Automatically classify and tag your wildlife photos with AI precision
RT-DETR object detection combined with iNat21 species classification identifies 10,000+ species automatically.
Process thousands of photos in minutes. 10x faster with GPU acceleration - up to 10 photos per second.
Works seamlessly with Lightroom Classic, On1 PhotoRAW, Immich, and other photo management tools.
Your photos never leave your computer. All AI processing happens locally - no cloud uploads, no data sharing, complete privacy.
Get started with a single Docker command. No complex installation, no dependencies to manage - just run and go.
Checkpoint-based processing lets you pause and resume anytime. Perfect for large collections - pick up right where you left off.
# Create project directory
mkdir -p lumina-docker/{photos,cache} && cd lumina-docker
# Download docker-compose.yml
curl -o docker-compose.yml https://raw.githubusercontent.com/stevenvanassche/Lumina/master/docker/docker-compose.yml
# Create .env file
cat > .env << EOF
PHOTOS_PATH=./photos
CACHE_PATH=./cache
EOF
# Add your photos to photos/ directory, then run:
docker compose --profile cpu up # CPU mode (~1 photo/sec)
docker compose --profile gpu up # GPU mode (~10 photos/sec)
First Run: Models download automatically (~2.5GB, 5-15 minutes)
View Full Documentation →
Automatically tag thousands of bird and animal species in your photo collection.
Organize your collection with AI precision. Works with your existing workflow.
Batch process biodiversity data for ecological studies and citizen science.
Start processing your photos with AI precision today