Add crack-seg notebook

[RizwanMunawar]

🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

Added a new tutorial and resources for crack segmentation using Ultralytics YOLO, including a step-by-step Jupyter Notebook and dataset details.

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📊 Key Changes

• New Crack Segmentation Tutorial: Introduced a Jupyter notebook for training YOLO on crack segmentation datasets, complete with setup, training, and inference.
• Dataset Support: Added details and YAML configuration for the crack segmentation dataset (3717 training, 200 validation, and 112 test images).
• Colab Integration: The new notebook is Colab-compatible for ease of experimentation.
• Demo Resources: Supplemental materials such as a dataset sample and pre-configured commands to enable smooth workflow.

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🎯 Purpose & Impact

• Simplifies Crack Detection in Infrastructure: Aimed at detecting cracks in roads, walls, or structural surfaces, helping in maintenance and safety inspections. 🚧
• Improved Accessibility: Provides users of all levels an easy, ready-to-use pipeline, empowering non-experts to leverage YOLO for segmentation tasks. 💡
• Enhances Research and Applications: Facilitates domain-specific use cases, enabling faster experimentation in civil engineering, road safety, and asset monitoring. 🚀

[UltralyticsAssistant]

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

• ✅ Define a Purpose: Clearly explain the purpose of your fix or feature in your PR description and link any relevant issues. Ensure your commit messages are clear, concise, and adhere to the project's conventions.
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For more guidance, please refer to our Contributing Guide. Feel free to leave a comment if you have any questions.

Thank you for expanding the ultralytics/notebooks project 🌟! An Ultralytics engineer will review your PR shortly. 🚀

[ambitious-octopus]

@RizwanMunawar Looks good!

[UltralyticsAssistant]

🚀 Merge Success! 🎉

Thank you, @RizwanMunawar and @ambitious-octopus, for this phenomenal contribution to expand Ultralytics' usability! Your work on the crack segmentation tutorial is a fantastic example of innovation meeting impact. The detailed notebook, accessible dataset integration, and Colab-friendly approach will empower users everywhere to apply YOLO for critical infrastructure safety.

As Henry Ford once said: "Coming together is a beginning, staying together is progress, and working together is success." Your teamwork here beautifully embodies this spirit—helping bridge technology with real-world solutions. 💡

We’re immensely grateful for your dedication and look forward to seeing the profound impact this PR will have within the community and beyond. Thank you for helping us build something that truly makes a difference! 🌟🚧