MAX-Fashion-MNIST

Classify fashion and clothing items.

Data Source:

IBM Developer - Data Asset Exchange

Curated free and open datasets under open data licenses for enterprise data science.

Link to download: https://developer.ibm.com/exchanges/data/all/fashion-mnist/

Framework

The model is developed using the Tensorflow framework.

Labels

Each training and test example is assigned to one of the following labels:

Label	Description
0	T-shirt/top
1	Trouser
2	Pullover
3	Dress
4	Coat
5	Sandal
6	Shirt
7	Sneaker
8	Bag
9	Ankle boot

Pre-requisite

Follow the process provided in the MAX-Skeleton to provide REST API to the your model inference code.
Basics of docker
OpenShift

What is Source-to-Image(S2I)?

Source-to-Image is a toolkit and workflow for building reproducible container images from the source code. S2I produces ready-to-run docker images by injecting source code into a container image and letting the conainer prepare that source code for execution.

Steps

Create a folder .s2i and add an file environment.
Update the environment file with the script name you wish to run to start your application. Here it is app.py. Copy the below code in the file:

APP_FILE=app.py

Login to your OpenShift cluster and open the web console
Go to Developer view and click on +Add. We will be building the image from the source code stored in Git. Select From Git.
Provide link to the source code stored in the git. Tool can automatically detect the builder image, make sure Python is selected. Provide name for the application and click Create.
Application will start to build. You can view the logs by clicking on View Logs.
Once built, click on the route and launch the application.

SSaishruthi / MAX-Fashion-MNIST-OpenShift