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qubvel avatar qubvel commented on June 29, 2024 1

You have to pass for each image (e.g. shape is HxWx3) corresponding mask (labeled image, where each pixel assigned to specific class) with shape HxWxN, where N is a number of classes you have (+ background for multiclass problems). Read more about semantic segmentation problem.

If have more than one class pass kwargs: classes=<num_classes>, activation='softmax'

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qubvel avatar qubvel commented on June 29, 2024 1

You`re welcome)
P.S. Great repo with information about datasets and networks for semantic segmentation https://github.com/mrgloom/awesome-semantic-segmentation

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chm60 avatar chm60 commented on June 29, 2024

Thanks :) - That saved me a lot of time. Another question if I may, do you have any resources that already contain labelled training images in that specific format, i'm struggling to find a reliable and accurate dataset.

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qubvel avatar qubvel commented on June 29, 2024

Try this one πŸ˜„

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chm60 avatar chm60 commented on June 29, 2024

Thank you again :D

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