add smoothing line to results.png to improve readability

[PetervanLunteren]

This PR contains a very small addition to the original code (+ 2 lines) and does not interfere with the machine learning process whatsoever. It adds a smoothing line on top of the original plots in the results.png. With this smoothing line I hope to improve plot readability for users and provide a better insight into when their model has the best fit, and where their model is under- or overfitted.

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🤖 Generated by Copilot at e32f5ee

Summary

📈🔬🎨

This pull request enhances the plot_results function in utils/plots.py by applying a Gaussian filter to smooth the plot lines. This makes the results easier to visualize and compare.

To plot results with more finesse
We use gaussian_filter1d to smooth and compress
The lines become clearer
And the peaks are nearer
This feature is a great success

Walkthrough

• Import and apply gaussian_filter1d function to smooth plot lines in plot_results (link, link)

🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

Improvement in visualization of training results with smoothed lines.

📊 Key Changes

• Imported gaussian_filter1d from scipy.ndimage.filters.
• Added smoothed line plots in the plot_results function using Gaussian filter.

🎯 Purpose & Impact

• Purpose: To provide a clearer visual representation of the model's training performance over time by smoothing out the results.
• Impact: Users can more easily identify trends and patterns in the results, as the smoothing helps to reduce noise in the visualization. This can be particularly helpful when presenting results to non-expert stakeholders or for better assessing the model's behavior during training.