Provide confusion matrix for the trained data

[hanannazri]

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• I have searched the HUB issues and found no similar feature requests.

Description

Provide confusion matrix for the trained data..also provide the api and model id ..so can see our trained result also in google colab and can be uploaded in github

Use case

No response

Additional

No response

[UltralyticsAssistant]

👋 Hello @hanannazri, thank you for raising an issue about Ultralytics HUB 🚀! Please visit our HUB Docs to learn more:

• Quickstart. Start training and deploying YOLO models with HUB in seconds.
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• Inference API. Understand how to use the Inference API for running your trained models in the cloud to generate predictions.

It looks like you're requesting a feature to view a confusion matrix for trained data as well as additional API/model functionalities like the capability to visualize results in Google Colab and upload them to GitHub. This sounds like a great idea 🎉! While this feature isn't currently available, we value all suggestions that improve HUB.

If this is a 🐛 Bug Report, please provide screenshots and steps to produce a minimum reproducible example (MRE) to better understand the issue.

If this is a ❓ Question or Feature Request, please expand on the use case and specific details. For example:

1. What is the structure of your data?
2. What specific workflows in Google Colab or GitHub integration are you envisioning?
3. How would you use/confusion matrix output?

Rest assured, this is an automated response 🤖, but an Ultralytics team member will follow up with personalized assistance soon. Thank you for your feedback and for helping improve Ultralytics HUB! 🚀

[sergiuwaxmann]

@hanannazri Hello!
I don't understand the question. Can you provide more information?

[gin721]

I think he probably wants the confusion matrix to be visible in the website for analysing the training and also download the results of the training process

[pderrenger]

@gin721 thank you for clarifying! 🙌 While the Ultralytics HUB doesn't currently display confusion matrices in its web interface, you can easily generate and analyze them through these methods:

1. Automatic Validation Outputs
   When training YOLO models locally, confusion matrices are automatically saved as confusion_matrix.png and confusion_matrix_normalized.png in the runs/detect/train directory. These visualizations are generated during model validation. You can find more details in the YOLO Performance Metrics guide.

2. HUB Integration Solutions
   For cloud-based analysis:

• Consider using Roboflow's model evaluation features which provide interactive confusion matrices and vector analysis
• Explore Comet ML integration for detailed performance tracking

3. Programmatic Access
   You can access model results and metrics via:

from ultralytics import YOLO

model = YOLO('yolov8n.pt')  # Load your custom model
metrics = model.val()  # Validation metrics dictionary
confusion_matrix = metrics.confusion_matrix  # Raw matrix data

For API access to your HUB models, you'll find the Model ID in the HUB interface under model details. We're continuously working to enhance our web visualization capabilities based on user feedback!

Remember that all usage of Ultralytics models requires compliance with our AGPL-3.0 license or an Enterprise License for commercial use.