Update Dockerfile

Dockerfile

@@ -7,7 +7,15 @@ RUN apt-get update && apt-get install -y \
     wget \
     && rm -rf /var/lib/apt/lists/*
 
-# Install Python packages including Hugging Face Transformers, TorchScript, Flask, TensorFlow, and TensorFlow Hub
+# Install system-level dependencies for OpenCV
+RUN apt-get update && apt-get install -y \
+    libglib2.0-0 \
+    libsm6 \
+    libxext6 \
+    libxrender-dev \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install Python packages including Hugging Face Transformers, TorchScript, Flask, TensorFlow, TensorFlow Hub, and OpenCV
 RUN pip install --no-cache-dir \
     torch \
     torchvision \
@@ -17,7 +25,8 @@ RUN pip install --no-cache-dir \
     Pillow \
     huggingface_hub \
     tensorflow \
-    tensorflow_hub
+    tensorflow_hub \
+    opencv-python
 
 # Set Hugging Face cache to a guaranteed writable directory
 ENV TRANSFORMERS_CACHE=/tmp/cache
@@ -28,17 +37,11 @@ RUN mkdir -p /models/blip /models/clip
 
 # Python script to download models using tensorflow_hub and huggingface_hub
 RUN echo "import os\n\
-import tensorflow_hub as hub\n\
-\n\
-# Download MoveNet model from TensorFlow Hub (loaded directly in app, not saved)\n\
-movenet_model = hub.load('https://tfhub.dev/google/movenet/singlepose/lightning/4')\n\
-\n\
-# Download BLIP model and tokenizer using huggingface_hub\n\
+import tensorflow_hub as hub\n\n\n# Download MoveNet model from TensorFlow Hub (loaded directly in app, not saved)\n\
+movenet_model = hub.load('https://tfhub.dev/google/movenet/singlepose/lightning/4')\n\n\n# Download BLIP model and tokenizer using huggingface_hub\n\
 from transformers import BlipForConditionalGeneration, BlipProcessor\n\
 BlipForConditionalGeneration.from_pretrained('Salesforce/blip-image-captioning-large').save_pretrained('/models/blip')\n\
-BlipProcessor.from_pretrained('Salesforce/blip-image-captioning-large').save_pretrained('/models/blip')\n\
-\n\
-# Download CLIP model and processor using huggingface_hub\n\
+BlipProcessor.from_pretrained('Salesforce/blip-image-captioning-large').save_pretrained('/models/blip')\n\n\n# Download CLIP model and processor using huggingface_hub\n\
 from transformers import CLIPModel, CLIPProcessor\n\
 CLIPModel.from_pretrained('openai/clip-vit-large-patch14').save_pretrained('/models/clip')\n\
 CLIPProcessor.from_pretrained('openai/clip-vit-large-patch14').save_pretrained('/models/clip')" > download_models.py