Projects
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Comparing AI computer vision with Human Labeling
We have AI results and volunteer contributed human labels for approximately 60,000 images.
This post explores the relationships between human error and ai errors. -
Deploying a computer vision model
Training and publishing a computer vision model on the web.
Try It Here!
- 🧪 Lightweight JavaScript demo
{you may need to visit the gradio/huggingface link below to wake up the app if it has been a while} - 🚀 Full-featured Gradio app
- 🧪 Lightweight JavaScript demo
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Building a Webapp for Species Geofencing
One of the issues we experienced with speciesnet classification was results where the species was not valid for our location. In speciesnet - specifying a geofence coordinate will cause missclassifications to move up to the highest level hierarchy - in most cases, this classifies an animal as “animal.”
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Catch A Vibe Code
I joined an ai for conservation slack group recently. In that group, one of the developers of SpeciesNet (camera trap computer vision) and the creator of the MegaDetector object detection model, Dan Morris, hosted a “Vibe coding party” this week.