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I need to build an image classification model in Azure ML- which initially takes an input from Phone (A check in app which takes information like ID and also we will capture the image of the person- Here ID is used to tag the image) which will be redirected to data storage. once it's done, we will upload the n number of images of person to the data storage, it should able to classify the image based on facial recognition and should categorize as separate image folder for different person( Just like Google Photos). In short, If there's a 100 unique people come for check in and during the event if we click random images of these 100 unique persons, when we load this data to blob - it should categorize the persons separately.

Can I go with approach-

1.Check in app-- Loads image with tag 2.Blob- store the image 3. custom vison- ML classifier 4.Loding n number of images to blob 5. comparing the image with check in app loaded image and categorizing as album just like google photos 6. Loading albums to app to make attendees to see the images

Please guide me with the solution and services need to be considered to make this possible in azure

Thanks in adavance

Thej
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1 Answers1

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Within Azure you need to look into Cognitive Services, with more information located here: https://azure.microsoft.com/en-us/services/cognitive-services/

Azure Cognitive Services is substantially surfaced as a series of API endpoints. In your example, you can post images from the mobile device to the Azure endpoint, where you can train the services to recognize individuals and have it return a JSON package of the people in the picture, or have it place rectangles around those people in a picture, etc. Other Cognitive Services include those related to images, speech, video, etc.

The Face API maps to your scenario well: https://azure.microsoft.com/en-us/services/cognitive-services/face/

https://azure.microsoft.com/en-us/services/cognitive-services/computer-vision/#overview

DanielG
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