Refactor Dockerfile and requirements.txt for improved dependency management; update README.md with clearer installation options and instructions for prebuilt images.

Dockerfile.gpu

@@ -0,0 +1,53 @@
+FROM python:3.11-slim
+
+# Set working directory
+WORKDIR /app
+
+# Install system dependencies including CUDA-related packages
+RUN apt-get update && apt-get install -y \
+    ffmpeg \
+    git \
+    wget \
+    curl \
+    build-essential \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements first for better Docker layer caching
+COPY requirements.txt .
+
+# Install CPU versions from requirements.txt first
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Install CUDA-optimized PyTorch (overwrites CPU versions)
+RUN pip install --force-reinstall \
+    torch==2.0.1+cu118 \
+    torchvision==0.15.2+cu118 \
+    torchaudio==2.0.2+cu118 \
+    --index-url https://download.pytorch.org/whl/cu118
+
+# Copy application code
+COPY . .
+
+# Create directories for mounted volumes
+RUN mkdir -p /app/data/videos /app/data/outputs /app/data/cache
+
+# Set environment variables
+ENV STREAMLIT_SERVER_PORT=8501
+ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
+ENV STREAMLIT_SERVER_HEADLESS=true
+ENV STREAMLIT_BROWSER_GATHER_USAGE_STATS=false
+
+# GPU-specific environment variables
+ENV CUDA_VISIBLE_DEVICES=0
+ENV NVIDIA_VISIBLE_DEVICES=all
+ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
+
+# Expose Streamlit port
+EXPOSE 8501
+
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
+    CMD curl -f http://localhost:8501/_stcore/health || exit 1
+
+# Start the application
+CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]