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AddaxAI 7.16.0
AI-assisted analysis for camera-trap wildlifeAddaxAI helps wildlife researchers analyze large collections of camera-trap photos. It uses machine-learning models to detect and classify animals, with a guided Simple Mode for selecting images and expected species. Advanced Mode adds confidence settings, people blurring, mapping and support for custom object-detection models. Results can be mapped or graphed when photos contain relevant location and date information.
AddaxAI 7.16.0 details
| Author: | Peter van Lunteren |
| License: | Open Source |
| Price: | FREE |
| Released: | Oct 16, 2026 |
| File size: | 174.00 MB |
| Downloads: | 359 |
| Keywords: | intuitive interface, camera trap image analysis, camera trap, GitHub, camera trap mapping, map, animal species identification, wildlife detection software, Peter van Lunteren, open-source innovation, AddaxAI, seamless integration, productivity enhancement, download AddaxAI, AI-powered automation, AddaxAI free download, map species, software, wildlife photo classifier, species, wildlife, custom object detection, analyze wildlife, development, user-friendly design, wildlife explorer |
| Author URL: | https://github.com/PetervanLunteren/AddaxAI |
AddaxAI for Windows 10 - Full description
AddaxAI is an open-source desktop tool for wildlife researchers and conservation teams working with images from motion-activated camera traps. These cameras can produce large collections in which many frames contain no animals, making manual review slow. AddaxAI uses machine-learning detection models to scan photos, identify animals and classify species, helping researchers focus attention on relevant images rather than sorting every frame by hand.
In Simple Mode, the workflow is guided: select the folder containing the camera-trap photos, choose a species detection model and mark the animals expected in the study area. AddaxAI then analyzes the images with that model. This setup is suited to routine processing when a project needs a straightforward path from a photo folder to detected wildlife. Automated results can reduce the time spent reviewing large image sets, while researchers can check the detections as part of their analysis.
Advanced Mode provides more control over detection and processing. Users can set the confidence threshold that determines when the software labels an animal, which helps adjust how cautiously detections are reported. The mode also offers an option to blur people appearing in images, supporting privacy when camera traps capture passersby. AddaxAI can also work with custom object-detection models, allowing teams to train and deploy models suited to their own species or research needs.
The software records where and when detections occur when that information is available in the photos. Camera-trap images need to contain relevant date, time or GPS metadata for those details to support spatial or temporal analysis. AddaxAI can use the recorded information to create maps and graphs, helping researchers examine where species appear and when activity occurs. These summaries complement image review by making patterns across a collection easier to inspect.
AddaxAI is intended for processing wildlife camera-trap collections, including research projects that need species detections, location summaries or activity patterns. It is open source and runs on 64-bit Windows 10 and Windows 11. The usefulness of its results depends on the selected detection model and the information available in the images; maps and timing analysis require suitable location or date metadata.