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The COCO dataset occasionally contains annotation errors. A systematic way to report and correct these errors would enhance the dataset's accuracy and utility.
Feature Proposal:
Implement a crowdsourced error correction mechanism, allowing users to report and rectify annotation errors directly.
Key Points:
User Reporting Interface: Simple UI for error reporting within the dataset platform.
Error Verification: Process for validating reported errors, possibly automated or manual by maintainers.
Community Engagement: Encourage user participation in dataset improvement.
Enhanced Accuracy: Continuous user feedback can improve dataset reliability over time.
Example Errors:
According to my estimates, as of December 2023, around 4% of the images in the COCO dataset contain annotations with at least one misspelled word.
The text was updated successfully, but these errors were encountered:
The COCO dataset occasionally contains annotation errors. A systematic way to report and correct these errors would enhance the dataset's accuracy and utility.
Feature Proposal:
Implement a crowdsourced error correction mechanism, allowing users to report and rectify annotation errors directly.
Key Points:
Example Errors:
According to my estimates, as of December 2023, around 4% of the images in the COCO dataset contain annotations with at least one misspelled word.
The text was updated successfully, but these errors were encountered: