visualization

[bobo0810]

Images generated by the training and validation process support visualization via tensorboard
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🛠️ PR Summary

_{Made with ❤️ by Ultralytics Actions}

🌟 Summary

Enhanced logging for TensorBoard within the Ultralytics YOLOv5 training process.

📊 Key Changes

• Added a condition to ensure only existing image files are logged.
• Extended TensorBoard logging to include images for training batch and validation results.
• Improved consistency of image logging across different platforms (WandB, ClearML, and now TensorBoard).

🎯 Purpose & Impact

• Purpose: To provide a more robust and informative logging experience for users monitoring their model's training progress.
• Impact:
  • For developers: Simplified error handling by auto-filtering non-existing image files, reducing potential file-related errors.
  • For users: Enhanced visualization of training and validation through TensorBoard, enabling easier interpretation and analysis of the model's performance. 📈

[github-actions]

👋 Hello there! We wanted to let you know that we've decided to close this pull request due to inactivity. We appreciate the effort you put into contributing to our project, but unfortunately, not all contributions are suitable or aligned with our product roadmap.

We hope you understand our decision, and please don't let it discourage you from contributing to open source projects in the future. We value all of our community members and their contributions, and we encourage you to keep exploring new projects and ways to get involved.

For additional resources and information, please see the links below:

• Docs: https://docs.ultralytics.com
• HUB: https://hub.ultralytics.com
• Community: https://community.ultralytics.com

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

[glenn-jocher]

@bobo0810 hi there! Thanks for sharing your inquiry.

To visualize training and validation images using TensorBoard, simply launch TensorBoard from the runs directory after training. As for the images you've linked, they seem to be screenshots. If you have any specific issues or questions about visualizing the training and validation process, feel free to ask.

Thanks for your support and contributions to YOLOv5! We truly appreciate it.