How to use Labeled image datasets to perform an image binary classification in Azure ML Designer

Question

I try to train a model for image binary classification in Azure Machine Learning Designer.

First, I have used the Label Tool, to set a label on each images :

Then, I have exported it as an Azure ML DataSet in order to import it in my ML workflow in the designer, as you can see below :

Then, in order to apply image transformation and to train my model, I have connected my DataSet to a "convert to image directory" module :

When I execute the workflow I have the following error :

Also, I could not find any documentations about all of these modules in Azure Machine Learning Designer :

So I am not sure about my understanding of how to proceed.

Answer 1

Thanks for reaching out. Based on feedback from the product team, the image related modules are being deployed to regions this week and official docs are yet to be published (hopefully by early next week). However, in the meantime, here are some guidance on how to use 'Convert to Image Directory' module.

Convert to Image Directory (Converts data input to the internal Dataset format used by Microsoft Azure Machine Learning)

Add the Convert to Image Directory module to your experiment

Connect the image dataset as input. Supported dataset formats:

• compressed file in these extensions: '.zip', '.tar', '.gz', '.bz2'
• folder containing 1 compressed file in above valid extensions
• folder containing images

Run the experiment

Feel free to comment below if you have any further questions or concerns.