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Image processing

Digital image processing is the use of algorithms to make computers analyze the content of digital images.

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albumentations
BloodAxe
BloodAxe commented Oct 6, 2021

Enhancement

A discussion in #614 revealed a good place for improvement - we should ensure that input image is continuous upon start of the augmentation pipeline. This could be implemented by adding image = np.ascontiguousarray(image) to image and mask targets.

A proposed place to add this call - somewhere at the beginning of A.Compose.__call__.

good first issue
VolkerH
VolkerH commented Apr 8, 2022

Splitting clumped objects after binarization/thresholding (e.g. touching cells or grains) using distance transform and seeded watershed is a very common operation when using tradiitonal (non-machine learning) segmentation. I just noticed that there is no tutorial covering this use case in the tutorials gallery.
The "coin" example is not very useful in that regard as everything is well separated.

AbhinavTuli
AbhinavTuli commented Mar 22, 2022

🚨🚨 Feature Request

  • A new implementation (Improvement, Extension)

Is your feature request related to a problem?

Currently, if a user tries to access an index that is larger than the dataset length or tensor length, an internal error is thrown which is not easy to understand.

Description of the possible solution

We can catch the error and throw a more descriptive e

enhancement good first issue