WildDetect is a powerful wildlife detection and census system for aerial imagery. It helps conservationists, researchers, and organizations analyze wildlife populations, generate geographic visualizations, and produce actionable reports—all with easy-to-use command-line tools.

• Multi-species detection (YOLO-based, optimized for aerial images)
• Batch processing of large image datasets
• Geographic analysis: GPS mapping, coverage, and flight path analysis
• Population statistics: species counts, density, and trends
• Interactive maps and visualizations
• Comprehensive reporting (JSON, CSV)

# Clone the repository
git clone https://github.com/fadelmamar/wildetect.git
cd wildetect

# Install dependencies
uv sync

uv pip install -e .
uv pip install git+https://github.com/FadelMamar/wildtrain
uv pip install git+https://github.com/FadelMamar/wildata

Detect wildlife in images:

wildetect detect /path/to/images --model model.pt --output results/

Run a census campaign:

wildetect census campaign_2024 /path/to/images --model model.pt --output campaign_results/

• detect – Run wildlife detection on images
• census – Orchestrate a full wildlife census campaign
• analyze – Post-process and analyze detection results
• visualize – Create interactive geographic visualizations
• info – Show system and environment info
• api – Launch FastAPI server for REST API access

For all options, run:

wildetect --help

WildDetect provides a powerful and flexible command-line interface (CLI) built with Typer, making it easy to run wildlife detection, census campaigns, analysis, visualization, and more—all from your terminal.

After installing WildDetect, simply run:

wildetect [COMMAND] [OPTIONS]

You can always see all available commands and options with:

wildetect --help

• detect
  Run wildlife detection on images or directories of images.

  wildetect detect /path/to/images --model model.pt --output results/

  Options include model type, confidence threshold, device (CPU/GPU), batch size, tiling, and more.

• census
  Orchestrate a full wildlife census campaign, including detection, statistics, and reporting.

  wildetect census campaign_2024 /path/to/images --model model.pt --output campaign_results/

  Supports campaign metadata, pilot info, target species, and advanced analysis.

• analyze
  Analyze detection results for statistics and insights.

  wildetect analyze results.json --output analysis/

• visualize
  Create interactive geographic maps and visualizations from detection results.

  wildetect visualize results.json --output maps/

• info
  Display system and environment information, including dependencies and hardware support.

  wildetect info

• ui
  Launch the WildDetect web interface (Streamlit-based) for interactive exploration.

  wildetect ui

• fiftyone
  Manage FiftyOne datasets: launch the app, get info, or export data.

  wildetect fiftyone --action launch
  wildetect fiftyone --action info --dataset my_dataset
  wildetect fiftyone --action export --format coco --output export_dir/

• clear-results
  Delete all detection results in a specified directory (with confirmation).

• Rich Output: Uses rich for beautiful tables, progress bars, and colored logs.
• Flexible Input: Accepts both individual image files and directories.
• Advanced Options: Fine-tune detection, tiling, device selection, and more.
• Batch Processing: Efficiently processes large datasets.
• Integration: Seamless export to FiftyOne, JSON, and CSV formats.
• Help for Every Command: Use wildetect [COMMAND] --help for detailed options.

Edit YAML files in config/ to adjust model, detection, or system settings. See example configs for details.

Contributions are welcome! Please fork the repo, create a feature branch, and submit a pull request. See the full README for details.

MIT License. See LICENSE for details.