Add PP-YOLOE+ Params and FLOPs

[glenn-jocher]

🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

Minor table cleanup for accuracy in comparison docs! 📝✨

📊 Key Changes

• Fixed column alignment and formatting across several comparison tables for YOLOv5, YOLOv6, YOLOv7, YOLOv8, DAMO-YOLO, PP-YOLOE, YOLO11, YOLOX, and EfficientDet.
• Resolved inconsistencies in FLOPs and params data alignment, ensuring data is presented in the correct columns.

🎯 Purpose & Impact

• Improved Readability: Cleaner, more professional presentation of performance benchmarking data. 🧹✨
• Reduced Confusion: Users can now interpret model stats more accurately without misaligned columns. 🙌
• Enhanced Comparisons: Ensures fair and accurate comparisons between different object detection models for developers and researchers. 🔍✅

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Name	Status	Preview	Comments	Updated (UTC)
docs	✅ Ready (Inspect)	Visit Preview	💬 Add feedback	Jan 28, 2025 8:36am

[UltralyticsAssistant]

👋 Hello @glenn-jocher, thank you for submitting an ultralytics/docs 🚀 PR! To ensure a seamless integration of your work, please review the following checklist:

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[UltralyticsAssistant]

🎉 PR Merged! Huge thanks, @glenn-jocher, for your meticulous work in refining our comparison tables. Your attention to detail has brought clarity and professionalism to our benchmarking data—an invaluable asset to the community. 🙌✨

As Leonardo da Vinci once said, "Details make perfection, and perfection is not a detail." Your contribution exemplifies this beautifully! Here's to empowering developers and researchers with clearer, more accurate insights. 🚀🔍💡