LabelingJobApi¶

class LabelingJobApi(api)[source]¶

Bases: RemoveableBulkModuleApi, ModuleWithStatus

API for working with labeling jobs.

Parameters:

api¶: Api object to use for API connection.

Usage Example:

import supervisely as sly
api = sly.Api.from_env()
jobs = api.labeling_job.get_list(9)

Methods

`archive`	Archives Labeling Job with given ID.
`clone`	Clone Labeling Job with given ID.
`convert_info_to_json`	Convert information about an entity to a dictionary.
`create`	Creates Labeling Job and assigns given Users to it.
`exists`	Checks if an entity with the given parent_id and name exists
`get_activity`
`get_annotations`	Return annotations for given image ids from labeling job with given id.
`get_custom_data`	Get custom data of Labeling Job with given ID.
`get_free_name`	Generates a free name for an entity with the given parent_id and name.
`get_info_by_id`	Get Labeling Job 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 Job 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 job with given id.
`get_stats`	Get stats of given Labeling Job ID.
`get_status`	Get status of Labeling Job with given ID.
`info_sequence`	Sequence of fields that are returned by the API to represent LabelingJobInfo.
`info_tuple_name`	Name of the tuple that represents LabelingJobInfo.
`raise_for_status`
`reject_annotations`	Reject annotations for all or unmarked entities in the labeling job with given id.
`remove`	Remove an entity with the specified ID from the Supervisely server.
`remove_batch`	Remove entities in batches from the Supervisely server.
`restart`	Restart Labeling Job with given ID.
`set_custom_data`	Update or replace custom data of Labeling Job with given ID.
`set_entity_review_status`	Sets review status for entity with given ID.
`set_status`	Sets Labeling Job status.
`stop`	Makes Labeling Job unavailable for labeler with given User ID.
`wait`	Wait for a Labeling Job to change to the expected target 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 LabelingJobInfo

class Status(*values)[source]¶

Bases: StrEnum

Labeling job lifecycle status values returned by the API.

classmethod has_value(value)¶

Check if a value is in the enum.

Parameters:

value : str¶: Value to check.

Returns:

True if value is in the enum, False otherwise.

Return type:

bool

classmethod values()¶: Get all values of the enum.

COMPLETED = 'completed'¶

IN_PROGRESS = 'in_progress'¶

ON_REVIEW = 'on_review'¶

PENDING = 'pending'¶

REVIEW_COMPLETED = 'review_completed'¶

STOPPED = 'stopped'¶

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]¶

Sequence of fields that are returned by the API to represent LabelingJobInfo.

Usage Example:

LabelingJobInfo(
    id=2,
    name='Annotation Job (#1) (#1) (dataset_01)',
    readme='',
    description='',
    team_id=4,
    workspace_id=8,
    workspace_name='First Workspace',
    project_id=58,
    project_name='tutorial_project',
    dataset_id=54,
    dataset_name='dataset_01',
    created_by_id=4,
    created_by_login='anna',
    assigned_to_id=4,
    assigned_to_login='anna',
    reviewer_id=4,
    reviewer_login='anna',
    created_at='2020-04-08T15:10:12.618Z',
    started_at='2020-04-08T15:10:19.833Z',
    finished_at='2020-04-08T15:13:39.788Z',
    status='completed',
    disabled=False,
    labeling_queue_id=3,
    labeling_exam_id=None,
    images_count=3,
    finished_images_count=0,
    rejected_images_count=1,
    accepted_images_count=2,
    progress_images_count=2,
    classes_to_label=[],
    tags_to_label=[],
    images_range=(1, 5),
    objects_limit_per_image=None,
    tags_limit_per_image=None,
    filter_images_by_tags=[],
    include_images_with_tags=[],
    exclude_images_with_tags=[],
    entities=None,
    priority=2
)

static info_tuple_name()[source]¶: Name of the tuple that represents LabelingJobInfo.

archive(id)[source]¶

Archives Labeling Job with given ID.

Parameters:

id : int¶: Labeling Job ID in Supervisely.

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_job.archive(23)

clone(id, new_title=None, reviewer_id=None, assignee_ids=None)[source]¶

Clone Labeling Job with given ID.

Parameters:

id : int¶: Labeling Job ID in Supervisely.
new_title : str, optional¶: New title for the job
reviewer_id : int, optional¶: ID of the reviewer
assignee_ids : List[int], optional¶: List of User IDs to assign the job

Returns:

List of information about Labeling Jobs.

Return type:

List[LabelingJobInfo]

create(name, dataset_id, user_ids, readme=None, description=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=[], dynamic_classes=False, dynamic_tags=False, disable_confirm=None, disable_submit=None, toolbox_settings=None, enable_quality_check=None, guide_id=None, allow_restore=False, read_only_tags=None)[source]¶

Creates Labeling Job and assigns given Users to it.

Parameters:

name : str¶: Labeling Job name in Supervisely.
dataset_id : int¶: Dataset ID in Supervisely.
user_ids : List[int]¶: User IDs in Supervisely to assign Users as labelers to Labeling Job.
readme : str, optional¶: Additional information about Labeling Job.
description : str, optional¶: Description of Labeling Job.
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 Job.
images_ids : List[int], optional¶: List of images ids to label in dataset
dynamic_classes : bool, optional¶: If True, classes created after creating the job will be available for annotators
dynamic_tags : bool, optional¶: If True, tags created after creating the job 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.
enable_quality_check : bool, optional¶: If True, adds an intermediate step between “review” and completing the Labeling Job.
guide_id : int, optional¶: Guide ID in Supervisely to assign a guide to the Labeling Job.
allow_restore : bool¶: If True, allows restoring a previously deleted labeling job with the same name in the same dataset.

Returns:

List of LabelingJobInfo objects with information about new Labeling Jobs.

Return type:

List[LabelingJobInfo]

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_jobs = api.labeling_job.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_jobs)

# >>> List[LabelingJobInfo(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_jobs = api.labeling_job.create(
name="Labeling Job name",
dataset_id=dataset_id,
user_ids=[user_id],
readme="Labeling Job 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_jobs)

# >>> List[LabelingJobInfo(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_annotations(id, image_ids=None, project_meta=None, image_infos=None)[source]¶

Return annotations for given image ids from labeling job with given id. To speed up the process, you can provide image infos, which will be used instead of fetching them from the API.

Parameters:

id : int¶: Labeling Job ID in Supervisely.
image_ids : List[int], optional¶: Image IDs in Supervisely. If not provided, you must provide image_infos. Have lower priority than image_infos.
project_meta=None¶: Project meta of the labeling job with given id. Can be retrieved with get_project_meta().
image_infos=None¶: List of ImageInfo objects. If not provided, will be retrieved from the API. Have higher priority than image_ids.

Returns:

Annotation for given image id from labeling job with given id.

Return type:

Annotation

get_custom_data(id)[source]¶

Get custom data of Labeling Job with given ID.

Parameters:

id : int¶: Labeling Job ID in Supervisely.

Returns:

Custom data of the job

Return type:

dict

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()

custom_data = api.labeling_job.get_custom_data(9)
print(custom_data)

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 Job information by ID.

Parameters:

id : int¶: Labeling Job ID in Supervisely.

Returns:

LabelingJobInfo object with information about the Labeling Job.

Return type:

LabelingJobInfo

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_job.get_info_by_id(2)
print(label_job_info)
# Output: [
#     2,
#     "Annotation Job (#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, created_by_id=None, assigned_to_id=None, project_id=None, dataset_id=None, show_disabled=False, reviewer_id=None, is_part_of_queue=True, queue_ids=None, exclude_statuses=None)[source]¶

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

Parameters:

team_id : int¶: Team ID in Supervisely.
created_by_id : int, optional¶: ID of the User who created the LabelingJob.
assigned_to_id : int, optional¶: ID of the assigned User.
project_id : int, optional¶: Project ID in Supervisely.
dataset_id : int, optional¶: Dataset ID in Supervisely.
show_disabled : bool, optional¶: Show disabled Labeling Jobs.
reviewer_id : int, optional¶: ID of the User who reviews the LabelingJob.
is_part_of_queue : bool, optional¶: Filter by Labeling Queue. If True, all existing Labeling Jobs are returned. If False, only Labeling Jobs that are not part of the queue are returned.
queue_ids : Union[List, int], optional¶: IDs of the Labeling Queues. If set, only Labeling Jobs from the selected queues are returned. Arg is_part_of_queue must be True.
exclude_statuses : List[Literal["pending", "in_progress", "on_review", "completed"]], optional¶: Exclude Labeling Jobs with given statuses.

Returns:

List of LabelingJobInfo objects with information about Labeling Jobs.

Return type:

List[LabelingJobInfo]

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_job.get_list(4)
print(label_jobs)
# Output: [
#     [
#         2,
#         "Annotation Job (#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,
#         null,
#         3,
#         0,
#         1,
#         2,
#         2,
#         [],
#         [],
#         [
#             1,
#             5
#         ],
#         null,
#         null,
#         [],
#         [],
#         [],
#         null
#     ],
#     [
#         3,
#         "Annotation Job (#1) (#2) (dataset_02)",
#         "",
#         "",
#         4,
#         8,
#         "First Workspace",
#         58,
#         "tutorial_project",
#         55,
#         "dataset_02",
#         4,
#         "anna",
#         4,
#         "anna",
#         4,
#         "anna",
#         "2020-04-08T15:10:12.618Z",
#         "2020-04-08T15:15:46.749Z",
#         "2020-04-08T15:17:33.572Z",
#         "completed",
#         false,
#         3,
#         null,
#         2,
#         0,
#         0,
#         2,
#         2,
#         [],
#         [],
#         [
#             1,
#             5
#         ],
#         null,
#         null,
#         [],
#         [],
#         [],
#         null
#     ]
# ]

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 job with given id.

Parameters:

id : int¶: Labeling Job ID in Supervisely.

Returns:

Project meta of the labeling job with given id.

Return type:

ProjectMeta

get_stats(id)[source]¶

Get stats of given Labeling Job ID.

Parameters:

id : int¶: Labeling Job ID in Supervisely.

Returns:

Dict with information about given Labeling Job

Return type:

dict

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()

status = api.labeling_job.get_stats(3)
print(status)
# Output: {
#     "job": {
#         "editingDuration": 0,
#         "annotationDuration": 720,
#         "id": 3,
#         "name": "Annotation Job (#1) (#2) (dataset_02)",
#         "startedAt": "2020-04-08T15:15:46.749Z",
#         "finishedAt": "2020-04-08T15:17:33.572Z",
#         "imagesCount": 2,
#         "finishedImagesCount": 2,
#         "tagsStats": [
#             {
#                 "id": 24,
#                 "color": "#ED68A1",
#                 "images": 1,
#                 "figures": 1,
#                 "name": "car_color"
#             },
#             {
#                 "id": 19,
#                 "color": "#A0A08C",
#                 "images": 0,
#                 "figures": 1,
#                 "name": "cars_number"
#             },
#             {
#                 "id": 20,
#                 "color": "#D98F7E",
#                 "images": 1,
#                 "figures": 1,
#                 "name": "like"
#             },
#             {
#                 "id": 23,
#                 "color": "#65D37C",
#                 "images": 0,
#                 "figures": 1,
#                 "name": "person_gender"
#             },
#             {
#                 "parentId": 23,
#                 "color": "#65D37C",
#                 "images": 0,
#                 "figures": 1,
#                 "name": "person_gender (male)"
#             },
#             {
#                 "parentId": 23,
#                 "color": "#65D37C",
#                 "images": 0,
#                 "figures": 0,
#                 "name": "person_gender (female)"
#             },
#             {
#                 "id": 21,
#                 "color": "#855D79",
#                 "images": 1,
#                 "figures": 1,
#                 "name": "situated"
#             },
#             {
#                 "parentId": 21,
#                 "color": "#855D79",
#                 "images": 1,
#                 "figures": 1,
#                 "name": "situated (inside)"
#             },
#             {
#                 "parentId": 21,
#                 "color": "#855D79",
#                 "images": 0,
#                 "figures": 0,
#                 "name": "situated (outside)"
#             },
#             {
#                 "id": 22,
#                 "color": "#A2B4FA",
#                 "images": 0,
#                 "figures": 1,
#                 "name": "vehicle_age"
#             },
#             {
#                 "parentId": 22,
#                 "color": "#A2B4FA",
#                 "images": 0,
#                 "figures": 1,
#                 "name": "vehicle_age (modern)"
#             },
#             {
#                 "parentId": 22,
#                 "color": "#A2B4FA",
#                 "images": 0,
#                 "figures": 0,
#                 "name": "vehicle_age (vintage)"
#             }
#         ]
#     },
#     "classes": [
#         {
#             "id": 43,
#             "color": "#F6FF00",
#             "shape": "rectangle",
#             "totalDuration": 0,
#             "imagesCount": 0,
#             "avgDuration": null,
#             "name": "bike",
#             "labelsCount": 0
#         },
#         {
#             "id": 42,
#             "color": "#BE55CE",
#             "shape": "polygon",
#             "totalDuration": 0,
#             "imagesCount": 0,
#             "avgDuration": null,
#             "name": "car",
#             "labelsCount": 0
#         },
#         {
#             "id": 41,
#             "color": "#FD0000",
#             "shape": "polygon",
#             "totalDuration": 0,
#             "imagesCount": 0,
#             "avgDuration": null,
#             "name": "dog",
#             "labelsCount": 0
#         },
#         {
#             "id": 40,
#             "color": "#00FF12",
#             "shape": "bitmap",
#             "totalDuration": 0,
#             "imagesCount": 0,
#             "avgDuration": null,
#             "name": "person",
#             "labelsCount": 0
#         }
#     ],
#     "images": {
#         "total": 2,
#         "images": [
#             {
#                 "id": 285,
#                 "reviewStatus": "accepted",
#                 "annotationDuration": 0,
#                 "totalDuration": 0,
#                 "name": "image_01",
#                 "labelsCount": 0
#             },
#             {
#                 "id": 284,
#                 "reviewStatus": "accepted",
#                 "annotationDuration": 0,
#                 "totalDuration": 0,
#                 "name": "image_02",
#                 "labelsCount": 0
#             }
#         ]
#     }
# }

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_job.get_status(4)
print(job_status) # pending

reject_annotations(id, mode='all')[source]¶

Reject annotations for all or unmarked entities in the labeling job with given id.

Parameters:

id : int¶: Labeling Job ID in Supervisely.
mode : str, optional¶: Reject mode. Can be “all” or “unmarked”.

Returns:

None

Return type:

None

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)

restart(id, assignee_ids=None, reviewer_id=None, title=None, complete_existing=True, only_rejected_entities=True, ignore_no_rejected_error=False)[source]¶

Restart Labeling Job with given ID.

Parameters:

id : int¶: Labeling Job ID in Supervisely.
assignee_ids : List[int], optional¶: List of User IDs to assign the job. If not set, the job will be assigned to the same user as the existing job.
reviewer_id : int, optional¶: ID of the reviewer
title : str, optional¶: New title for the job <= 255 characters
complete_existing : bool, optional¶: If False, existing job will not be completed.
only_rejected_entities : bool, optional¶: If False, all entities that do not have an “accepted” status will be included in new job, all unmarked entities will be rejected for the existing job.
ignore_errors : bool, optional: If True, the job will not be restarted if there are errors in request data.

Returns:

List of dicts with information about created Labeling Jobs.

Return type:

List[dict]

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_info_list = api.labeling_job.restart(222)

print(job_info_list)
# Output:
#   [
#       {
#           'id': 940,
#           'userId': 342,
#           'type': 'annotation',
#           'name': 'Annotation Job (#2)'
#       }
#   ]

set_custom_data(id, custom_data, update=True)[source]¶

Update or replace custom data of Labeling Job with given ID. By default, updates existing custom data. To replace it entirely, set update to False.

Parameters:

id : int¶: Labeling Job ID in Supervisely.
custom_data : dict¶: Custom data to set
update : bool¶: Whether to update existing custom data or replace it entirely.

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_job.set_custom_data(9, {"key": "value"})

set_entity_review_status(id, entity_id, status)[source]¶

Sets review status for entity with given ID.

Parameters:

id : int¶: Labeling Job ID in Supervisely.
entity_id : int¶: Entity ID
status : str¶: New review status for entity

Returns:

None

Return type:

None

set_status(id, status)[source]¶

Sets Labeling Job status.

Parameters:

id : int¶: Labeling Job ID in Supervisely.
status : str¶: New Labeling Job 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_job.set_status(id=9, status="completed")

stop(id)[source]¶

Makes Labeling Job unavailable for labeler with given User ID.

Parameters:

id : int¶: User ID in Supervisely.

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_job.stop(9)

wait(id, target_status, wait_attempts=None, wait_attempt_timeout_sec=None)[source]¶

Wait for a Labeling Job to change to the expected target status.

Parameters:

id : int¶: Labeling Job ID in Supervisely.
target_status : str¶: Expected result status of Labeling Job.
wait_attempts : int, optional¶: Number of attempts to retry, when WaitingTimeExceeded raises.
wait_attempt_timeout_sec : int, optional¶: Time between attempts.

:raises WaitingTimeExceeded: if waiting time exceeded :returns: None :rtype: 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_job.wait(4, 'completed', wait_attempts=2, wait_attempt_timeout_sec=1)
# supervisely.api.module_api.WaitingTimeExceeded: Waiting time exceeded