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https://github.com/cassiebreviu/use-ml-to-classify-yoga-poses

This tutorial will go over how to use Azure Cognitive Services to get an image dataset and train a Custom Vision model. The repository has a simple nodejs console app that uses Bing Image Search to scrape images to a local directory based on search term(s). Then use the images scraped to create a Custom Vision model with Azure Cognitive Services.
https://github.com/cassiebreviu/use-ml-to-classify-yoga-poses

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This tutorial will go over how to use Azure Cognitive Services to get an image dataset and train a Custom Vision model. The repository has a simple nodejs console app that uses Bing Image Search to scrape images to a local directory based on search term(s). Then use the images scraped to create a Custom Vision model with Azure Cognitive Services.

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# How to Get a Dataset and Create a ML Model to Classify Yoga Poses (Using Azure Cognitive Services)

This tutorial will go over how to use Azure Cognitive Services to get an image dataset and train a Custom Vision model. The repository has a simple nodejs console app that uses Bing Image Search to scrape images to a local directory based on search term(s). Then use the images scraped to create a Custom Vision model with Azure Cognitive Services.



### Create an Azure Account

[Click here to create your account](https://azure.microsoft.com/free/?WT.mc_id=blog-github-casiljan)



### Create Bing Search Api Resource

* Go to [portal.azure.com](https://portal.azure.com/)

* Select "Create Resource"

* Select "AI + Machine Learning"

* Select "Bing Search v7"

* Complete the required fields

* Select "Create"

* When the deployment succeeds you will get a notification in the top right corner.

* Select "Go to resource"

* Select "Keys" from the left hand navigation for the resource.

* Copy the Subscription Key and paste it into the script.



### How to Run the Image Scraper Script

# Image Scraper using Bing Search Cognitive Service

Clone the repo 


`https://github.com/cassieview/Use-ML-To-Classify-Yoga-Poses.git`




`cd Use-ML-To-Classify-Yoga-Poses`



Install packages 


`npm install`



Open in VS Code 


`code .`



Add the key into the app.js script 


`const subscriptionKey = 'addyourkeyhere'`



Update the host to the endpoint you created 


`const host = 'resourcename.cognitiveservices.azure.com';`



Run the script 


`node app.js`



### Create Custom Vision Api Resource

* Go to [portal.azure.com](https://portal.azure.com/)

* Select "Create Resource"

* Search "Custom Vision"

* Select "Create"

* Complete the required fields

* Select "Create"

* When the deployment succeeds you will get a notification in the top right corner.

* Select "Go to resource"



### Create Project and Train Model

* Select "Quick Start"

* Select "Custom Vision Portal" or go to https://www.customvision.ai/projects and login

* Select 'Sign in"

* Select "New Project"

  - Enter a Name and Resource Group and 

  - Project Types: Classification

  - Classification Types: MultiClass General

  - Domains: General

* Create project

* Add and tag images

  - Select "Add Images" and navigate to the train folder for the scraped images

  - Ctrl + A to select all the images in the folder

  - Select "Open"

  - Add tag for photos to indicate the yoga pose

  - Select "Upload photos"

  - Repeat these steps for each yoga pose (class)

* Select "Train"

* Test your model

   - Select "Quick Test" from the upper right corner

   - Browse to local files and select a image from the test folder

   - The predication will appear on the right side of the window

   

### Get the Prediction Url

* Select "Performace" from the top navigation in the Custom Vision portal

* Select "Prediction Url"

* Copy the Url to either use an image url or image file

* Additionally by selecting the settings icon in the right corner will bring you to the keys and urls to call the endpoint.



### Consume the API in an App



Once the model is trained and at a satisfactory accuracy its ready to be used in your App

* Go to the Resource Group that contains the Custom Vision Resource

* There should be a resource named "YourCustomVisionResourceName_Prediction - Quick start"

* The Select "Api Reference" from the list of helpful links

* This will open a page with docs on how to call the api to get predictions from the model

* If you scroll all the way to the bottom there are code samples in multiple languages to get you started



### Test API in Postman

* Get the predction url as described above

* Select "Post" from the dropdown and paste in the url

* Go to the settings and get the Prediction Key

* In the headers add the `Prediction-key` as the key and the actual key as the value

* Auth should be set to no auth

* Select Body > Raw > Json

* Paste in the following Json

``{

  "Url": "UrlForImageGoesHere"

}``

* Send Request



## Helpful Doc Links



[Quickstart: Search for images with the Bing Image Search SDK for Node.js](https://docs.microsoft.com/en-us/azure/cognitive-services/bing-image-search/image-search-sdk-node-quickstart?WT.mc_id=github-talk-cassieb)



[Quickstart: Create an image classification project with the Custom Vision Node.js SDK](https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/node-tutorial?WT.mc_id=github-talk-cassieb)



[Cognitive Service Bing Search Docs](https://docs.microsoft.com/en-us/azure/cognitive-services/bing-web-search?WT.mc_id=learn-docs-cassieb)



[Cognitive Service Custom Vision Docs](https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/home?WT.mc_id=github-talk-cassieb)



[Create a Node.js app in Azure App Service on Linux](https://docs.microsoft.com/en-us/azure/app-service/containers/quickstart-nodejs?WT.mc_id=github-talk-cassieb)