Updated the SPPF code slightly to run tiny bit faster

[chinya07]

I have checked and there are no previous PR**

2. Link Related Issues: If your PR addresses an open issue, please link it in your submission. This helps us better understand the context and impact of your contribution.

--> There is no open issue as this is just a small updation with the existing SPPF code to slightly enhance the execution speed of the module.

3. Elaborate Your Changes: Clearly articulate the purpose of your PR. Whether it's a bug fix or a new feature, a detailed description aids in a smoother integration process.

--> This is a try to slightly improve the overall execution speed of the SPPF module by streamlining the forward pass. This approach minimizes the amount of repeated code and may offer slight improvements in execution speed due to the looped pooling operations.

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For more detailed guidance and best practices on contributing, refer to our ✅ Contributing Guide. Your adherence to these guidelines ensures a faster and more effective review process.
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🛠️ PR Summary

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🌟 Summary

Optimized Spatial Pyramid Pooling layer (SPPF) introduces an iterative pooling approach for enhanced feature extraction in YOLOv5.

📊 Key Changes

• SPPF Enhancement: Shift from a static to an iterative max pooling method within the SPPF layer.
• Adjustable Pooling Levels: Introduction of a levels parameter to customize the number of pooling levels.
• Increased Flexibility: Modified channel calculations to support the new dynamic number of pooling levels.

🎯 Purpose & Impact

• Improved Performance: The iterative approach could potentially enhance feature extraction, contributing to better model accuracy and efficiency.
• Customizable Complexity: Users can adjust the pooling levels (levels parameter), allowing for a balance between computational performance and model complexity.
• Enhanced Versatility: This update may enable the SPPF layer to be more adaptable to different tasks and datasets, potentially improving overall model robustness and versatility.

🚀 This optimization not only aims to bolster the YOLOv5 model's performance but also provides users with greater control over model architecture customization, paving the way for tailored applications in various domains.

[github-actions]

👋 Hello @chinya07, thank you for submitting a YOLOv5 🚀 PR! To allow your work to be integrated as seamlessly as possible, we advise you to:

• ✅ Verify your PR is up-to-date with ultralytics/yolov5 master branch. If your PR is behind you can update your code by clicking the 'Update branch' button or by running git pull and git merge master locally.
• ✅ Verify all YOLOv5 Continuous Integration (CI) checks are passing.
• ✅ Reduce changes to the absolute minimum required for your bug fix or feature addition. "It is not daily increase but daily decrease, hack away the unessential. The closer to the source, the less wastage there is." — Bruce Lee

[glenn-jocher]

@chinya07 thank you for the fantastic work on optimizing the SPPF layer! 🚀 Your contribution emphasizes the community's crucial role in enhancing YOLOv5's performance and evolving its capabilities. This optimization indeed paves the way for better feature extraction, flexibility, and versatility, allowing users to fine-tune the balance between computational efficiency and model complexity. We appreciate your efforts in making YOLOv5 even more adaptable and efficient for a wide range of applications. Your detailed summary and the thoughtful implementation of adjustable pooling levels and iterative pooling are great examples of the innovative spirit that drives our community forward. Let's keep pushing the boundaries of what's possible together! 🌟

[glenn-jocher]

@chinya07 all tests are failing in your PR, seems like your changes have created bugs. Review and fix all of the issues before we can consider this, thank you!

[github-actions]

Thank you for your submission, we really appreciate it. Like many open-source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution. You can sign the CLA by just posting a Pull Request Comment same as the below format.

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I have read the CLA Document and I sign the CLA

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2 out of 3 committers have signed the CLA.
✅ (glenn-jocher)[https://github.com/glenn-jocher]
✅ (UltralyticsAssistant)[https://github.com/UltralyticsAssistant]
❌ @chinya07
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