DayPack allows Machine Learning Engineers who are already using Gradio to develop web applications to further leverage their experience and develop Hybrid Mobile Applications. The goal of DayPack is to allow rapid prototyping so that OnDevice Machine Learning models can be tested and demostrated OnDevice, anywhere people go.
import gradio as gr
import daypack
dp = daypack(dp)
dp.pack()
dp.start()
The goal of DayPack is to allow rapid development of OnDevice Machine Learning models without Machine Learning engineers to have to learn C++, and for Machine Learning Engineers to be able to leverage existing Gradio applications.
- Android Studio
- An Android Device with Debugging Enabled
- XCode
- A valid developer certificate
- ios-deploy
Because the name backpack was already taken by other Python packages, and to keep with the outdoor theme of BaseWeight.
BaseWeight is a small company founded by @infil00p and @flyingoctopus. If you are interested in contacting BaseWeight regarding consulting, funding, legal, please visit [[baseweight.ai]].
Open Source Contributions such as PRs and Issues (including Feature Requests) are welcome.