LabelingQueueApi¶

class LabelingQueueApi[source]¶

Bases: supervisely.api.module_api.RemoveableBulkModuleApi, supervisely.api.module_api.ModuleWithStatus

API for working with Labeling Queues. LabelingQueueApi object is immutable.

Parameters

api : Api: API connection to the server.

Usage example

import os
from dotenv import load_dotenv

import supervisely as sly

# Load secrets and create API object from .env file (recommended)
# Learn more here: https://developer.supervisely.com/getting-started/basics-of-authentication
if sly.is_development():
    load_dotenv(os.path.expanduser("~/supervisely.env"))
api = sly.Api.from_env()

# Pass values into the API constructor (optional, not recommended)
# api = sly.Api(server_address="https://app.supervisely.com", token="4r47N...xaTatb")

queue = api.labeling_queues.get_info_by_id(2) # api usage example

Methods

`convert_info_to_json`	_convert_info_to_json
`create`	Creates Labeling Queue and assigns given Users to it.
`exists`	Checks if an entity with the given parent_id and name exists
`get_entities_all_pages`	Get list of all or limited quantity entities from the Supervisely server.
`get_entities_count_by_status`	Get count of entities in the given Labeling Queue with given status. :type id: `int` :param id: Labeling Queue ID in Supervisely. :type id: int :type status: `Union`[`List`, `Literal`['none', 'done', 'accepted', 'null'], `None`] :param status: Status of entities to filter. "null" - pending (in queue). "none" - annotating (not in queue), "done" - on review, "accepted" - accepted, :type status: str or List[str], optional :type filter_by: `Optional`[`List`[`Dict`]] :param filter_by: Filter for entities. e.g. [{"field": "name", "operator": "in", "value": ["image_01", "image_02"]}] - field - field name to filter by ("id", "name", "reviewedAt") - operator - operator to use for filtering ("=", ">", "<", ">=", "<=") - value - value to filter by :type filter_by: List[Dict], optional :return: Count of entities in the Labeling Queue with given status. :rtype: int :Usage example:.
`get_free_name`	Generates a free name for an entity with the given parent_id and name.
`get_info_by_id`	Get Labeling Queue information by ID.
`get_info_by_name`	Get information about an entity by its name from the Supervisely server.
`get_list`	Get list of information about Labeling Queues in the given Team.
`get_list_all_pages`	Get list of all or limited quantity entities from the Supervisely server.
`get_list_all_pages_generator`	This generator function retrieves a list of all or a limited quantity of entities from the Supervisely server, yielding batches of entities as they are retrieved
`get_list_idx_page_async`	Get the list of items for a given page number.
`get_list_page_generator_async`	Yields list of images in dataset asynchronously page by page.
`get_project_meta`	Returns project meta with classes and tags used in the labeling queue with given id.
`get_status`	Get status of Labeling Job with given ID.
`info_sequence`	NamedTuple LabelingQueueInfo information about Labeling Queue.
`info_tuple_name`	NamedTuple name - LabelingQueueInfo.
`raise_for_status`
`remove`	Remove an entity with the specified ID from the Supervisely server.
`remove_batch`	Remove entities in batches from the Supervisely server.
`set_status`	Sets Labeling Queue status.

Attributes

`MAX_WAIT_ATTEMPTS`	Maximum number of attempts that will be made to wait for a certain condition to be met.
`WAIT_ATTEMPT_TIMEOUT_SEC`	Number of seconds for intervals between attempts.

InfoType¶: alias of supervisely.api.module_api.LabelingQueueInfo

classmethod convert_info_to_json(info)¶

_convert_info_to_json

Return type: Dict

create(name, user_ids, reviewer_ids, dataset_id=None, collection_id=None, readme=None, classes_to_label=None, objects_limit_per_image=None, tags_to_label=None, tags_limit_per_image=None, include_images_with_tags=None, exclude_images_with_tags=None, images_range=None, reviewer_id=None, images_ids=None, dynamic_classes=False, dynamic_tags=False, disable_confirm=None, disable_submit=None, toolbox_settings=None, hide_figure_author=False, allow_review_own_annotations=False, skip_complete_job_on_empty=False, enable_quality_check=None, quality_check_user_ids=None)[source]¶

Creates Labeling Queue and assigns given Users to it.

Parameters

name : str: Labeling Queue name in Supervisely.
dataset_id : int: Dataset ID in Supervisely.
collection_id : int, optional: Entities Collection ID in Supervisely.
user_ids : List[int]: User IDs in Supervisely to assign Users as labelers to Labeling Queue.
reviewer_ids : List[int]: User IDs in Supervisely to assign Users as reviewers to Labeling Queue.
readme : str, optional: Additional information about Labeling Queue.
description : str, optional: Description of Labeling Queue.
classes_to_label : List[str], optional: List of classes to label in Dataset.
objects_limit_per_image : int, optional: Limit the number of objects that the labeler can create on each image.
tags_to_label : List[str], optional: List of tags to label in Dataset.
tags_limit_per_image : int, optional: Limit the number of tags that the labeler can create on each image.
include_images_with_tags : List[str], optional: Include images with given tags for processing by labeler.
exclude_images_with_tags : List[str], optional: Exclude images with given tags for processing by labeler.
images_range : List[int, int], optional: Limit number of images to be labeled for each labeler.
reviewer_id : int, optional: User ID in Supervisely to assign User as Reviewer to Labeling Queue.
images_ids : List[int], optional: List of images ids to label in dataset
dynamic_classes : bool, optional: If True, classes created after creating the queue will be available for annotators
dynamic_tags : bool, optional: If True, tags created after creating the queue will be available for annotators
disable_confirm : bool, optional: If True, the Confirm button will be disabled in the labeling tool. It will remain disabled until the next API call sets the parameter to False, re-enabling the button.
disable_submit : bool, optional: If True, the Submit button will be disabled in the labeling tool. It will remain disabled until the next API call sets the parameter to False, re-enabling the button.
toolbox_settings : Dict, optional: Settings for the labeling tool. Only video projects are supported.
hide_figure_author : bool, optional: If True, hides the author of the figure in the labeling tool.
allow_review_own_annotations : bool, optional: If True, allows labelers to review their own annotations.
skip_complete_job_on_empty : bool, optional: If True, skips completing the Labeling Queue if there are no images to label.
enable_quality_check : bool, optional: If True, adds an intermediate step between “review” and completing the Labeling Queue.
quality_check_user_ids : List[int], optional: List of User IDs in Supervisely to assign Users as Quality Checkers to Labeling Queue.

Returns

Labeling Queue ID in Supervisely.

Return type

int

Usage example

import supervisely as sly

os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()

user_name = 'alex'
dataset_id = 602
new_labeling_queue_id = api.labeling_queue.create(
    user_name,
    dataset_id,
    user_ids=[111, 222],
    readme='Readmy text',
    description='Work for labelers',
    objects_limit_per_image=5,
    tags_limit_per_image=3
)
print(new_labeling_queue_id)

# >>> 2

# Create video labeling job with toolbox settings

user_id = 4
dataset_id = 277
video_id = 24897
toolbox_settings = {"playbackRate": 32, "skipFramesSize": 15, "showVideoTime": True}

new_labeling_queue_id = api.labeling_queue.create(
    name="Labeling Queue name",
    dataset_id=dataset_id,
    user_ids=[user_id],
    readme="Labeling Queue readme",
    description="Some description",
    classes_to_label=["car", "animal"],
    tags_to_label=["animal_age_group"],
    images_ids=[video_id],
    toolbox_settings=toolbox_settings,
)
print(new_labeling_queue_id)

# >>> 3

exists(parent_id, name)¶

Checks if an entity with the given parent_id and name exists

Parameters

parent_id : int: ID of the parent entity.
name : str: Name of the entity.

Returns

Returns True if entity exists, and False if not

Return type

bool

Usage example

import supervisely as sly

# You can connect to API directly
address = 'https://app.supervisely.com/'
token = 'Your Supervisely API Token'
api = sly.Api(address, token)

# Or you can use API from environment
os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()


name = "IMG_0315.jpeg"
dataset_id = 55832
exists = api.image.exists(dataset_id, name)
print(exists) # True

get_entities_all_pages(id, collection_id=None, per_page=25, sort='name', sort_order='asc', status=None, limit=None, filter_by=None)[source]¶

Get list of all or limited quantity entities from the Supervisely server.

Parameters

id : int

Labeling Queue ID in Supervisely.

collection_id : int, optional

Collection ID in Supervisely.

per_page : int, optional

Number of entities per page.

sort : str, optional

Sorting field.

sort_order : str, optional

Sorting order.

status : str or List[str], optional

Status of entities to filter. “null” - pending (in queue). “none” - annotating (not in queue), “done” - on review, “accepted” - accepted,

limit : int, optional

Limit the number of entities to return. If limit is None, all entities will be returned.

filter_by : List[Dict], optional

Filter for entities. e.g. [{“field”: “name”, “operator”: “in”, “value”: [“image_01”, “image_02”]}]

field - field name to filter by (“id”, “name”, “reviewedAt”)

operator - operator to use for filtering (“=”, “>”, “<”, “>=”, “<=”)

value - value to filter by

return_first_response : bool, optional

Specify if return first response

Return type

Dict[str, Union[List[Dict], int]]

get_entities_count_by_status(id, status=None, filter_by=None)[source]¶

Get count of entities in the given Labeling Queue with given status. :type id: int :param id: Labeling Queue ID in Supervisely. :type id: int :type status: Union[List, Literal[‘none’, ‘done’, ‘accepted’, ‘null’], None] :param status: Status of entities to filter.

“null” - pending (in queue). “none” - annotating (not in queue), “done” - on review, “accepted” - accepted,

Parameters

filter_by : List[Dict], optional

Filter for entities. e.g. [{“field”: “name”, “operator”: “in”, “value”: [“image_01”, “image_02”]}]

field - field name to filter by (“id”, “name”, “reviewedAt”)

operator - operator to use for filtering (“=”, “>”, “<”, “>=”, “<=”)

value - value to filter by

Returns

Count of entities in the Labeling Queue with given status.

Return type

int

Usage example

import supervisely as sly

os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()

entities_count = api.labeling_queue.get_entities_count_by_status(4, status="none")
print(entities_count)
# Output: 3

get_free_name(parent_id, name)¶

Generates a free name for an entity with the given parent_id and name. Adds an increasing suffix to original name until a unique name is found.

Parameters

parent_id : int: ID of the parent entity.
name : str: Name of the entity.

Returns

Returns free name.

Return type

str

Usage example

import supervisely as sly

# You can connect to API directly
address = 'https://app.supervisely.com/'
token = 'Your Supervisely API Token'
api = sly.Api(address, token)

# Or you can use API from environment
os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()


name = "IMG_0315.jpeg"
dataset_id = 55832
free_name = api.image.get_free_name(dataset_id, name)
print(free_name) # IMG_0315_001.jpeg

get_info_by_id(id)[source]¶

Get Labeling Queue information by ID.

Parameters

id : int: Labeling Queue ID in Supervisely.

Returns

Information about Labeling Queue. See info_sequence

Return type

LabelingJobInfo

Usage example

import supervisely as sly

os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()

label_job_info = api.labeling_queue.get_info_by_id(2)
print(label_job_info)
# Output: [
#     2,
#     "Annotation Queue (#1) (#1) (dataset_01)",
#     "",
#     "",
#     4,
#     8,
#     "First Workspace",
#     58,
#     "tutorial_project",
#     54,
#     "dataset_01",
#     4,
#     "anna",
#     4,
#     "anna",
#     4,
#     "anna",
#     "2020-04-08T15:10:12.618Z",
#     "2020-04-08T15:10:19.833Z",
#     "2020-04-08T15:13:39.788Z",
#     "completed",
#     false,
#     3,
#     0,
#     1,
#     2,
#     2,
#     [],
#     [],
#     [
#         1,
#         5
#     ],
#     null,
#     null,
#     [],
#     [],
#     [],
#     [
#         {
#             "reviewStatus": "rejected",
#             "id": 283,
#             "name": "image_03"
#         },
#         {
#             "reviewStatus": "accepted",
#             "id": 282,
#             "name": "image_02"
#         },
#         {
#             "reviewStatus": "accepted",
#             "id": 281,
#             "name": "image_01"
#         }
#     ]
# ]

get_info_by_name(parent_id, name, fields=[])¶

Get information about an entity by its name from the Supervisely server.

Parameters

parent_id : int: ID of the parent entity.
name : str: Name of the entity for which the information is being retrieved.
fields : List[str]: The list of api fields which will be returned with the response.

Usage example

import supervisely as sly

# You can connect to API directly
address = 'https://app.supervisely.com/'
token = 'Your Supervisely API Token'
api = sly.Api(address, token)

# Or you can use API from environment
os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()


dataset_id = 55832
name = "IMG_0315.jpeg"
info = api.image.get_info_by_name(dataset_id, name)
print(info)
# Output: ImageInfo(id=19369643, name='IMG_0315.jpeg', ...)

get_list(team_id, dataset_id=None, project_id=None, ids=None, names=None, show_disabled=False)[source]¶

Get list of information about Labeling Queues in the given Team.

Parameters

team_id : int: Team ID in Supervisely.
dataset_id : int, optional: Dataset ID in Supervisely.
project_id : int, optional: Project ID in Supervisely.
ids : List[int], optional: List of Labeling Queue IDs in Supervisely.
names : List[str], optional: List of Labeling Queue names in Supervisely.
show_disabled : bool, optional: Show disabled Labeling Queues.

Returns

List of information about Labeling Queues. See info_sequence

Return type

List[LabelingQueueInfo]

Usage example

import supervisely as sly

os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()

label_jobs = api.labeling_queue.get_list(4)

get_list_all_pages(method, data, progress_cb=None, convert_json_info_cb=None, limit=None, return_first_response=False)¶

Get list of all or limited quantity entities from the Supervisely server.

Parameters

method : str: Request method name
data : dict: Dictionary with request body info
progress_cb : Progress, optional: Function for tracking download progress.
convert_json_info_cb : Callable, optional: Function for convert json info
limit : int, optional: Number of entity to retrieve
return_first_response : bool, optional: Specify if return first response

get_list_all_pages_generator(method, data, progress_cb=None, convert_json_info_cb=None, limit=None, return_first_response=False)¶

This generator function retrieves a list of all or a limited quantity of entities from the Supervisely server, yielding batches of entities as they are retrieved

Parameters

method : str: Request method name
data : dict: Dictionary with request body info
progress_cb : Progress, optional: Function for tracking download progress.
convert_json_info_cb : Callable, optional: Function for convert json info
limit : int, optional: Number of entity to retrieve
return_first_response : bool, optional: Specify if return first response

async get_list_idx_page_async(method, data)¶

Get the list of items for a given page number. Page number is specified in the data dictionary.

Parameters

method : str: Method to call for listing items.
data : dict: Data to pass to the API method.

Returns

List of items.

Return type

Tuple[int, List[NamedTuple]]

async get_list_page_generator_async(method, data, pages_count=None, semaphore=None)¶

Yields list of images in dataset asynchronously page by page.

Parameters

method : str: Method to call for listing items.
data : dict: Data to pass to the API method.
pages_count : int, optional: Preferred number of pages to retrieve if used with a per_page limit. Will be automatically adjusted if the pagesCount differs from the requested number.
semaphore : asyncio.Semaphore, optional: Semaphore for limiting the number of simultaneous requests.
kwargs: Additional arguments.

Returns

List of images in dataset.

Return type

AsyncGenerator[List[ImageInfo]]

Usage example

import supervisely as sly
import asyncio

os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()

method = 'images.list'
data = {
    'datasetId': 123456
}

loop = sly.utils.get_or_create_event_loop()
images = loop.run_until_complete(api.image.get_list_generator_async(method, data))

get_project_meta(id)[source]¶

Returns project meta with classes and tags used in the labeling queue with given id.

Parameters

id : int: Labeling Queue ID in Supervisely.

Returns

Project meta of the labeling queue with given id.

Return type

ProjectMeta

get_status(id)[source]¶

Get status of Labeling Job with given ID.

Parameters

id : int: Labeling job ID in Supervisely.

Returns

Labeling Job Status

Return type

Status

Usage example

import supervisely as sly

os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()

job_status = api.labeling_queue.get_status(4)
print(job_status) # pending

static info_sequence()[source]¶

NamedTuple LabelingQueueInfo information about Labeling Queue.

Example

LabelingQueueInfo(
    id=2,
    name='Annotation Queue (#1)',
    team_id=4,
    project_id=58,
    dataset_id=54,
    created_by_id=4,
    labelers=[4],
    reviewers=[4],
    created_at='2020-04-08T15:10:12.618Z',
    finished_at='2020-04-08T15:13:39.788Z',
    status='completed',
    jobs=[283, 282, 281],
    entities_count=3,
    accepted_count=2,
    annotated_count=3,
    in_progress_count=2,
    pending_count=1,
    meta={}
)

static info_tuple_name()[source]¶: NamedTuple name - LabelingQueueInfo.

raise_for_status(status)¶

remove(id)¶

Remove an entity with the specified ID from the Supervisely server.

Parameters

id : int: Entity ID in Supervisely.

Usage example

import supervisely as sly

# You can connect to API directly
address = 'https://app.supervisely.com/'
token = 'Your Supervisely API Token'
api = sly.Api(address, token)

# Or you can use API from environment
os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()


image_id = 19369643
api.image.remove(image_id)

remove_batch(ids, progress_cb=None, batch_size=50)¶

Remove entities in batches from the Supervisely server. All entity IDs must belong to the same nesting (for example team, or workspace, or project, or dataset). Therefore, it is necessary to sort IDs before calling this method.

Parameters

ids : List[int]: IDs of entities in Supervisely.
progress_cb : Callable: Function for control remove progress.

Usage example

import supervisely as sly

# You can connect to API directly
address = 'https://app.supervisely.com/'
token = 'Your Supervisely API Token'
api = sly.Api(address, token)

# Or you can use API from environment
os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()


image_ids = [19369645, 19369646, 19369647]
api.image.remove_batch(image_ids)

set_status(id, status)[source]¶

Sets Labeling Queue status.

Parameters

id : int: Labeling Queue ID in Supervisely.
status : str: New Labeling Queue status

Returns

None

Return type

NoneType

Usage example

import supervisely as sly
from supervisely.api.labeling_job_api.LabelingJobApi.Status import COMPLETED

os.environ['SERVER_ADDRESS'] = 'https://app.supervisely.com'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()

api.labeling_queue.set_status(id=9, status="completed")