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Update multi-label document and conversion script #2358

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merged 2 commits into from
Jul 17, 2023
Merged

Update multi-label document and conversion script #2358

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0aa5c0e
Update docs, label convert script
sungmanc Jul 14, 2023
07cd01f
Merge branch 'releases/1.4.0' into update-multilabel
sungmanc Jul 16, 2023
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5 changes: 4 additions & 1 deletion ...urce/guide/explanation/algorithms/classification/multi_label_classification.rst
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Expand Up @@ -24,7 +24,7 @@ Dataset Format
**************

As it is a common practice to use object detection datasets in the academic area, we support the most popular object detection format: `COCO <https://cocodataset.org/#format-data>`_.
Specifically, this format should be converted in our `internal representation <https://github.com/openvinotoolkit/training_extensions/tree/develop/data/datumaro_multilabel>`_ first. We provided a `script <https://github.com/openvinotoolkit/training_extensions/blob/develop/src/otx/algorithms/classification/utils/convert_coco_to_multilabel.py>` to help with conversion.
Specifically, this format should be converted in our `internal representation <https://github.com/openvinotoolkit/training_extensions/tree/develop/tests/assets/datumaro_multilabel>`_ first. We provided a `script <https://github.com/openvinotoolkit/training_extensions/blob/develop/src/otx/algorithms/classification/utils/convert_coco_to_multilabel.py>` to help with conversion.
To convert the COCO data format to our internal one, run this script in similar way:

.. code-block::
Expand All @@ -35,6 +35,9 @@ To convert the COCO data format to our internal one, run this script in similar

Please, refer to our :doc:`dedicated tutorial <../../../tutorials/base/how_to_train/classification>` for more information how to train, validate and optimize classification models.

.. note::
For now, "___" is a symbol to distinguish the multi-label format. So, it must be included at the front of the label name.

******
Models
******
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2 changes: 1 addition & 1 deletion src/otx/algorithms/classification/utils/convert_coco_to_multilabel.py
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Expand Up @@ -61,7 +61,7 @@ def coco_to_datumaro_multilabel(ann_file_path: str, data_root_dir: str, output:
overall_classes: List = coco_dataset.get_classes()
for class_name in overall_classes:
multilabel_ann_format["categories"]["label"]["label_groups"].append(
{"name": str(class_name), "group_type": "exclusive", "labels": [str(class_name)]}
{"name": f"___{str(class_name)}", "group_type": "exclusive", "labels": [str(class_name)]}
)

multilabel_ann_format["categories"]["label"]["labels"].append(
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