cedric
November 6, 2018, 6:04am
3
A bit of background what is this tool for and why we need it?
hayder78, init_27 and I are working together in the part 1, v3 course project in our virtual study group.
https://hackernoon.com/anothernothotdog-280ee5b86fb3
Share your work here ✅ - #316 by init_27 (accessible only to part1-v3 participants)
Instead of doing the Lesson2 homework-which was trying web deployment of a model, we- a few members of the Fast.ai Asia Virtual study group are trying building a mobile app (everything to run on the phone) : “Another Not Hotdog” app, but using PyTorch.
Our goal of starting this project:
Make it easier to ship and test your neural network model in PyTorch on mobile devices.
Please see my GitHub repo for more details:
# Fast.ai Mobile Camera
:tada: Check out a working PyTorch-Caffe2 implementation on mobile: :tada:
- [Android Camera app demo (video)](https://youtu.be/TYkoaVNCMos)
**Guide - How I Shipped a Neural Network on Android/iOS Phones with PyTorch and Android Studio/Xcode**
I'll walk you through every step, from problem all the way to building and deploying the Android/iOS app to mobile phones.
Learn how to ship SqueezeNet from PyTorch to Caffe2 + Android/iOS app. Please follow the tutorials in order from top to bottom:
1. Get started with an introduction to [Open Neural Network Exchange format (ONNX)](https://onnx.ai/) in this Jupyter [notebook](https://nbviewer.jupyter.org/github/cedrickchee/data-science-notebooks/blob/master/notebooks/deep_learning/fastai_mobile/onnx_from_pytorch_to_caffe2.ipynb).
2. Putting it all together. Ship a SqueezeNet from PyTorch to Android. Please take a look at this [notebook](https://nbviewer.jupyter.org/github/cedrickchee/data-science-notebooks/blob/master/notebooks/deep_learning/fastai_mobile/shipping_squeezenet_from_pytorch_to_android.ipynb).
- Jump to the Android project for AI Camera app tutorial in this [notebook](https://nbviewer.jupyter.org/github/cedrickchee/data-science-notebooks/blob/master/notebooks/deep_learning/fastai_mobile/shipping_squeezenet_from_pytorch_to_android.ipynb#Fast.ai-Mobile-Camera-Project).
3. ~~Ship a SqueezeNet from PyTorch to iOS (TBD).~~
[Source code for the Android app](https://github.com/cedrickchee/pytorch-android).
**Updates:**
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What is happening in this project that such tool is valuable? We need tool to visualize and debug our ONNX graph and see the network architecture:
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