DeepLabV3Example
The repository contains code for a PyTorch Live object detection prototype. The prototype uses the DeepLabV3 model for the semantic segmentation task and runs on-device. It runs on Android only for now.
NOTE: This example uses an unreleased version of PyTorch Live including an API that is currently under development and can change for the final release.
How was this project bootstrapped?
The project was bootstrapped with the following command:
npx torchlive-cli@nightly init DeepLabV3Example --template react-native-template-pytorch-live@nightly
Unused packages were removed and react-native
upgraded to version 0.64.3
.
Screenshots
Android | iOS |
---|---|
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!TODO: add Screenshot of DeepLabV3Example on iOS |
Run project in emulator or on a device
Prerequisites
Install React Native development depencencies. Follow the instructions for Setting up the development environment as provided on the React Native website.
Install project dependencies
Run yarn install
to install the project dependencies.
Start Metro server
Start the Metro server, which is needed to build the app bundle (containing the transpiled TypeScript code in the <PROJECT>/src
directory).
yarn start
Android
Build the apk
for Android and install and run on the emulator (or on a physical device if connected via USB).
yarn android
See instructions on the React Native website for how to build the app in release variant.
iOS
Install CocoaPod dependencies
(cd ios && pod install)
Build the prototype app for iOS and run it in the simulator.
yarn ios
or use the following command to open the Xcode workspace in Xcode to build and run it.
xed ios/DeepLabV3Example.xcworkspace
See instructions on the React Native website for how to build the app in release scheme.