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Optimize Docs images (#15900)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Muhammad Rizwan Munawar 2024-08-30 05:52:10 +05:00 • committed by GitHub
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6
docs/en/guides/hyperparameter-tuning.md
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@ -20,7 +20,7 @@ Hyperparameters are high-level, structural settings for the algorithm. They are
- **Architecture Specifics**: Such as channel counts, number of layers, types of activation functions, etc.
<p align="center">
<img width="640" src="https://user-images.githubusercontent.com/26833433/263858934-4f109a2f-82d9-4d08-8bd6-6fd1ff520bcd.png" alt="Hyperparameter Tuning Visual">
<img width="640" src="https://github.com/ultralytics/docs/releases/download/0/hyperparameter-tuning-visual.avif" alt="Hyperparameter Tuning Visual">
</p>
For a full list of augmentation hyperparameters used in YOLOv8 please refer to the [configurations page](../usage/cfg.md#augmentation-settings).
@ -157,7 +157,7 @@ This is a plot displaying fitness (typically a performance metric like AP50) aga
- **Usage**: Performance visualization
<p align="center">
<img width="640" src="https://user-images.githubusercontent.com/26833433/266847423-9d0aea13-d5c4-4771-b06e-0b817a498260.png" alt="Hyperparameter Tuning Fitness vs Iteration">
<img width="640" src="https://github.com/ultralytics/docs/releases/download/0/best-fitness.avif" alt="Hyperparameter Tuning Fitness vs Iteration">
</p>
#### tune_results.csv
@ -182,7 +182,7 @@ This file contains scatter plots generated from `tune_results.csv`, helping you
- **Usage**: Exploratory data analysis
<p align="center">
<img width="1000" src="https://user-images.githubusercontent.com/26833433/266847488-ec382f3d-79bc-4087-a0e0-42fb8b62cad2.png" alt="Hyperparameter Tuning Scatter Plots">
<img width="1000" src="https://github.com/ultralytics/docs/releases/download/0/tune-scatter-plots.avif" alt="Hyperparameter Tuning Scatter Plots">
</p>
#### weights/