Dockerfile

FROM pytorch/pytorch:2.5.1-cuda12.4-cudnn9-runtime

WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y \
    git \
    wget \
    curl \
    libsm6 \
    libxext6 \
    libxrender-dev \
    libgl1-mesa-glx \
    && rm -rf /var/lib/apt/lists/*

# Install Python dependencies first
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Clone Segment Anything 2 from Meta
RUN git clone https://github.com/facebookresearch/sam2.git segment-anything-2 && \
    cd segment-anything-2 && \
    pip install -e . && \
    cd ..

# Download SAM2 model weights
RUN cd segment-anything-2/checkpoints && \
    bash download_ckpts.sh && \
    cd ../..

# Set Hugging Face token for VREyeSAM weights (injected by HF Spaces)
ENV HF_TOKEN=""

# Copy application files
COPY app.py model_server.py ./

# Create .streamlit directory and config
RUN mkdir -p .streamlit
COPY .streamlit/config.toml .streamlit/

# Note: VREyeSAM fine-tuned weights will be downloaded at runtime by model_server.py
# using the HF_TOKEN from HF Spaces Secrets

# Expose Streamlit port
EXPOSE 7860

# Run Streamlit app
CMD ["streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0"]