VidyasagarMSC/image-classification-code-engine

Image classification with Code Engine and TensorFlow

Image Classification with Code Engine and TensorFlow

🔆 The code in this GitHub repo is an extension to the Solution tutorial mentioned below. You can follow the steps in the solution tutorial but instead of uploading a text file, upload an image (.jpeg, .png) to COS and you don't have to provision NLU service.

Build the container images

Before building and pushing your container images, plan your image registry

Using a private container registry

Follow the steps here to add access to a private registry

Using public Docker Hub

Run the below command to build and push three container images - frontend, backend and backend-job respectively.

./deploy.sh <DOCKER_ACCOUNT_NAME>

Note: If you don't wish to build your own container images, you can use the pre-built container images - vidyasagarmsc/*. For example,

docker pull vidyasagarmsc/frontend

Use the container images with the solution tutorial

Follow the steps in the solution tutorial and use this code sample to learn about IBM Cloud™ Code Engine by deploying an image classification application.

Note:

• Use the container images built from this code sample. Replace ibmcom/* with <ACCOUNT_NAME>/*
• 🔆 Instead of uploading a text file, upload an image (.jpeg, .png) to COS. For sample images, check the images folder in this repo.

Expected output