Projects
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Chicago wildlife species analysis - a starting point
After improving the species classification model to a point where we can start to trust its predictions - we ran it on 71k+ images where speciesnet predicted at least 5% likely containing an animal.
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Filtering 90% of blank wildife photos for a better UX
Our community wildlife classification/identification project is live at rangers.urbanrivers.org.
Using AI, we are massively fixing the boring part. -
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!
- ๐งช Lightweight JavaScript demo
{you may need to visit the gradio/huggingface link below to wake up the app if it has been a while} - ๐ Full-featured Gradio app
- ๐งช Lightweight JavaScript demo
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