Prevent the outbreak of infection

Call for Code Challenge 2019

Application Summary

Wiki

Deployment guide

Prerequisites

Pleaase create a custom model on Watson Visual Recognition using Watson Studio.

If you don't use Watson Studio, I recomend that you get IBM Cloud Lite Account. And you can try custom model useing following contents. https://www.ibm.com/support/knowledgecenter/DSXDOC/analyze-data/visual-recognition-create-model.html

In this project, we created a custom image model using images that assumes gram stain bacteria image.

Frontend

This Frontend app is pwa. development and test used Nginx on IBM Cloud IaaS Virtual Server.

ex https://yourserver.com

Deploy the contents of the "frontend directory" on "/usr/share/nginx/html".

Backend

This Backend uses Node-RED.You need to be able to access Node-RED from Nginx using a reverse proxy.

ex https://yourserver.com/red

Please add the following nodes to Node-RED.

You have Node-RED ready and Please import "flows_web_form_image_recognition_stable.json" to Node-RED from backend directory.

Node-RED node settings

node name display name operation
function node Select Custom Model ID replace with your custom model ID
visual recognition node visual recognition set your Watson Visual Recognition API Key and Endpoint URL
cloudantplus out node log_recog_image connect your IBM Cloudnat instance
http request node http request Set your Slack Incoming webhook URL

List display and download method of CSV file

If you want to download recognition data as a CSV file, Please import "notebook_datalistview.ipynb" to Jupyter Notebook. You can use Jupyter Notebook on Watson Studio.