Labeling Job API¶
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class
supervisely_lib.api.labeling_job_api.LabelingJobApi(api)[source]¶ Bases:
supervisely_lib.api.module_api.RemoveableModuleApi,supervisely_lib.api.module_api.ModuleWithStatusAPI for working with Labeling Jobs.
LabelingJobApiobject is immutable.- Parameters
api (Api) – API connection to the server.
- Usage example
# You can connect to API directly address = 'https://app.supervise.ly/' token = 'Your Supervisely API Token' api = sly.Api(address, token) # Or you can use API from environment os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly' os.environ['API_TOKEN'] = 'Your Supervisely API Token' api = sly.Api.from_env() jobs = api.labeling_job.get_list(9) # api usage example
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class
Status(value)[source]¶ Bases:
supervisely_lib.collection.str_enum.StrEnumAn enumeration.
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PENDING= 'pending'¶
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IN_PROGRESS= 'in_progress'¶
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ON_REVIEW= 'on_review'¶
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COMPLETED= 'completed'¶
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STOPPED= 'stopped'¶
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static
info_sequence()[source]¶ NamedTuple LabelingJobInfo information about Labeling Job.
- 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, 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)
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create(name: str, dataset_id: int, user_ids: List[int], readme: str = None, description: str = None, classes_to_label: List[str] = None, objects_limit_per_image: int = None, tags_to_label: List[str] = None, tags_limit_per_image: int = None, include_images_with_tags: List[str] = None, exclude_images_with_tags: List[str] = None, images_range: List[int, int] = None, reviewer_id: int = None) → List[NamedTuple][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.
- Returns
List of information about new Labeling Job. See
info_sequence- Return type
List[NamedTuple]- Usage example
os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly' os.environ['API_TOKEN'] = 'Your Supervisely API Token' api = sly.Api.from_env() user_name = 'alex' dataset_id = 602 new_label_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_label_jobs) # Output: [ # [ # 92, # "alex (#1) (#3)", # "Readmy text", # "Work for labelers", # 13, # 29, # "Labelling Workspace", # 494, # "Test Dataset", # 602, # "ds1", # 8, # "alex", # 111, # "quantigo273", # 8, # "alex", # "2021-03-25T11:04:34.031Z", # null, # null, # "pending", # false, # 3, # 0, # 0, # 0, # 0, # [], # [], # [ # null, # null # ], # 5, # 3, # [], # [], # [], # [ # { # "reviewStatus": "none", # "id": 287244, # "name": "IMG_0813" # }, # { # "reviewStatus": "none", # "id": 287246, # "name": "IMG_0432" # }, # { # "reviewStatus": "none", # "id": 287245, # "name": "IMG_0315" # } # ] # ], # [ # 93, # "alex (#2) (#3)", # "Readmy text", # "Work for labelers", # 13, # 29, # "Labelling Workspace", # 494, # "Test Dataset", # 602, # "ds1", # 8, # "alex", # 222, # "quantigo19", # 8, # "alex", # "2021-03-25T11:04:34.031Z", # null, # null, # "pending", # false, # 3, # 0, # 0, # 0, # 0, # [], # [], # [ # null, # null # ], # 5, # 3, # [], # [], # [], # [ # { # "reviewStatus": "none", # "id": 287248, # "name": "IMG_8454" # }, # { # "reviewStatus": "none", # "id": 287249, # "name": "IMG_6896" # }, # { # "reviewStatus": "none", # "id": 287247, # "name": "IMG_1942" # } # ] # ] # ]
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get_list(team_id: int, created_by_id: Optional[int] = None, assigned_to_id: Optional[int] = None, project_id: Optional[int] = None, dataset_id: Optional[int] = None, show_disabled: bool = False) → List[NamedTuple][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.
- Returns
List of information about Labeling Jobs. See
info_sequence- Return type
List[NamedTuple]- Usage example
os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly' os.environ['API_TOKEN'] = 'Your Supervisely API Token' 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, # 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, # 2, # 0, # 0, # 2, # 2, # [], # [], # [ # 1, # 5 # ], # null, # null, # [], # [], # [], # null # ] # ]
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stop(id: int) → None[source]¶ Makes Labeling Job unavailable for labeler with given User ID.
- Parameters
id (int) – User ID in Supervisely.
- Returns
None
- Return type
NoneType- Usage example
os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly' os.environ['API_TOKEN'] = 'Your Supervisely API Token' api = sly.Api.from_env() api.labeling_job.stop(9)
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get_info_by_id(id: int) → NamedTuple[source]¶ Get Labeling Job information by ID.
- Parameters
id (int) – Labeling Job ID in Supervisely.
- Returns
Information about Labeling Job. See
info_sequence- Return type
NamedTuple- Usage example
os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly' os.environ['API_TOKEN'] = 'Your Supervisely API Token' 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" # } # ] # ]
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archive(id: int) → None[source]¶ Archives Labeling Job with given ID.
- Parameters
id (int) – Labeling Job ID in Supervisely.
- Returns
None
- Return type
NoneType- Usage example
os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly' os.environ['API_TOKEN'] = 'Your Supervisely API Token' api = sly.Api.from_env() api.labeling_job.archive(23)
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get_status(id: int) → Status[source]¶ Get status of Labeling Job with given ID.
- Parameters
id (int) – Labeling job ID in Supervisely.
- Returns
Status object
- Return type
- Usage example
os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly' os.environ['API_TOKEN'] = 'Your Supervisely API Token' api = sly.Api.from_env() job_status = api.labeling_job.get_status(4) print(job_status) # pending
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wait(id: int, target_status: str, wait_attempts: Optional[int] = None, wait_attempt_timeout_sec: Optional[int] = None) → 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
WaitingTimeExceededraises.wait_attempt_timeout_sec (int, optional) – Time between attempts.
- Raises
WaitingTimeExceeded, if waiting time exceeded- Returns
None
- Return type
NoneType- Usage example
os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly' os.environ['API_TOKEN'] = 'Your Supervisely API Token' api = sly.Api.from_env() api.labeling_job.wait(4, 'completed', wait_attempts=2, wait_attempt_timeout_sec=1) # supervisely_lib.api.module_api.WaitingTimeExceeded: Waiting time exceeded
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get_stats(id: int) → dict[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
os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly' os.environ['API_TOKEN'] = 'Your Supervisely API Token' 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 # } # ] # } # }
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get_activity(id: int) → pandas.core.frame.DataFrame[source]¶ Get all activity for given Labeling Job by ID.
- Parameters
id (int) – Labeling Job ID in Supervisely.
- Returns
Activity data as pd.DataFrame
- Return type
pd.DataFrame- Usage example
os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly' os.environ['API_TOKEN'] = 'Your Supervisely API Token' api = sly.Api.from_env() activity = api.labeling_job.get_activity(3) print(activity) # Output: # userId action ... tagId meta # 0 4 update_figure ... NaN {} # 1 4 create_figure ... NaN {} # 2 4 attach_tag ... 20.0 {} # 3 4 attach_tag ... 21.0 {'value': 'inside'} # 4 4 attach_tag ... 24.0 {'value': '12'} # 5 4 update_figure ... NaN {} # 6 4 update_figure ... NaN {} # 7 4 update_figure ... NaN {} # 8 4 create_figure ... NaN {} # 9 4 update_figure ... NaN {} # [10 rows x 18 columns]
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InfoType¶ alias of
supervisely_lib.api.module_api.LabelingJobInfo