Annotation set

Annotation set is a collection of annotations for a dataset. Use the Annotation set class to easily manipulate annotations across the whole dataset.

An annotation set is defined by:

• a task

• a reference dataset

• the collection of image-level annotations

class remo.AnnotationSet

Remo annotation set

documentation

class remo.AnnotationSet(id: int = None, name: str = None, task: str = None, dataset_id: int = None, total_classes=None, updated_at=None, released_at=None, total_images: int = None, top3_classes=None, total_annotation_objects: int = None, \*\*kwargs)

• Parameters

  • id – annotation set id

  • name – annotation set name

  • task – annotation task. See also: remo.task

  • dataset_id – dataset id

  • total_classes – total annotation classes

  • updated_at – date, when annotation set was last updated

  • released_at – annotation set release date

  • total_images – total number of images

  • top3_classes – top 3 classes in annotation set

  • total_annotation_objects – total number of annotation objects in annotation set

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add_annotations

Upload of annotations to the annotation set.

Example::

urls = [‘[https://remo-scripts.s3-eu-west-1.amazonaws.com/open_images_sample_dataset.zip](https://remo-scripts.s3-eu-west-1.amazonaws.com/open_images_sample_dataset.zip)’]
ds = remo.create_dataset(name = ‘D1’, urls = urls)
ann_set = ds.create_annotation_set(annotation_task = ‘Object Detection’, name = ‘test_set’)

image_name = ‘000a1249af2bc5f0.jpg’
annotations = []

annotation = remo.Annotation()
annotation.img_filename = image_name
annotation.classes=’Human hand’
annotation.bbox=[227, 284, 678, 674]
annotations.append(annotation)

annotation = remo.Annotation()
annotation.img_filename = image_name
annotation.classes=’Fashion accessory’
annotation.bbox=[496, 322, 544,370]
annotations.append(annotation)

ann_set.add_annotations(annotations)

documentation

add_annotations(annotations: List[remo.domain.annotation.Annotation])

• Parameters

  annotations – list of Annotation objects

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add_image_annotation

Adds new annotation to the image

documentation

add_image_annotation(image_id: int, annotation: remo.domain.annotation.Annotation)

• Parameters

  • image_id – image id

  • annotation – annotation data

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classes

List classes within the annotation set

documentation

classes()

• Returns

  List of classes

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export_annotations_to_file

Exports annotations in a given format and saves it to a file. If export_tags = True, output_file needs to be a .zip file.

It offers some convenient export options, including:

• Methods to append the full_path to image filenames,

• Choose between coordinates in pixels or percentages,

• Export tags to a separate file

• Export annotations filtered by user-determined tags.

documentation

export_annotations_to_file(output_file: str, annotation_format: str = 'json', export_coordinates: str = 'pixel', append_path: bool = True, export_tags: bool = True, filter_by_tags: list = None)

• Parameters

  • output_file – output file to save. Includes file extension and can include file path. If export_tags = True, output_file needs to be a .zip file

  • annotation_format – can be one of [‘json’, ‘coco’, ‘csv’]. Default=’json’

  • append_path – if True, appends the path to the filename (e.g. local path). Default: True

  • export_coordinates – converts output values to percentage or pixels, can be one of [‘pixel’, ‘percent’]. Default=’pixel’

  • export_tags – exports the tags to a CSV file, it can be one of [True, False. Default=True

  • filter_by_tags – allows to filter results by tags, can be list or str

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view

Opens browser on the annotation tool page for this annotation set

documentation

view()

view_stats

Opens browser on annotation set insights page

documentation

view_stats()