I built a simple inference API originally backed by a CNN ResNet50, but currently InceptionV3 is running. It is available at http://datascience.lays.pro.
Note : The gif was sped up at inference time, as the model runs on the free AWS tier with a t2.micro. Real inference time is about 15 seconds for the three images.
Inception-v3 is a convolutional neural network that is trained on more than a million images from the ImageNet database. It can classify images into 1000 object categories, such as keyboard, mouse, pencil, and many animals. As a result, the network has learned rich feature representations for a very wide range of images. The network has an image input size of 299x299.
Currently, the API is running on a simple t2.micro on AWS EC2 along with my personal website. The back-end code is also on my github.
This project was bootstrapped with Create React App.
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 minimizes, optimizes the build for the best performance.
The app is ready to be deployed ! Just point your webserver to the index.html page of the build folder.