feat: add Docker configuration for containerized deployment

.dockerignore

@@ -0,0 +1,54 @@
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+.env/
+.venv/
+env/
+venv/
+ENV/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+*~
+
+# Project specific
+output/*.tif
+data/*.tif
+data/*.shp
+data/*.shx
+data/*.dbf
+data/*.prj
+*.dbf
+*.shp
+*.shx
+*.prj
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Testing
+.pytest_cache/
+.coverage
+htmlcov/

Dockerfile

@@ -0,0 +1,38 @@
+# GIS Classification - Docker Image
+FROM python:3.11-slim
+
+# Set working directory
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    gdal-bin \
+    libgdal-dev \
+    libgeos-dev \
+    libproj-dev \
+    && rm -rf /var/lib/apt/lists/*
+
+# Set GDAL environment variables
+ENV GDAL_VERSION=3.6.2
+
+# Copy requirements first for better caching
+COPY requirements.txt .
+
+# Install Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY . .
+
+# Create necessary directories
+RUN mkdir -p /app/data /app/output /app/static
+
+# Expose port
+EXPOSE 8000
+
+# Set environment variables
+ENV PYTHONUNBUFFERED=1
+ENV PYTHONDONTWRITEBYTECODE=1
+
+# Run the application
+CMD ["uvicorn", "src.api:app", "--host", "0.0.0.0", "--port", "8000"]

README.md

@@ -8,6 +8,9 @@ Python project for land cover classification using GIS data (GeoTIFF + Shapefile
 gis-classification/
 ├── main.py              # Main script with parameters
 ├── requirements.txt     # Dependencies
+├── Dockerfile           # Docker image configuration
+├── docker-compose.yml   # Docker Compose configuration
+├── .dockerignore        # Docker ignore rules
 ├── data/                # Input data folder
 ├── output/              # Classification results
 ├── static/              # Web frontend
@@ -33,6 +36,44 @@ Or with uv:
 uv pip install -r requirements.txt
 ```
 
+### Docker Deployment
+
+**Build and run with Docker Compose:**
+
+```bash
+docker-compose up --build
+```
+
+**Or run with Docker directly:**
+
+```bash
+docker build -t gis-classification .
+docker run -p 8000:8000 -v $(pwd)/data:/app/data -v $(pwd)/output:/app/output gis-classification
+```
+
+Then open http://localhost:8000 in your browser.
+
+**Production with Nginx (optional):**
+
+1. Uncomment the nginx section in `docker-compose.yml`
+2. Create `nginx.conf` (see example below)
+3. Run `docker-compose up -d`
+
+Example `nginx.conf`:
+```nginx
+events { worker_connections 1024; }
+http {
+    server {
+        listen 80;
+        location / {
+            proxy_pass http://gis-classification:8000;
+            proxy_set_header Host $host;
+            proxy_set_header X-Real-IP $remote_addr;
+        }
+    }
+}
+```
+
 ## Usage
 
 ### CLI Mode

docker-compose.yml

@@ -0,0 +1,40 @@
+version: '3.8'
+
+services:
+  gis-classification:
+    build:
+      context: .
+      dockerfile: Dockerfile
+    container_name: gis-classification
+    ports:
+      - "8000:8000"
+    volumes:
+      # Mount data directory for input files
+      - ./data:/app/data
+      # Mount output directory for results
+      - ./output:/app/output
+      # Mount static files (frontend)
+      - ./static:/app/static
+    environment:
+      - PYTHONUNBUFFERED=1
+      # Optional: Set max upload size (in bytes)
+      - MAX_UPLOAD_SIZE=104857600
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 40s
+
+# Optional: Add nginx reverse proxy for production
+# nginx:
+#   image: nginx:alpine
+#   container_name: gis-nginx
+#   ports:
+#     - "80:80"
+#   volumes:
+#     - ./nginx.conf:/etc/nginx/nginx.conf:ro
+#   depends_on:
+#     - gis-classification
+#   restart: unless-stopped