Open-source AI model for Sub-Saharan Africa camera trap species detection
The TrapTracker Sub-Saharan Africa Mammals Models are object detection models designed to support camera trap image analysis across Sub-Saharan African wildlife monitoring projects.
The models have been trained to detect a wide range of African mammal species commonly captured in camera trap studies, alongside people and vehicles. It is intended to help conservation organisations, researchers, students, and field teams process large image datasets more efficiently while keeping analysis workflows local, transparent, and accessible.
The models are released for non-commercial conservation, research, education, and citizen science use.
Model Overview
Several model architectures (see below) have been trained on camera trap imagery representing a broad range of Sub-Saharan African mammal species.
They are designed to detect and localise animals within camera trap images, including images captured under challenging field conditions such as low light, infrared night imagery, partial occlusion, distant subjects, multiple animals in a frame, and varied habitat backgrounds.
The models are intended as a practical tool for accelerating image review, reducing manual sorting time, and supporting conservation monitoring workflows.
Training Data
The models were trained on labelled instances drawn from Sub Saharan Africa camera trap images collected through conservation deployments over nearly a decade.
The dataset includes a wide range of practical camera trap conditions, including:
- daylight RGB images
- infrared night-time images
- motion blur
- partial occlusion
- multi-animal frames
- juveniles and adults
- manufacturer overlays and timestamps
- varied Sub Saharan Africa habitats and deployment settings
Training setup
The model was trained using:
- Architecture: YOLO10x and YOLO26x
- Input resolution: 640 × 640
- Training hardware: 8 × NVIDIA RTX A6000 GPUs
- Global batch size: 256
- Framework: Ultralytics
- Export format: ONNX
The model was trained with deterministic settings and a fixed random seed to support reproducibility.
Intended Use
The models are intended for non-commercial use in:
- Sub-Saharan African camera trap image analysis
- wildlife monitoring
- biodiversity surveys
- ecological research
- conservation project workflows
- university research and teaching
- citizen science projects
- offline or local image processing
- pre-filtering images before manual review
The models are particularly useful where users need to process large numbers of images and identify likely species detections before manual verification.
Not Intended For
The models are not intended for:
- commercial resale
- paid inference services
- use as a legally authoritative identification system
- replacing expert ecological judgement
- surveillance or monitoring of people
- use outside the model’s species coverage without validation
- making conservation decisions without appropriate human review
Where outputs are used in publications, reports, conservation management, or policy-facing work, results should be manually checked and validated.
Why we are releasing it
Camera trap AI has become increasingly important for biodiversity monitoring, but access to high-performing species recognition tools is often limited by commercial platforms, proprietary weights, pay-per-image models, or cloud-based inference.
This release is intended as a practical counterweight to that trend.
The aim is simple: a conservation organisation with limited funding, no machine-learning team, and no GPU should still be able to process camera trap images locally and obtain useful species-level detections.
The models are free for non-commercial use, runs offline, and is designed for ecologists and conservation practitioners rather than machine-learning specialists.
How to cite
If you use the model in research, reports, publications, or conservation outputs, please cite:
Paper to follow
A formal citation will be added here once the paper is available online.
Licence
The model weights are released for non-commercial use.
You may use the models for conservation, research, teaching, ecological monitoring, citizen science, and non-commercial biodiversity work.
You may not resell the models, use them to provide a paid commercial inference service, or incorporate them into a commercial product without prior permission.
For commercial licensing enquiries, please contact:
Download
By downloading the models, you agree to use them only for non-commercial purposes and to acknowledge the models appropriately in any resulting publications, reports, or public outputs.
Updates
The Trap Tracker Sub Saharan Africa Mammals Model will continue to be developed as new data become available and as the underlying model architecture improves. Future releases will be made available periodically, with clear versioning so that users can track changes, improvements, and compatibility across model updates.