LabelingQueueApi¶

class LabelingQueueApi(api)[source]¶

Bases: RemoveableBulkModuleApi, ModuleWithStatus

API for working with labeling queues. LabelingQueueApi object is immutable.

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()

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

Parameters:

api¶: Api object to use for API connection.

Methods

`convert_info_to_json`	Convert information about an entity to a dictionary.
`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.
`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`	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 LabelingQueueInfo

classmethod convert_info_to_json(info)¶

Convert information about an entity to a dictionary.

Parameters:

info : NamedTuple¶: Information about the entity.

Returns:

Dictionary with information about the entity.

Return type:

dict

static info_sequence()[source]¶

NamedTuple LabelingQueueInfo information about Labeling Queue.

Usage 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={},
    collection_id=None,
)

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

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, guide_id=None, description=None)[source]¶

Creates Labeling Queue and assigns given Users to it.

Parameters:

name : str¶: Labeling Queue name 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.
dataset_id : int¶: Dataset ID in Supervisely.
collection_id : int, optional¶: Entities Collection ID in Supervisely.
readme : str, optional¶: Additional information about 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.
guide_id : int, optional¶: Guide ID in Supervisely to assign a guide to the Labeling Queue.
description : str, optional¶: Description of Labeling Queue.

Returns:

Labeling Queue ID in Supervisely.

Return type:

int

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()

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 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()

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. Possible values:

"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. Each element is a dict with keys field, operator, value. Example: [{"field": "name", "operator": "in", "value": ["image_01", "image_02"]}].

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

Get count of entities in the given Labeling Queue with given status.

Parameters:

id : int¶

Labeling Queue ID in Supervisely.

status : str or List[str], optional¶

Status of entities to filter. Possible values:

"null" - pending (in queue)
"none" - annotating (not in queue)
"done" - on review
"accepted" - accepted

filter_by : List[Dict], optional¶

Filter for entities. Each element is a dict with keys field, operator, value. Example: [{"field": "name", "operator": "in", "value": ["image_01", "image_02"]}].

Returns:

Count of entities in the Labeling Queue with given status.

Return type:

int

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()

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 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()

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.

Return type:

LabelingQueueInfo

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()

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 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()

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, collection_id=None)[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.
collection_id : int, optional¶: Entities Collection ID in Supervisely.

Returns:

List of information about Labeling Queues.

Return type:

List[LabelingQueueInfo]

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()

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

Returns:

List of entities.

Return type:

List[dict]

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=None¶: Semaphore for limiting the number of simultaneous requests.

Returns:

List of images in dataset.

Return type:

AsyncGenerator[List[ImageInfo]]

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()

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 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()

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

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 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()

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 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()

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:

None

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