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Cleaned up input to TextImage #2387

Merged
merged 1 commit into from
Mar 5, 2025
Merged

Cleaned up input to TextImage #2387

merged 1 commit into from
Mar 5, 2025

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ternaus
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@ternaus ternaus commented Mar 5, 2025

Summary by Sourcery

Refactor TextImage transform to improve handling of font colors for different image types, including grayscale and multi-channel images. This change ensures compatibility and correct color representation across various image modes.

Enhancements:

  • Improve font color handling in TextImage transform for grayscale and multi-channel images.
  • Update the TextImage transform to accept a tuple of floats for the font color, representing RGB values.
  • Modify the TextImage transform to pad or truncate font color values to match the number of image channels.
  • Update test cases to use tuple colors

Tests:

  • Add test cases for grayscale and single-channel images.

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sourcery-ai bot commented Mar 5, 2025

Reviewer's Guide by Sourcery

This pull request focuses on cleaning up the input to the TextImage transform, specifically around the font_color parameter. The changes involve standardizing the input type for font_color to a tuple of floats (RGB), adapting the color handling logic for different image modes (grayscale, RGB, multi-channel), and updating the test cases and documentation to reflect these changes. The goal is to simplify the API, improve consistency, and ensure correct color representation across different image types.

Sequence diagram for drawing text on a multi-channel image

sequenceDiagram
    participant TextImage
    participant draw_text_on_multi_channel_image
    participant PIL Image

    TextImage->>draw_text_on_multi_channel_image: image, metadata_list
    loop for each channel
        draw_text_on_multi_channel_image->>PIL Image: text(position, text, font=font, fill=font_color[channel_id])
    end
    draw_text_on_multi_channel_image-->>TextImage: stacked image
Loading

File-Level Changes

Change Details Files
Standardized and simplified the font_color parameter in TextImage transform to accept a tuple of floats representing RGB values, ensuring consistency and removing ambiguity in color handling.
  • Modified TextImage's __init__ method to accept font_color as a tuple of floats (RGB).
  • Updated InitSchema to reflect the change in font_color type to a tuple of floats.
  • Removed the font color choice logic in preprocess_metadata.
  • Updated the test cases to use tuple-based font colors.
  • Updated the example in the documentation to use a tuple for font color.
albumentations/augmentations/text/transforms.py
tests/test_text.py
tests/aug_definitions.py
Improved handling of font_color in draw_text_on_pil_image to adapt to different image modes (grayscale, RGB) and ensure correct color representation.
  • Added logic to handle grayscale images by averaging RGB values if a tuple is provided.
  • Ensured that font_color is converted to a tuple of integers for RGB and other modes.
albumentations/augmentations/text/functional.py
Enhanced draw_text_on_multi_channel_image to handle font colors with different lengths compared to the number of image channels, padding or truncating as necessary.
  • Implemented padding with zeros if the font color tuple has fewer values than image channels.
  • Implemented truncation if the font color tuple has more values than image channels.
  • Converted font color values to integers for PIL compatibility.
albumentations/augmentations/text/functional.py

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Hey @ternaus - I've reviewed your changes - here's some feedback:

Overall Comments:

  • The changes to handle font color based on image mode and number of channels look good.
  • Consider adding a check to ensure the font file exists before attempting to use it.
Here's what I looked at during the review
  • 🟢 General issues: all looks good
  • 🟢 Security: all looks good
  • 🟢 Testing: all looks good
  • 🟡 Complexity: 1 issue found
  • 🟢 Documentation: all looks good

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@ternaus ternaus merged commit 3363e0a into main Mar 5, 2025
14 checks passed
@ternaus ternaus deleted the fix_text_image branch March 5, 2025 21:08
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1 participant