Efficient batch processing mechanism
Annot8's batch processing system uses multi-threaded optimization technology to load and pre-process a large number of images simultaneously. Its intelligent memory management mechanism ensures smooth operation even when processing datasets as large as 500 images, with average load times kept under 3 seconds.
Batch Workflow Benefits
- Supports drag-and-drop batch import of folders to reduce repetitive operations
- Provides continuous labeling mode, automatically jumping to the next image
- Label memory function can reuse frequently used labeling categories
- Real-time display of progress indicators for workload management
Comparison tests show that the total time consumed for batch annotation of 1000 images using Annot8 is about 70% shorter than single processing, saving professional developers a lot of time and cost.
This answer comes from the articleAnnot8: Quickly Labeling Images to Train AI ModelsThe
May not be reproduced without permission:AI productivity tools " Annot8's batch processing capability significantly improves annotation efficiency.
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