FeedbackBots
ailab
FeedbackBots | ailab | |
---|---|---|
1 | 2 | |
0 | 7,641 | |
- | 0.3% | |
10.0 | 0.0 | |
almost 2 years ago | 11 months ago | |
C# | C# | |
GNU Affero General Public License v3.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
FeedbackBots
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A small feedback bot I built on a hackathon
It is built on enterprise-grade infrastructure with Azure functions, and I published sources for the self-hosted version https://github.com/xakpc/FeedbackBots
ailab
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AI-Powered Developer Tools
Sorry about that! I should have checked before sharing that link.
It looks like Microsoft published the code on GitHub, so you might be able to deploy it via Azure. (I haven't tried it.)
https://github.com/Microsoft/ailab/blob/master/Sketch2Code/R...
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Feature detection with Lobe
I came across this project: https://github.com/microsoft/ailab/tree/master/Sketch2Code
What are some alternatives?
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Alturos.Yolo - C# Yolo Darknet Wrapper (real-time object detection)
azure-functions-university - Repository with training material to learn all about Azure Functions <⚡>
azure-functions-proxy - A simple dynamic http proxy built using azure functions
azure-webjobs-sdk - Azure WebJobs SDK
azure-functions-core-tools - Command line tools for Azure Functions
Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment - This project is part of the CS course 'Systems Engineering Meets Life Sciences I' at Goethe University Frankfurt. In this Computer Vision project, we present our first attempt at tackling the problem of traffic sign recognition using a systems engineering approach.
lt-app - React Native application for Language Transfer
links-detector - 📖 👆🏻 Links Detector makes printed links clickable via your smartphone camera. No need to type a link in, just scan and click on it.