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Dataset Viewer visualization issue #965

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WhoIsElMasri opened this issue Jan 1, 2025 · 2 comments
Open
1 task done

Dataset Viewer visualization issue #965

WhoIsElMasri opened this issue Jan 1, 2025 · 2 comments
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bug Something isn't working HUB Ultralytics HUB issues

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@WhoIsElMasri
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Search before asking

  • I have searched the HUB issues and found no similar bug report.

HUB Component

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Bug

Hey together, I am experimenting around and found some visualization issues of the HUB dataset viewer for this dataset:
synthetic_dataset.zip

Here you can see that the masks are going crazy:
Screencast from 2025-01-01 14-49-16.webm

Environment

  • Ubuntu 24
  • Firefox 133.0.3 (64-bit)

Minimal Reproducible Example

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Additional

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@WhoIsElMasri WhoIsElMasri added the bug Something isn't working label Jan 1, 2025
@UltralyticsAssistant UltralyticsAssistant added the HUB Ultralytics HUB issues label Jan 1, 2025
@UltralyticsAssistant
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👋 Hello @WhoIsElMasri, thank you for raising an issue about Ultralytics HUB 🚀! We appreciate your feedback and are here to help.

From your description, it seems like you've encountered some visualization issues with the dataset viewer. To help us address this issue more effectively, could you provide a minimal reproducible example (MRE)? This includes a description of the dataset configuration and any specific steps that lead to the problem, as well as ensuring that the files shared are representative of the bug.

If this is a 🐛 bug report, screenshots or screencasts (like the one you uploaded) are very helpful in identifying the issue. For any ❓ questions, please include additional details such as the dataset's structure, size, or specifics of your use case to assist us in understanding the context.

This is an automated response, but rest assured, an Ultralytics engineer will review your report promptly and assist you further. Thank you for your patience! 😊

@pderrenger
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@WhoIsElMasri thank you for reporting this issue and providing the dataset and screencast for reference! Let's work together to resolve the dataset visualization problem in the Ultralytics HUB dataset viewer.

First, here are a few steps to help identify the root cause:

  1. Dataset Validation: Ensure that the dataset adheres to the expected format for Ultralytics HUB. You can use the check_dataset function from the Ultralytics library to check for any errors in your dataset. Here's an example:

    from ultralytics.hub import check_dataset
    
    check_dataset("path/to/synthetic_dataset.zip", task="segment")  # Replace with the correct task

    This will validate the dataset structure and provide feedback if there are issues. For more details, refer to the dataset validation documentation.

  2. Browser Cache and Compatibility: Since you're using Firefox 133.0.3, try clearing your browser cache or testing the visualization in another browser (e.g., Chrome) to rule out browser-specific issues.

  3. Software Version: Ensure you are using the latest version of Ultralytics HUB and the ultralytics Python package. Visualization issues may already be addressed in recent updates. You can upgrade the library using:

    pip install --upgrade ultralytics
  4. Dataset Debugging: If the issue persists, check the annotation files for this dataset. Visual anomalies often occur due to incorrect or corrupted annotation formatting, such as:

    • Out-of-bounds coordinates
    • Incorrect mask encoding
    • Missing or mismatched labels

    You can also perform exploratory data analysis (EDA) on your dataset using tools like histograms or heatmaps to ensure annotations align with expectations. The Preprocessing Annotated Data Guide may provide helpful insights.


If you confirm the dataset and environment are correct but the issue persists, it might be a bug in the HUB dataset viewer. In that case, please share:

  • Confirmation that the issue is reproducible in the latest version of HUB.
  • Any additional logs or error messages from the browser console (accessible via developer tools in Firefox).

We'll investigate this further based on this information. Thank you for your patience and for bringing this to our attention! 🚀

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