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Add rotation 90 degrees to augs #11792
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #11792 +/- ##
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- Coverage 70.58% 70.48% -0.11%
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Files 124 124
Lines 15648 15683 +35
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+ Hits 11045 11054 +9
- Misses 4603 4629 +26
Flags with carried forward coverage won't be shown. Click here to find out more. β View full report in Codecov by Sentry. |
@Burhan-Q what should I do if test failed after merging current main branch? There were no conflicts, but test didn't run. Can I rerun it? And should I just wait for a PR review at this point? |
@ArgoHA I just re-ran the test for you. I believe that you can add a comment with only the text "recheck" (no quotes) to have the tests re-run. |
@Burhan-Q sorry, I still don't understand what I need to do for this PR to be reviewed. Should I just wait? |
@ArgoHA I don't think I'll be able to provide a lot of input personally on the additions here as I'm not entirely familiar with the construction of the augmentation pipeline. I will share that at face value (I have not looked at your changes), the idea of including 90-degree rotation seems superfluous given the |
@Burhan-Q both |
This is a PR to add one more type of augmentation for detection model. It's rotation to fixed 90 degrees (+ or -). User can choose a probability of this augmentation to be applied during the training.
I find this augmentation useful and decided to quickly implement it for my custom training pipeline. As this might be useful for others - I create this PR. Probability by default will be 0, so it won't be applied.
I have read the CLA Document and I sign the CLA
Note: I only tested bboxes implementation and I am not sure if rotating image and labels from scratch was the best solution, maybe I should've used Albumentation. Let me know how to make this PR better.
π οΈ PR Summary
Made with β€οΈ by Ultralytics Actions
π Summary
Enhance your images with a twist! Introducing random 90-degree rotations for more dynamic data augmentation. π
π Key Changes
rotate90
configuration option in the default settings, allowing a chance from 0 to 1 to rotate images by 90 degrees during augmentation.RandomRotation90
class dedicated to applying a 90-degree rotation to images, bounding boxes (bboxes), segments, and keypoints.π― Purpose & Impact
rotate90
setting, developers and researchers can fine-tune how often images should be rotated, offering flexibility in data augmentation strategies. βοΈThis change could significantly benefit users working on image recognition tasks, making models more versatile and reliable across different applications.