output",
     cpu=True,
@@ -88,8 +89,7 @@ def predict(rgb_image: str, depth_image: str, intrinsic: np.ndarray, num_samples
         return [None] * 5
 
     # run model
-    weights_path = hf_hub_download(repo_id=ARGS.model["repo_id"], filename=ARGS.model["filename"])
-    ARGS.model = weights_path
+    ARGS.model = hf_hub_download(repo_id=HF_MODEL_PATH["repo_id"], filename=HF_MODEL_PATH["filename"])
     cfg = setup_cfg(ARGS)
     engine.launch(
         main,