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What Do the Options for Accepting a Team Labeling Task Mean?
Updated on 2024-06-15 GMT+08:00
What Do the Options for Accepting a Team Labeling Task Mean?
- All passed: All items, including the rejected ones will pass the review.
- All rejects: All items, including the ones that have passed the review will be rejected. In this case, the passed items must be labeled and reviewed again in the next acceptance.
- All remaining items pass: The rejected items are still rejected, and the remaining items will automatically pass the review.
- All remaining items rejects: The selected items that have passed the review do not need to be labeled. All the selected items that have been rejected and the items that have not been selected must be labeled again for acceptance.
Parent topic: Data Management (Old Version)
Data Management (Old Version) FAQs
- Are There Size Limits for Images to be Uploaded?
- What Do I Do If Images in a Dataset Cannot Be Displayed?
- How Do I Integrate Multiple Object Detection Datasets into One Dataset?
- What Do I Do If Importing a Dataset Failed?
- Can a Table Dataset Be Labeled?
- What Do I Do to Import Locally Labeled Data to ModelArts?
- Why Does Data Fail to Be Imported Using the Manifest File?
- Where Are Labeling Results Stored?
- How Do I Download Labeling Results to a Local PC?
- Why Cannot Team Members Receive Emails for a Team Labeling Task?
- Can Two Accounts Concurrently Label One Dataset?
- How Data Is Distributed Between Team Members During Team Labeling?
- Can I Delete an Annotator from a Labeling Team with a Labeling Task Assigned? What Is the Impact on the Labeling Result After Deletion? If the Annotator Cannot Be Deleted, Can I Separate the Annotator's Labeling Result?
- How Do I Define a Hard Example in Data Labeling? Which Samples Are Identified as Hard Examples?
- Can I Add Multiple Labeling Boxes to an Object Detection Dataset Image?
- How Do I Merge Two Datasets?
- Does Auto Labeling Support Polygons?
- What Do the Options for Accepting a Team Labeling Task Mean?
- Why Are Images Displayed in Different Angles Under the Same Account?
- Do I Need to Train Data Again If New Data Is Added After Auto Labeling Is Complete?
- Why Does the System Display a Message Indicating My Label Fails to Save on ModelArts?
- Can One Label By Identified Among Multiple Labels?
- Why Are Newly Added Images Not Automatically Labeled After Data Amplification Is Enabled?
- Why Cannot Videos in a Video Dataset Be Displayed or Played?
- Why All the Labeled Samples Stored in an OBS Bucket Are Displayed as Unlabeled in ModelArts After the Data Source Is Synchronized?
- How Do I Use Soft-NMS to Reduce Bounding Box Overlapping?
- Why ModelArts Image Labels Are Lost?
- How Do I Add Images to a Validation or Training Dataset?
- Can I Customize Labels for an Object Detection Dataset?
- What ModelArts Data Management Can Be Used for?
- Will My Old-Version Datasets Be Cleared After the Old Version Is Discontinued? The existing datasets and the ones newly created in the old version will be retained after the old version is discontinued.
- Why Is My New Dataset Version Unavailable in Versions?
- How Do I View the Size of a Dataset?
- How Do I View Labeling Details of a New Dataset?
- How Do I Export Labeled Data?
- Why Cannot I Find My Newly Created Dataset?
- What Do I Do If the Database Quota Is Incorrect?
- How Do I Split a Dataset?
- How Do I Delete a Dataset Image?
- Why Is There No Sample in the ModelArts Dataset Downloaded from AI Gallery and Then an OBS Bucket?
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