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83 lines
3.1 KiB
Python
83 lines
3.1 KiB
Python
# Copyright (C) 2021-2022 Intel Corporation
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# Copyright (C) 2022 CVAT.ai Corporation
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#
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# SPDX-License-Identifier: MIT
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import zipfile
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from tempfile import TemporaryDirectory
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from datumaro.components.annotation import (AnnotationType, Label,
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LabelCategories)
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from datumaro.components.dataset import Dataset
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from datumaro.components.extractor import ItemTransform
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from cvat.apps.dataset_manager.bindings import (GetCVATDataExtractor,
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import_dm_annotations)
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from cvat.apps.dataset_manager.util import make_zip_archive
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from .registry import dm_env, exporter, importer
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class AttrToLabelAttr(ItemTransform):
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def __init__(self, extractor, label):
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super().__init__(extractor)
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assert isinstance(label, str)
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self._categories = {}
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label_cat = self._extractor.categories().get(AnnotationType.label)
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if not label_cat:
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label_cat = LabelCategories()
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self._label = label_cat.add(label)
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self._categories[AnnotationType.label] = label_cat
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def categories(self):
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return self._categories
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def transform_item(self, item):
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annotations = list(item.annotations)
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attributes = item.attributes
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if item.attributes:
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annotations.append(Label(self._label, attributes=item.attributes))
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attributes = {}
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return item.wrap(annotations=annotations, attributes=attributes)
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class LabelAttrToAttr(ItemTransform):
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def __init__(self, extractor, label):
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super().__init__(extractor)
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assert isinstance(label, str)
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label_cat = self._extractor.categories().get(AnnotationType.label)
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self._label = label_cat.find(label)[0]
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def transform_item(self, item):
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annotations = list(item.annotations)
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attributes = dict(item.attributes)
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if self._label is not None:
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labels = [ann for ann in annotations
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if ann.type == AnnotationType.label \
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and ann.label == self._label]
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if len(labels) == 1:
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attributes.update(labels[0].attributes)
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annotations.remove(labels[0])
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return item.wrap(annotations=annotations, attributes=attributes)
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@exporter(name='Market-1501', ext='ZIP', version='1.0')
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def _export(dst_file, instance_data, save_images=False):
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dataset = Dataset.from_extractors(GetCVATDataExtractor(
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instance_data, include_images=save_images), env=dm_env)
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with TemporaryDirectory() as temp_dir:
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dataset.transform(LabelAttrToAttr, label='market-1501')
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dataset.export(temp_dir, 'market1501', save_images=save_images)
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make_zip_archive(temp_dir, dst_file)
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@importer(name='Market-1501', ext='ZIP', version='1.0')
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def _import(src_file, instance_data, load_data_callback=None):
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with TemporaryDirectory() as tmp_dir:
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zipfile.ZipFile(src_file).extractall(tmp_dir)
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dataset = Dataset.import_from(tmp_dir, 'market1501', env=dm_env)
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dataset.transform(AttrToLabelAttr, label='market-1501')
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if load_data_callback is not None:
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load_data_callback(dataset, instance_data)
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import_dm_annotations(dataset, instance_data)
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