Dockerfile

# Use Python 3.10 slim image for smaller size
FROM python:3.10-slim

# Set working directory
WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y \
    gcc \
    g++ \
    libgl1-mesa-glx \
    libglib2.0-0 \
    libsm6 \
    libxext6 \
    libxrender-dev \
    libgomp1 \
    libglib2.0-0 \
    libfontconfig1 \
    libgtk-3-0 \
    libavcodec-dev \
    libavformat-dev \
    libswscale-dev \
    libv4l-dev \
    libxvidcore-dev \
    libx264-dev \
    libjpeg-dev \
    libpng-dev \
    libtiff-dev \
    libatlas-base-dev \
    libhdf5-dev \
    libhdf5-serial-dev \
    libhdf5-103 \
    python3-dev \
    python3-pip \
    python3-setuptools \
    python3-wheel \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Create cache directories with proper permissions
RUN mkdir -p /tmp/huggingface /tmp/matplotlib /tmp/ultralytics /tmp/fontconfig \
    && chmod 777 /tmp/huggingface /tmp/matplotlib /tmp/ultralytics /tmp/fontconfig

# Set environment variables for cache directories
ENV TRANSFORMERS_CACHE=/tmp/huggingface
ENV HF_HOME=/tmp/huggingface
ENV MPLCONFIGDIR=/tmp/matplotlib
ENV YOLO_CONFIG_DIR=/tmp/ultralytics
ENV FONTCONFIG_PATH=/tmp/fontconfig

# Copy requirements first for better caching
COPY requirements.txt .

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

# Copy application files
COPY . .

# Create necessary directories
RUN mkdir -p uploads property_images

# Download YOLO model
RUN python -c "from ultralytics import YOLO; YOLO('yolov8n.pt')"

# Set environment variables
ENV PYTHONPATH=/app
ENV FLASK_APP=app.py
ENV FLASK_ENV=production
ENV PORT=7860

# Expose port
EXPOSE 7860

# Health check
HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
    CMD curl -f http://localhost:7860/health || exit 1

# Run the application
CMD ["python", "app.py"]