Understand Image Classification

By Ashwin Venugopal -

 




Introduction

A model is trained to predict a class label for an image based on its contents in the computer vision process known as image classification. The class label typically refers to the image's primary subject. Models can be trained for either multilabel classification (where each image may be associated with many labels) or multiclass classification (where there are multiple classes but each picture may belong to just one class).

Train an Image Classifier

The Azure AI Custom Vision site, the Azure AI Custom Vision REST API or SDK, or a combination of the two can be used to train an image classification model using the Azure AI Custom Vision service. To train your model, you will usually use the Azure AI Custom Vision portal.

The portal provides a graphical interface that you can use to:

  • Create an image classification project for your model and associate it with a training resource.

  • Upload images, assigning class label tags to them.

  • Review and edit tagged images.

  • Train and evaluate a classification model.

  • Test a trained model.

  • Publish a trained model to a prediction resource.

The REST API and SDKs enable you to perform the same tasks by writing code, which is useful if you need to automate model training and publishing as part of a DevOps process.

Conclusion

We have successfully learnt about basics of training a image classifier.

 

 






































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