How It Works
Camera traps are an invaluable tool for analysing wildlife populations. However, the sheer amount of data they generate can be overwhelming – to annotate, organise, and analyse. That’s where TrapTagger comes in:
A powerful web-based application that leverages the latest artificial intelligence technologies to DETECT, COUNT, CLASSIFY and INDIVIDUALLY IDENTIFY animals, allowing you to focus on what’s important – your research.
Best of all – TrapTagger is completely FREE to use.
Choose Your Involvement
Whether you are a lone ecologist, or an entire research institution, you can choose the annotation approach that is right for you. Rely on our AI to automatically annotate the vast majority of your dataset with 99% precision. Or if accuracy is of utmost importance, manually annotate the dataset, and compare yourself to the AI to hone your results. Or choose something in between by having a select few low-interest, high-volume species automatically annotated to get the best of both worlds.
Features
Automatic AI-Annotation
Accuracy is at the heart of everything we do, so we only annotate images where the AI is confident of its species classification, leaving any uncertainties to the rigour of the human eye. This allows us to automatically annotate up to 95% of your dataset with incredible precision, allowing you to be confident in your results. Read more
Optimised Annotation Interface
Have multiple people annotating simultaneously with an optimised interface that uses custom hotkeys and AI aids to achieve per-person rates of up to 2 500 images per hour. Break your species down into hierarchical levels, and only tag the levels that are important to you, leaving the others for when they are needed, or for expert analysis. Read more
Image Clusters
Images of the same group of animals, from the same location, are clustered together as a single species sighting. These image clusters can then be rapidly annotated using a single button press, viewed together as a group, and counted together – or separately – in your results.
Import and Compare
Import your old datasets to keep your data centralised, analysable, and even make use of the AI to help detect errors and improve the quality of your data. Additionally, generate new datasets for your old surveys, and perform in-depth comparisons between their results.
Expert Analysis Tools
Use a number of interactive tools to analyse your results, including the distributions of all species across your survey area, or even their time-based activity patterns. Alternatively, simply download an Excel report for your records, or a custom csv file that you can easily import into any 3rd party software for analysis.
Data Privacy
We understand how important it can be to keep your camera locations secret, or images of vulnerable species out of the wrong hands, and as such we keep all your data entirely private. It is never shared with anybody else, ever.
TrapTagger vs. Traditional Approaches
TrapTagger achieves comparable recall and precision rates to traditional approaches in only 1,56% of the time, consequently reducing data-processing costs by 98.44%.
Learn More About TrapTagger
About
TrapTagger massively reduces the amount of time required to analyse camera-trap surveys, allowing ecologists to focus their time on what really matters.
Artificial Intelligence
The annotation process has been massively streamlined, and user workload reduced, by using AI in a number of powerful ways.
Interface
We strove to make all manual annotation processes as efficient and easy to use as possible. Read more about these optimisations here.
News
Read the latest TrapTagger success stories.
Documentation
Take a look through our published documentation, field tests, and reports.
Tutorials
Watch our tutorials to learn how TrapTagger works.
TrapTagger is Entirely Open Source
As our contribution to the conservation community, Traptagger has been released as open source. Being open source means that you can be assured that you will always have access to the platform free of charge. Moreover, it means that you can host your own organisational instance of the platform, or contribute your own features.