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Dockerfile

@@ -49,6 +49,7 @@ RUN pip install --no-cache-dir -U \
     Pillow==9.5.0 \
     colored==1.4.4
 RUN pip install --no-cache-dir -U gradio==4.43.0
+RUN pip install -U "huggingface_hub[cli]"
 
 COPY --chown=1000 . ${HOME}/app
 RUN git clone https://github.com/facebookresearch/CutLER.git

model.py

@@ -3,6 +3,7 @@
 
 import argparse
 import multiprocessing as mp
+import os
 import pathlib
 import shlex
 import subprocess
@@ -87,14 +88,23 @@ WEIGHT_URL = 'http://dl.fbaipublicfiles.com/cutler/checkpoints/cutler_cascade_fi
 
 
 def load_model(score_threshold: float) -> VisualizationDemo:
+    # Get secrets
+    hf_token = os.getenv('HF_TOKEN')
+    model_filename = os.getenv('MODEL_NAME')
+
     model_dir = pathlib.Path('checkpoints')
     model_dir.mkdir(exist_ok=True)
-    weight_path = model_dir / WEIGHT_URL.split('/')[-1]
+    #weight_path = model_dir / WEIGHT_URL.split('/')[-1]
+    weight_path = model_dir / ".cache" / "huggingface" / "download"/ model_filename
     print("***weight_path***", weight_path)
     print("torch.cuda.is_available()", torch.cuda.is_available())
 
-    if not weight_path.exists():
-        subprocess.run(shlex.split(f'wget {WEIGHT_URL} -O {weight_path}'))
+
+    # Load the model weights file from huggingface hub, use token to authenticate
+    subprocess.run(shlex.split(f'huggingface-cli download leonsick/cuts3d_zeroshot {model_filename} --token {hf_token} --local-dir {model_dir}'))
+
+    #if not weight_path.exists():
+    #    subprocess.run(shlex.split(f'wget {WEIGHT_URL} -O {weight_path}'))
 
     arg_list = [
         '--config-file',