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improve image quality of cropped jpg files by disabling chroma subsampling #7007

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LaserBorg opened this issue Mar 16, 2022 · 6 comments · Fixed by #7008
Closed
2 tasks done

improve image quality of cropped jpg files by disabling chroma subsampling #7007

LaserBorg opened this issue Mar 16, 2022 · 6 comments · Fixed by #7008
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enhancement New feature or request

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@LaserBorg
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Search before asking

  • I have searched the YOLOv5 issues and found no similar feature requests.

Description

opencv was used to save ROI crops, but imwrite is limited at jpg quality since it uses 2x2 chroma subsampling, often reffered to as "4:2:2" (-> jpg is YUV color space) even when setting cv2.IMWRITE_JPEG_QUALITY to 100.
Quality loss is clearly visible when working on images with highly saturated colors or sharp color changes.

I propose using pillow to write jpg files, with subsampling flag set to False. It is already in the requirements and the existing numpy matrix can easily get converted to pil format.

Use case

image quality of the crops is crucial when cropped output files are further used as training data, while jpg compression still offers great benefit-cost ratio in filesize and compression speed compared to lossless (png) or even uncompressed (bmp) formats.

Additional

I have a PR ready.

Are you willing to submit a PR?

  • Yes I'd like to help by submitting a PR!
@LaserBorg LaserBorg added the enhancement New feature or request label Mar 16, 2022
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github-actions bot commented Mar 16, 2022

👋 Hello @LaserBorg, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

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@glenn-jocher
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glenn-jocher commented Mar 20, 2022

@LaserBorg good news 😃! Your original issue may now be fixed ✅ in PR #7008. To receive this update:

  • Gitgit pull from within your yolov5/ directory or git clone https://github.com/ultralytics/yolov5 again
  • PyTorch Hub – Force-reload model = torch.hub.load('ultralytics/yolov5', 'yolov5s', force_reload=True)
  • Notebooks – View updated notebooks Open In Colab Open In Kaggle
  • Dockersudo docker pull ultralytics/yolov5:latest to update your image Docker Pulls

Thank you for spotting this issue and informing us of the problem. Please let us know if this update resolves the issue for you, and feel free to inform us of any other issues you discover or feature requests that come to mind. Happy trainings with YOLOv5 🚀!

@Mob-Nikhil898
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The current save_one_box() is not saving anything in the desired folder.

@glenn-jocher
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glenn-jocher commented May 8, 2022

@Mob-Nikhil898 saving crops works correctly.

Screen Shot 2022-05-08 at 12 47 56 PM

We've created a few short guidelines below to help users provide what we need in order to start investigating a possible problem.

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For Ultralytics to provide assistance your code should also be:

  • Current – Verify that your code is up-to-date with GitHub master, and if necessary git pull or git clone a new copy to ensure your problem has not already been solved in master.
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If you believe your problem meets all the above criteria, please close this issue and raise a new one using the 🐛 Bug Report template with a minimum reproducible example to help us better understand and diagnose your problem.

Thank you! 😃

@Mob-Nikhil898
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Thank you bro, I messed up my detect.py settings that's why it was not saving . My bad.

@glenn-jocher
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@Mob-Nikhil898 no worries at all! It happens to the best of us 😊. If you encounter any other issues or have further questions, feel free to ask. Happy to help anytime!

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3 participants