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Dataset Management Framework (Datumaro)

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A framework and CLI tool to build, transform, and analyze datasets.

VOC dataset                                  ---> Annotation tool
     +                                     /
COCO dataset -----> Datumaro ---> dataset ------> Model training
     +                                     \
CVAT annotations                             ---> Publication, statistics etc.

Features

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  • Dataset reading, writing, conversion in any direction.

    Other formats and documentation for them can be found here.

  • Dataset building

    • Merging multiple datasets into one
    • Dataset filtering by a custom criteria:
      • remove polygons of a certain class
      • remove images without annotations of a specific class
      • remove occluded annotations from images
      • keep only vertically-oriented images
      • remove small area bounding boxes from annotations
    • Annotation conversions, for instance:
      • polygons to instance masks and vice-versa
      • apply a custom colormap for mask annotations
      • rename or remove dataset labels
    • Splitting a dataset into multiple subsets like train, val, and test:
      • random split
      • task-specific splits based on annotations, which keep initial label and attribute distributions
        • for classification task, based on labels
        • for detection task, based on bboxes
        • for re-identification task, based on labels, avoiding having same IDs in training and test splits
  • Dataset quality checking

    • Simple checking for errors
    • Comparison with model inference
    • Merging and comparison of multiple datasets
    • Annotation validation based on the task type(classification, etc)
  • Dataset comparison

  • Dataset statistics (image mean and std, annotation statistics)

Check the design document for a full list of features. Check the user manual for usage instructions.

Contributing

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Feel free to open an Issue, if you think something needs to be changed. You are welcome to participate in development, instructions are available in our contribution guide.

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Source Distribution

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