Watson Visual Recognition Custom Classifier

Overview

This flow builds a very simple web page / form that prompts the user to create a Watson Visual Recognition Custom Classifier. The web form requires a name for the custom classifier, prompts the user to upload a training set of >10 images of an object and >10 images of a negative training set.

The flow then uploads the images, creates two zip files and finally calls the Watson Visual Recognition Custom Classifier API.

To test the Visual Recognition model, the form optionally prompts for an image URL to be analyzed.

To test the Visual Recognition model, the form optionally prompts for an image to upload to be analyzed.

Watson Visual Recognition Web Form Flow

Here is the web application / form it creates: Watson Visual Recognition Web Form

Prerequistes

Register for a free IBM Cloud Account
Log into IBM Cloud
Create a Watson Visual Recognition service
Returned to the IBM Cloud Resources Dashboard
Click on your Watson Visual Recognition instance
Copy the Watson Visual Recognition API key to your clipboard
This flow requires node-red-contrib-zip and node-red-node-watson

Deploy on IBM Cloud Node-RED Starter Kit or Node-RED local

This flow will run in the IBM Cloud Node-RED Starter Kit or on a local instance of Node-RED. You will need to either bind the Watson Visual Recognition service to your IBM Cloud application or paste the Watson Visual Recognition API key into the Watson Visual Recognition nodes in the flow.

Testing your Watson Visual Recognition Custom Classifier with Node-RED Web App

This flow creates a Node-RED web form at http://127.0.0.1:1880/visualrecognition or http://your-node-red-app.mybluemix.net/visualrecognition which you can use to upload an image or paste a URL link to analyze.

Testing your Watson Visual Recognition Custom Classifier model

Open your Watson Visual Recognition instance
Click on Create a Custom Model
Scroll down to the Custom Models section and click on Test to open Watson Studio
Click on the Test tab
Upload test images to validate your trained model

Note: some third-party nodes may appear with blank styling, and not as they appear in the Node-RED Editor.

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Watson Visual Recognition is Training a custom classifier","tot":"str"}],"action":"","property":"","from":"","to":"","reg":false,"x":740,"y":500,"wires":[["56ef5dbe.d9afbc"]]},{"id":"94f3c37.b02ff4","type":"debug","z":"7eeff30a.6e3d1c","name":"","active":true,"tosidebar":true,"console":false,"tostatus":false,"complete":"true","targetType":"full","x":730,"y":540,"wires":[]},{"id":"972816d2.00f088","type":"visual-recognition-util-v3","z":"7eeff30a.6e3d1c","name":"","vr-service-endpoint":"https://gateway-a.watsonplatform.net/visual-recognition/api","image-feature":"createClassifier","x":500,"y":700,"wires":[["f6c7cbd7.78b798","ba09e21c.8ead08"]]},{"id":"47169bc6.ad95dc","type":"function","z":"7eeff30a.6e3d1c","name":"Prepare to Create a Classifier","func":"// Create a Classifier\n//  Provide the following input :\n//   msg.params[\"name\"] : a string name that will be used as prefix for the returned classifier_id (Required)\n//   msg.params[\"{classname}_positive_examples\"] : a Node.js binary Buffer of the ZIP that contains a minimum of 10 images. 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Created 6 years, 4 months ago

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johnwalicki

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