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TRAPPER

Open-source, AI-powered camera trap data management.

TRAPPER is a next-generation, open-source Django based web application revolutionizing camera trapping project management. 🎯

As camera trapping becomes increasingly vital for ecological research and wildlife conservation, the challenge of managing massive multimedia datasets grows exponentially. TRAPPER transforms this challenge into an opportunity by providing a comprehensive, AI-powered platform that handles everything from data ingestion to advanced analytics.

What sets TRAPPER apart is its modern approach to camera trap data management: full compliance with the emerging global Camtrap DP standard, cutting-edge AI processing pipelines, and deployment flexibility that scales from laptop research to enterprise cloud infrastructure. Whether you're a researcher working on a small field study or managing large-scale citizen science projects, TRAPPER adapts to your needs. πŸš€

Get started Run the AI pipeline Citizen Science

Finding your way around these docs

graph TD
    Q["What do you need?"]
    Q -->|"I'm new β€” walk me through it"| T["Tutorials<br/>learning-oriented"]
    Q -->|"I need to do a specific task"| H["How-to guides<br/>task-oriented"]
    Q -->|"I need exact fields, flags, endpoints"| R["Reference<br/>information-oriented"]
    Q -->|"I want to understand why it works this way"| E["Explanation<br/>understanding-oriented"]

TRAPPER in a nutshell

  • 🌍 Global Standards

    Full support for the emerging Camtrap DP standard.

  • πŸ€– AI-Powered

    Automatic AI-driven data processing pipelines with object detection, species classification & privacy protection.

  • πŸ”§ AI Integration

    Easy integration of new AI models and algorithms.

  • ⚑ Scalable Processing

    GPU-based image and video processing that scales with your needs.

  • πŸ—οΈ Flexible Deployment

    Deploy anywhere, from laptops to cloud infrastructure.

  • ☁️ Cloud Ready

    Supported on Azure, AWS, OVH, MinIO and more.

  • πŸ“± Portable

    Runs on micro-servers (Raspberry Pi 5, NVIDIA Jetson).

  • πŸ‘₯ Dual Interface

    Expert module for researchers + user-friendly Citizen Science interface.

  • πŸ—„οΈ Advanced Management

    Spatially-enabled database with robust project management.

  • πŸ”„ Open Source

    Fully open-source with collaborative development.

  • πŸ“Š Media Support

    Handles both pictures & videos seamlessly.

  • πŸ”— API First

    Comprehensive API for integrations and data access.

The ecosystem at a glance

graph LR
    CS["Citizen Science<br/>frontend"] --> Expert
    Tools["Trapper Tools<br/>(CLI)"] --> Expert
    Expert["Trapper Expert<br/>(this module)"] <--> Manager["Trapper AI<br/>Manager"]
    Manager <--> Worker["Trapper AI<br/>Worker(s)"]
Module Role
Trapper Expert Core web application β€” project management, classification, admin. Django (its UI is the Django admin itself), PostgreSQL/PostGIS, Celery/RabbitMQ.
Trapper Citizen Science Frontend UI purpose-built for Citizen Science projects.
Trapper AI AI Manager + Trapper AI Worker β€” object detection & species classification, GPU-scalable.
Trapper Tools CLI for converting, packaging and uploading large camera trap data volumes, with optional pipeline triggers.
Trapper Jupyter Hub Not yet released β€” shared JupyterHub/notebooks for Python/R analysis within TRAPPER.

See Explanation β€Ί Ecosystem for the full module breakdown and deployment blueprints.

Demo β€” in progress 🚧

An interactive demo is currently being polished to showcase TRAPPER's AI-driven workflows, the Citizen Science interface, and API integrations. Stay tuned for an early preview and hands-on walkthroughs covering real-world project workflows, performance, and deployment options. πŸ‘€

Citations

Bubnicki, J. W., Churski, M. and Kuijper, D. P. (2016), TRAPPER: an open source web‐based application to manage camera trapping projects. Methods Ecol Evol, 7: 1209-1216. doi:10.1111/2041-210X.12571

Frauendorf, M., Bubnicki, J.W., Γ…nΓΆstam, F., Tynecki, P., WaΕ‚ejko, Ł., Cromsigt, J.P., Widemo, F. and Hofmeester, T.R., 2025. Trapper Citizen Science: an open-source camera trap platform for citizen science in wildlife research and management. Preprint, ecoevorxiv.org.

Bubnicki, J.W., Norton, B., Baskauf, S.J., Bruce, T., Cagnacci, F., Casaer, J., Churski, M., Cromsigt, J.P., Farra, S.D., Fiderer, C. and Forrester, T.D., 2024. Camtrap DP: an open standard for the FAIR exchange and archiving of camera trap data. Remote sensing in ecology and conservation, 10(3), pp.283-295. doi:10.1002/rse2.374

Stachowicz, I., Bubnicki, J.W., 2025. Trapper AI - a scalable, open-source camera trap data infrastructure for professional and citizen-science projects. 14th European Vertebrate Management Conference, Ankaran, Slovenia. doi:10.13140/RG.2.2.18435.62241

For more news about TRAPPER, visit the Open Science Conservation Fund (OSCF) website or follow OSCF on LinkedIn.