DatasetApi¶

class DatasetApi[source]¶

Bases: supervisely.api.module_api.UpdateableModule, supervisely.api.module_api.RemoveableModuleApi

API for working with Dataset. DatasetApi 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.supervise.ly", token="4r47N...xaTatb")

project_id = 1951
ds = api.dataset.get_list(project_id)

Methods

`copy`	Copies given Dataset in destination Project by ID.
`copy_batch`	Copy given Datasets to the destination Project by IDs.
`create`	Create Dataset with given name in the given Project.
`exists`	Checks if an entity with the given parent_id and name exists
`get_free_name`	Generates a free name for an entity with the given parent_id and name.
`get_info_by_id`	Get Datasets information by ID.
`get_info_by_name`	Get information about an entity by its name from the Supervisely server.
`get_list`	List of Datasets in the given Project.
`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_or_create`	Checks if Dataset with given name already exists in the Project, if not creates Dataset with the given name.
`info_sequence`	NamedTuple DatasetInfo information about Dataset.
`info_tuple_name`	NamedTuple name - DatasetInfo.
`move`	Moves given Dataset in destination Project by ID.
`move_batch`	Moves given Datasets to the destination Project by IDs.
`remove`	Remove an entity with the specified ID from the Supervisely server.
`remove_batch`	Remove entities with given IDs from the Supervisely server.
`update`

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.DatasetInfo

copy(dst_project_id, id, new_name=None, change_name_if_conflict=False, with_annotations=False)[source]¶

Copies given Dataset in destination Project by ID.

Parameters

dst_project_id : int: Destination Project ID in Supervisely.
id : int: ID of copied Dataset.
new_name : str, optional: New Dataset name.
change_name_if_conflict : bool, optional: Checks if given name already exists and adds suffix to the end of the name.
with_annotations : bool, optional: If True copies Dataset with annotations, otherwise copies just items from Dataset without annotation.

Returns

Information about Dataset. See info_sequence

Return type

DatasetInfo

Usage example

import supervisely as sly

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

dst_proj_id = 1982
ds = api.dataset.get_list(dst_proj_id)
print(len(ds)) # 0

new_ds = api.dataset.copy(dst_proj_id, id=2540, new_name="banana", with_annotations=True)
ds = api.dataset.get_list(dst_proj_id)
print(len(ds)) # 1

copy_batch(dst_project_id, ids, new_names=None, change_name_if_conflict=False, with_annotations=False)[source]¶

Copy given Datasets to the destination Project by IDs.

Parameters

dst_project_id : int: Destination Project ID in Supervisely.
ids : List[int]: IDs of copied Datasets.
new_names : List[str], optional: New Datasets names.
change_name_if_conflict : bool, optional: Checks if given name already exists and adds suffix to the end of the name.
with_annotations : bool, optional: If True copies Datasets with annotations, otherwise copies just items from Datasets without annotations.

Raises

RuntimeError if can not match “ids” and “new_names” lists, len(ids) != len(new_names)

Returns

Information about Datasets. See info_sequence

Return type

List[DatasetInfo]

Usage example

import supervisely as sly

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

dst_proj_id = 1980
ds = api.dataset.get_list(dst_proj_id)
print(len(ds)) # 0

ds_ids = [2532, 2557]
ds_names = ["lemon_test", "kiwi_test"]

copied_datasets = api.dataset.copy_batch(dst_proj_id, ids=ds_ids, new_names=ds_names, with_annotations=True)
ds = api.dataset.get_list(dst_proj_id)
print(len(ds)) # 2

create(project_id, name, description='', change_name_if_conflict=False)[source]¶

Create Dataset with given name in the given Project.

Parameters

project_id : int: Project ID in Supervisely where Dataset will be created.
name : str: Dataset Name.
description : str, optional: Dataset description.
change_name_if_conflict : bool, optional: Checks if given name already exists and adds suffix to the end of the name.

Returns

Information about Dataset. See info_sequence

Return type

DatasetInfo

Usage example

import supervisely as sly

project_id = 116482

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

ds_info = api.dataset.get_list(project_id)
print(len(ds_info)) # 1

new_ds = api.dataset.create(project_id, 'new_ds')
new_ds_info = api.dataset.get_list(project_id)
print(len(new_ds_info)) # 2

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.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()


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

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.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()


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, raise_error=False)[source]¶

Get Datasets information by ID.

Parameters

id : int: Dataset ID in Supervisely.

Returns

Information about Dataset. See info_sequence

Return type

DatasetInfo

Usage example

import supervisely as sly

dataset_id = 384126

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

ds_info = api.dataset.get_info_by_id(dataset_id)

get_info_by_name(parent_id, name)¶

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

Usage example

import supervisely as sly

# 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()


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(project_id, filters=None)[source]¶

List of Datasets in the given Project.

Parameters

project_id : int: Project ID in which the Datasets are located.
filters : List[dict], optional: List of params to sort output Datasets.

Returns

List of all Datasets with information for the given Project. See info_sequence

Return type

List[DatasetInfo]

Usage example

import supervisely as sly

project_id = 1951

os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'
api = sly.Api.from_env()
ds = api.dataset.get_list(project_id)

print(ds)
# Output: [
#     DatasetInfo(id=2532,
#                 name="lemons",
#                 description="",
#                 size="861069",
#                 project_id=1951,
#                 images_count=6,
#                 items_count=6,
#                 created_at="2021-03-02T10:04:33.973Z",
#                 updated_at="2021-03-10T09:31:50.341Z",
#                 reference_image_url="http://app.supervise.ly/z6ut6j8bnaz1vj8aebbgs4-public/images/original/...jpg"),
#                 DatasetInfo(id=2557,
#                 name="kiwi",
#                 description="",
#                 size="861069",
#                 project_id=1951,
#                 images_count=6,
#                 items_count=6,
#                 created_at="2021-03-10T09:31:33.701Z",
#                 updated_at="2021-03-10T09:31:44.196Z",
#                 reference_image_url="http://app.supervise.ly/h5un6l2bnaz1vj8a9qgms4-public/images/original/...jpg")
# ]

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

get_or_create(project_id, name, description='')[source]¶

Checks if Dataset with given name already exists in the Project, if not creates Dataset with the given name.

Parameters

project_id : int: Project ID in Supervisely.
name : str: Dataset name.
description : str, optional: Dataset description.

Returns

Information about Dataset. See info_sequence

Return type

DatasetInfo

Usage example

import supervisely as sly

project_id = 116482

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

ds_info = api.dataset.get_list(project_id)
print(len(ds_info)) # 1

api.dataset.get_or_create(project_id, 'ds1')
ds_info = api.dataset.get_list(project_id)
print(len(ds_info)) # 1

api.dataset.get_or_create(project_id, 'new_ds')
ds_info = api.dataset.get_list(project_id)
print(len(ds_info)) # 2

static info_sequence()[source]¶

NamedTuple DatasetInfo information about Dataset.

Example

DatasetInfo(id=452984,
            name='ds0',
            description='',
            size='3997776',
            project_id=118909,
            images_count=11,
            items_count=11,
            created_at='2021-03-03T15:54:08.802Z',
            updated_at='2021-03-16T09:31:37.063Z',
            reference_image_url='https://app.supervise.ly/h5un6l2bnaz1vj8a9qgms4-public/images/original/K/q/jf/...png')

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

move(dst_project_id, id, new_name=None, change_name_if_conflict=False, with_annotations=False)[source]¶

Moves given Dataset in destination Project by ID.

Parameters

dst_project_id : int: Destination Project ID in Supervisely.
id : int: ID of moved Dataset.
new_name : str, optional: New Dataset name.
change_name_if_conflict : bool, optional: Checks if given name already exists and adds suffix to the end of the name.
with_annotations : bool, optional: If True moves Dataset with annotations, otherwise moves just items from Dataset without annotation.

Returns

Information about Dataset. See info_sequence

Return type

DatasetInfo

Usage example

import supervisely as sly

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

dst_proj_id = 1985
ds = api.dataset.get_list(dst_proj_id)
print(len(ds)) # 0

new_ds = api.dataset.move(dst_proj_id, id=2550, new_name="cucumber", with_annotations=True)
ds = api.dataset.get_list(dst_proj_id)
print(len(ds)) # 1

move_batch(dst_project_id, ids, new_names=None, change_name_if_conflict=False, with_annotations=False)[source]¶

Moves given Datasets to the destination Project by IDs.

Parameters

dst_project_id : int: Destination Project ID in Supervisely.
ids : List[int]: IDs of moved Datasets.
new_names : List[str], optional: New Datasets names.
change_name_if_conflict : bool, optional: Checks if given name already exists and adds suffix to the end of the name.
with_annotations : bool, optional: If True moves Datasets with annotations, otherwise moves just items from Datasets without annotations.

Raises

RuntimeError if can not match “ids” and “new_names” lists, len(ids) != len(new_names)

Returns

Information about Datasets. See info_sequence

Return type

List[DatasetInfo]

Usage example

import supervisely as sly

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

dst_proj_id = 1978
ds = api.dataset.get_list(dst_proj_id)
print(len(ds)) # 0

ds_ids = [2545, 2560]
ds_names = ["banana_test", "mango_test"]

movied_datasets = api.dataset.move_batch(dst_proj_id, ids=ds_ids, new_names=ds_names, with_annotations=True)
ds = api.dataset.get_list(dst_proj_id)
print(len(ds)) # 2

remove(id)¶

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

Parameters

id : int: Entity ID in Supervisely

remove_batch(ids, progress_cb=None)¶

Remove entities with given IDs from the Supervisely server.

Parameters

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

update(id, name=None, description=None)¶