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

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

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

classes¶

List classes within the annotation set

documentation

classes()

Returns

List of classes

export_annotations¶

Exports annotations in a given format

documentation

export_annotations(annotation_format: str = 'json', export_coordinates: str = 'pixel', full_path: bool = True, export_tags: bool = True)

Parameters
- annotation_format – choose format from this list [‘json’, ‘coco’, ‘csv’]
- full_path – uses full image path (e.g. local path), it can be one of [True, False], 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
Returns

annotation file content

export_annotations_to_file¶

Exports annotations in given format and save to output file

documentation

export_annotations_to_file(output_file: str, annotation_format: str = 'json', export_coordinates: str = 'pixel', full_path: bool = True, export_tags: bool = True)

Parameters
- output_file – output file to save
- annotation_format – can be one of [‘json’, ‘coco’, ‘csv’], default=’json’
- full_path – uses full image path (e.g. local path), it can be one of [True, False], 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

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()