Library for converting from RGB / GrayScale image to base64 and back.

Overview

Library for converting RGB / Grayscale numpy images from to base64 and back.

Installation

pip install -U image_to_base_64

Conversion

RGB to base 64

base64 = rgb2base64(rgb_image, image_format)

where image format is JPEG, PNG

Grayscale to base 64

base64 = grayscale2base64(grayscale_image)

Base64 to RGB image

rgb_image = base64_to_rgb(base64)

Base64 to Grayscale image

grayscale_image = base64_to_grayscale(base64)

Issues

For some reason I cannot convert RGB image to JPEG representation in base 64 and back without losses. => test only for PNG and not JPEG

Issues
  • CHanged package (Sourcery refactored)

    CHanged package (Sourcery refactored)

    Pull Request #2 refactored by Sourcery.

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    opened by sourcery-ai[bot] 1
  • CHanged package (Sourcery refactored)

    CHanged package (Sourcery refactored)

    Pull Request #2 refactored by Sourcery.

    If you're happy with these changes, merge this Pull Request using the Squash and merge strategy.

    NOTE: As code is pushed to the original Pull Request, Sourcery will re-run and update (force-push) this Pull Request with new refactorings as necessary. If Sourcery finds no refactorings at any point, this Pull Request will be closed automatically.

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    Run Sourcery locally

    Reduce the feedback loop during development by using the Sourcery editor plugin:

    Review changes via command line

    To manually merge these changes, make sure you're on the fixed_package branch, then run:

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    git merge --ff-only FETCH_HEAD
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    opened by sourcery-ai[bot] 1
  • About the JPEG encoding, decoding

    About the JPEG encoding, decoding

    Referring to the issue in the README, saving the image as JPEG will inevitably apply some level of compression. So decoding the image to retrieve the exact pixel intensities of the original image may not be possible unless using lossless formats like PNG

    However, I found a little parameter of PIL save subsampling while doing the JPEG compression which tries to maintain the pixel intensity, still incurring some loss but not as big as without this parameter.

    Given codebase without subsampling

    Original implementation: https://github.com/ternaus/base64ToImageConverters/blob/main/image2base64/converters.py Line number: 12 format: 'JPEG', quality=100

    im.save(buffered, format=image_format, quality=quality)
    

    RGB Image: download

    Converted Image: download

    Mean difference of the assertion test: 125.74196689386562

    With Subsampling parameter set to 0

    im.save(buffered, format=image_format, quality=quality, subsampling=0)
    

    RGB Image: download

    Converted Image: download

    Mean difference of the assertion test: 53.83414475819539

    The visual as well as numerical difference in clear. JPEG will definitely lead to losses. But subsampling=0 can preserve more details.

    opened by Nachimak28 0
Owner
Vladimir Iglovikov
Ph.D. in Physics. Kaggle GrandMaster. Co-creator of Albumentations.
Vladimir Iglovikov
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