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This guide explains the processing issues you may encounter when importing data and how to resolve them. When data is ingested, Labelbox processes it to generate embeddings, extract media attributes, and standardize formats. If an issue occurs, it will be flagged as an error or a warning.

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Processing states

  • Processing: The initial state when a data row is ingested.
  • Success: The data row was processed successfully.
  • Failure: The data row could not be processed due to an error or warning. It will not appear in the Catalog until the issue is fixed.

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View and fix failed data rows

  1. Find failures: In Catalog, an issue icon will appear next to datasets with processing issues. Click this icon to go to the “Processing Issues” view.
  2. Filter issues: You can filter the view to see data rows with specific errors or warnings.
  3. Fix the source issue: Use the error descriptions below to diagnose the problem (e.g., fix a broken URL, correct cloud storage permissions).
  4. Re-process: Once you’ve fixed the underlying issue, select the failed data rows in the “Processing Issues” view and click Re-process.

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Large files

Large files such as TIF, Video, and Audio can take a few seconds to process.

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Common errors (failures)

An error is a serious issue that prevents a data row from being used.

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Warnings

A warning indicates a non-critical issue. The data row can be used, but your experience may be degraded.
Processing issues and the Python SDK
  • If you export data rows from Catalog using the SDK, all data rows are exported, including those with processing issues.
  • If you send data rows to a labeling project using the SDK, all data rows are sent to the labeling project, including those with processing issues.