Overview

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! 🚀

TRAPPER in a nutshell

🌍 Global Standards: Full support for the emerging Camtrap DP standard
🤖 AI-Powered: Automatic AI-driven data processing pipelines with object detection, species classification & privacy protection
🔧 AI Integration: Easy integration of new AI models and algorithms
⚡ Scalable Processing: GPU-based image and video processing that scales with your needs
🏗️ Flexible Deployment: Deploy anywhere - from laptops to cloud infrastructure
☁️ Cloud Ready: Supported on Azure, AWS, OVH, MinIO and more
📱 Portable: Runs on micro-servers (Raspberry Pi 5, NVIDIA Jetson)
👥 Dual Interface: Expert module for researchers + user-friendly citizen science interface
🗄️ Advanced Management: Spatially-enabled database with robust project management
🔄 Open Source: Fully open-source with collaborative development
📊 Media Support: Handles both pictures & videos seamlessly
🔗 API First: Comprehensive API for integrations and data access

TRAPPER ecosystem

Trapper Expert — the core web application (TRAPPER), providing all essential system functionalities. It features an Angular and Bootstrap-based frontend, paired with a Django backend. The application uses a PostgreSQL database with the PostGIS extension for spatial data management, and employs RabbitMQ as a message broker with Celery workers for asynchronous task processing.

Trapper Citizen Science — an innovative frontend application (UI) for TRAPPER, specifically designed for Citizen Science projects.

Trapper AI — a module responsible for integrating and configuring AI models for object detection and species classification. This component includes the Trapper AI Manager web interface and Trapper AI Worker. Workers can utilize GPUs and can be scaled or deployed across multiple machines.

Trapper Jupyter Hub (not yet released) — a module for sharing JupyterHub and Jupyter notebooks within TRAPPER, enabling users to explore and analyze data using Python or R scientific libraries.

Trapper Tools — a Python CLI application for creating and uploading camera trap data packages compatible with the TRAPPER system. This tool is recommended for uploading large volumes of data (many GBs) to the TRAPPER web application. It features an automated pipeline that can convert, package, and upload data in a single command. Optionally, it can also trigger post-upload collection processing, including automatic sequence building and an AI pipeline for object detection and species classification for both images and videos.

Deployment Blueprints

TRAPPER’s flexible architecture supports diverse deployment scenarios:

Local Development & Research - Laptop/desktop installations for individual researchers - Lab PC setups for small research teams - Standalone workstations with GPU acceleration

Organizational Networks - Corporate/institutional local network deployments - Private cloud environments - Multi-user collaborative platforms

Public Cloud Platforms - Microsoft Azure - Amazon Web Services (AWS) - OVH Cloud solutions - MinIO object storage integration

Edge & Portable Computing - Raspberry Pi 5 micro-servers for field deployments - NVIDIA Jetson platforms for edge AI processing - Portable research stations for remote locations

Demo

In progress 🚧

An interactive demo is currently being polished to showcase TRAPPER’s AI-driven workflows, new innovative Citizen-Science interface and API integrations. Stay tuned for an early preview and hands-on walkthroughs that will highlight real-world project workflows, performance, and deployment options. 👀

Overview

TRAPPER in a nutshell

TRAPPER ecosystem

Deployment Blueprints

Demo

Read more