Instagram with Face Detection is a geo & photo based social media site, and I built it by React and token-based server-side user authentication (JWT). This project was bootstrapped with Create React App. In addition, I also created features, such as create/browse/search nearby posts, with Geolocation API and Google Map API. Used Google Vision API to provide a face detection model, and integrate the model with the Go service. The backend of this project was create in Golang, and used Elasticsearch (GCE) to provide geo-based search features
- Node.js
- npm
- yarn
git clone [email protected]:tingkaiwu/around-frontend.git
cd around-frontend
yarn
yarn start
- React
- Golang
- JWT
- GCE
- Elasticsearch
- Google Map API
- Google Vision API
- Geo Location API
In the project directory, you can run:
Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.
The page will reload if you make edits.
You will also see any lint errors in the console.
Launches the test runner in the interactive watch mode.
See the section about running tests for more information.
Builds the app for production to the build
folder.
It correctly bundles React in production mode and optimizes the build for the best performance.
The build is minified and the filenames include the hashes.
Your app is ready to be deployed!
See the section about deployment for more information.
Note: this is a one-way operation. Once you eject
, you can’t go back!
If you aren’t satisfied with the build tool and configuration choices, you can eject
at any time. This command will remove the single build dependency from your project.
Instead, it will copy all the configuration files and the transitive dependencies (webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except eject
will still work, but they will point to the copied scripts so you can tweak them. At this point you’re on your own.
You don’t have to ever use eject
. The curated feature set is suitable for small and middle deployments, and you shouldn’t feel obligated to use this feature. However we understand that this tool wouldn’t be useful if you couldn’t customize it when you are ready for it.