Enhance `classify` results plotting

[RizwanMunawar]

@glenn-jocher Hi, this PR enhances the visualization of classification results. Currently, there are no background rectangles or distinct text colours for each classified object. This PR introduces these features. Thanks

Sample#	Old version	This PR
01

🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

Enhanced visualizations by improving multi-line text rendering with color-coded backgrounds for better readability. 🖼️✨

📊 Key Changes

• Updated the annotator.text function to remove hardcoded font color settings, offering more flexibility.
• Improved text rendering to color-code each line of multi-line text, using background rectangles for better distinction.
• Adjusted layout logic to handle multi-line text more elegantly by dynamically calculating dimensions for each line.

🎯 Purpose & Impact

• Purpose: Improves the clarity and visual appeal of plotted text, particularly in annotations with multiple lines.
• Impact: Users benefit from enhanced readability of annotations, especially in cases involving detailed information like top predictions. This makes analyzing plots easier and more user-friendly. 👀✅

[UltralyticsAssistant]

👋 Hello @RizwanMunawar, thank you for submitting an ultralytics/ultralytics 🚀 PR! Your contribution to enhancing visualization in classification plots is greatly appreciated. 🎨 To ensure a smooth process, please review the following checklist:

• ✅ Define a Purpose: Thank you for clearly explaining the purpose of your PR and providing detailed descriptions alongside examples! 🌟 Ensure you link any relevant issues if applicable.
• ✅ Synchronize with Source: Confirm your PR is synchronized with the ultralytics/ultralytics main branch. If it's behind, please update it by clicking the 'Update branch' button or by running git pull and git merge main locally.
• ✅ Ensure CI Checks Pass: Verify all Ultralytics Continuous Integration (CI) checks are passing. If any checks fail, kindly address the issues.
• ✅ Update Documentation: For new features or modifications, ensure you update the relevant documentation.
• ✅ Add Tests: If applicable, please include or update tests to cover your changes and confirm that all tests pass successfully.
• ✅ Sign the CLA: Ensure you have signed our Contributor License Agreement if this is your first PR. To do so, please write "I have read the CLA Document and I sign the CLA" in a new comment.
• ✅ Minimize Changes: Keep your changes to the minimum necessary for your contributions to enhance maintainability and review clarity. "It is not daily increase but daily decrease, hack away the unessential." — Bruce Lee

📊 For further guidance, please refer to our Contributing Guide. If you encounter any issues or have additional questions, feel free to comment here, and we'll assist you.

🌟 Your proposed updates to text rendering and plotting aesthetics look promising. Dynamic text coloring and background rectangles will undoubtedly improve the visualization and user experience. Thank you for including a well-documented diff and comparative media to showcase your work. 🖌️✨

This is an automated response to help streamline the process, but rest assured that an Ultralytics engineer will review your PR in detail and provide further guidance soon. 🚀 Thank you for contributing to Ultralytics!

[codecov[bot]]

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 72.75%. Comparing base (c1860b8) to head (ef20fa1).

Additional details and impacted files

```diff @@ Coverage Diff @@ ## main #18978 +/- ## ========================================== - Coverage 73.05% 72.75% -0.31% ========================================== Files 129 129 Lines 17486 17484 -2 ========================================== - Hits 12775 12721 -54 - Misses 4711 4763 +52 ``` | [Flag](https://app.codecov.io/gh/ultralytics/ultralytics/pull/18978/flags?src=pr&el=flags&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=ultralytics) | Coverage Δ | | |---|---|---| | [Benchmarks](https://app.codecov.io/gh/ultralytics/ultralytics/pull/18978/flags?src=pr&el=flag&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=ultralytics) | `34.07% <0.00%> (+<0.01%)` | :arrow_up: | | [GPU](https://app.codecov.io/gh/ultralytics/ultralytics/pull/18978/flags?src=pr&el=flag&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=ultralytics) | `37.70% <44.44%> (-0.24%)` | :arrow_down: | | [Tests](https://app.codecov.io/gh/ultralytics/ultralytics/pull/18978/flags?src=pr&el=flag&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=ultralytics) | `66.60% <100.00%> (-0.31%)` | :arrow_down: | Flags with carried forward coverage won't be shown. [Click here](https://docs.codecov.io/docs/carryforward-flags?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=ultralytics#carryforward-flags-in-the-pull-request-comment) to find out more.

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

[sentry-io[bot]]

🔍 Existing Issues For Review

Your pull request is modifying functions with the following pre-existing issues:

📄 File: ultralytics/engine/results.py

Function	Unhandled Issue
plot	error: OpenCV(4.10.0) :-1: error: (-5:Bad argument) in function 'polylines' ultralytics.... Event Count: 1
plot	TypeError: Argument 'thickness' is required to be an integer ultralytics.utils.plotting ... Event Count: 1

---

_{Did you find this useful? React with a 👍 or 👎}

[Laughing-q]

@RizwanMunawar yeah nice idea! Personally I do have issues of current style of classify plotting when the background is white(basically can not see the plotted names). I think you could start this PR with the box_style argument we already have for Annotator.text method: https://github.com/ultralytics/ultralytics/blob/c5ac5548aeac8ed1554ef6224bd3d839974abc5b/ultralytics/utils/plotting.py#L494-L494 which I created this style(similar with the one you proposed in this PR) for visualizations when training/validating classification task. A val_batch0_pred.jpg example below: Ideally if we want this style we could implement this by directly adding box_style=True here: https://github.com/ultralytics/ultralytics/blob/c5ac5548aeac8ed1554ef6224bd3d839974abc5b/ultralytics/engine/results.py#L565-L565 and pass different color based on the predicted categories, instead of (255, 255, 255).

[RizwanMunawar]

@Laughing-q Wow, I didn't realize the same code had been used for plotting during the training. Your idea looks good, Let me test it.

Edit: BTW, I just performed testing and I have noticed the changes we made are not used in training and validation, these are only related to predictions i.e yolo classify predict. Additionally If I set box_style=True, annotator.text([x, x], text, txt_color=(255, 255, 255), box_style=True). I am getting the mentioned output.

I think the main issue here is, that text includes not a single class, it's a combination of 5 classes, which I believe can not be plotted directly so loop will be required.

[Laughing-q]

@RizwanMunawar I've updated the code a bit to reuse the box_style argument, currently we just add box_style=True in Results.plot() for classification then it's all good.

[RizwanMunawar]

@Laughing-q ok, I will test it sometime today. In the meantime can you please attach some output results with new changes you made?

[Laughing-q]

@RizwanMunawar here it is! with box_style=True: box_style=False:

Also the training/validation plots become using the same red color, but I think it's ok since the category context is still different.

[RizwanMunawar]

@Laughing-q ok, Thanks. so this PR is ready?

[Laughing-q]

good to go from my side

[RizwanMunawar]

@Laughing-q ok thanks, @glenn-jocher Hi, can you please take a look, If everything is good, maybe we can merge this PR. Thanks