Merge pull request #8 from siesto1elemento/my-feature-branch

formatting changes

Author: siesto1elemento

cvat/apps/dataset_manager/formats/datumaro.py

@@ -9,76 +9,62 @@
 
 from pyunpack import Archive
 
-from cvat.apps.dataset_manager.bindings import (
-    GetCVATDataExtractor,
-    detect_dataset,
-    import_dm_annotations,
-)
+from cvat.apps.dataset_manager.bindings import (GetCVATDataExtractor, detect_dataset,
+    import_dm_annotations)
 from cvat.apps.dataset_manager.util import make_zip_archive
 from cvat.apps.engine.models import DimensionType
 
 from .registry import dm_env, exporter, importer
 
-
 class DeleteImagePath(ItemTransform):
     def transform_item(self, item):
         image = None
         if item.has_image and item.image.has_data:
             image = Image(data=item.image.data, size=item.image.size)
-        return item.wrap(image=image, point_cloud="", related_images=[])
+        return item.wrap(image=image, point_cloud='', related_images=[])
 
 
 @exporter(name="Datumaro", ext="ZIP", version="1.0")
 def _export(dst_file, temp_dir, instance_data, save_images=False):
-    with GetCVATDataExtractor(
-        instance_data=instance_data, include_images=save_images
-    ) as extractor:
+    with GetCVATDataExtractor(instance_data=instance_data, include_images=save_images) as extractor:
         dataset = Dataset.from_extractors(extractor, env=dm_env)
         if not save_images:
             dataset.transform(DeleteImagePath)
-        dataset.export(temp_dir, "datumaro", save_images=save_images)
+        dataset.export(temp_dir, 'datumaro', save_images=save_images)
 
     make_zip_archive(temp_dir, dst_file)
 
-
 @importer(name="Datumaro", ext="ZIP", version="1.0")
 def _import(src_file, temp_dir, instance_data, load_data_callback=None, **kwargs):
     Archive(src_file.name).extractall(temp_dir)
 
-    detect_dataset(
-        temp_dir, format_name="datumaro", importer=dm_env.importers.get("datumaro")
-    )
-    dataset = Dataset.import_from(temp_dir, "datumaro", env=dm_env)
+    detect_dataset(temp_dir, format_name='datumaro', importer=dm_env.importers.get('datumaro'))
+    dataset = Dataset.import_from(temp_dir, 'datumaro', env=dm_env)
 
     if load_data_callback is not None:
         load_data_callback(dataset, instance_data)
     import_dm_annotations(dataset, instance_data)
 
-
 @exporter(name="Datumaro 3D", ext="ZIP", version="1.0", dimension=DimensionType.DIM_3D)
 def _export(dst_file, temp_dir, instance_data, save_images=False):
     with GetCVATDataExtractor(
-        instance_data=instance_data,
-        include_images=save_images,
+        instance_data=instance_data, include_images=save_images,
         dimension=DimensionType.DIM_3D,
     ) as extractor:
         dataset = Dataset.from_extractors(extractor, env=dm_env)
 
         if not save_images:
             dataset.transform(DeleteImagePath)
-        dataset.export(temp_dir, "datumaro", save_images=save_images)
+        dataset.export(temp_dir, 'datumaro', save_images=save_images)
 
     make_zip_archive(temp_dir, dst_file)
 
-
 @importer(name="Datumaro 3D", ext="ZIP", version="1.0", dimension=DimensionType.DIM_3D)
 def _import(src_file, temp_dir, instance_data, load_data_callback=None, **kwargs):
     Archive(src_file.name).extractall(temp_dir)
 
-    detect_dataset(
-        temp_dir, format_name="datumaro", importer=dm_env.importers.get("datumaro")
-    )
-    dataset = Dataset.import_from(temp_dir, "datumaro", env=dm_env)
+    detect_dataset(temp_dir, format_name='datumaro', importer=dm_env.importers.get('datumaro'))
+    dataset = Dataset.import_from(temp_dir, 'datumaro', env=dm_env)
 
     if load_data_callback is not None:
         load_data_callback(dataset, instance_data)