Comments (1)
Don't need to wait for #7 here. I think we can shoot for using tensorflow either with a model file located in the project or hosted on tfhub. Ideally, we could have all of the image processing and prediction happen on the client application. Eventually this could allow our application to be used while not connected to the internet.
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Related Issues (20)
- [Feature]: Static JS bundle support HOT 2
- [Feature]: Docker compose only deployment HOT 3
- Document frontend functions and structure
- Integration trash-ai in citizen science project HOT 5
- [Feature]: Data augmentation method by extracting objects and placing them on different backgrounds
- [Feature]: Document model/build tools
- Convert weights per model into bin files
- Write up guide for using project board HOT 5
- Find complementary annotated image databases
- Create pull request template HOT 1
- TrashAI Project Meeting Times:
- Meeting Times
- Understand the Project
- Ready to start?
- Create onboarding issue "template" for new contributors HOT 4
- Onboarding Checklist Issue HOT 4
- [Bug]: Dependabot targets production branch
- [Bug]: Summary adds one to all counts HOT 1
- [Feature]: Review 2 HOT 3
- [Feature]: API Endpoint
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