AnnotationApi¶

class AnnotationApi[source]¶

Bases: supervisely.api.module_api.ModuleApi

Annotation for a single image. AnnotationApi 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")

dataset_id = 254737
ann_infos = api.annotation.get_list(dataset_id)

Methods

`append_labels`	Append labels to image with given ID in API.
`copy`	Copy annotation from one image ID to another image ID in API.
`copy_batch`	Copy annotations from one images IDs to another in API.
`copy_batch_by_ids`	Copy annotations from one images IDs to another images IDs in API.
`download`	Download AnnotationInfo by image ID from API.
`download_async`	Download AnnotationInfo by image ID from API.
`download_batch`	Get list of AnnotationInfos for given dataset ID from API.
`download_batch_async`	Get list of AnnotationInfos for given dataset ID from API.
`download_bulk_async`	Get list of AnnotationInfos for given dataset ID from API.
`download_json`	Download Annotation in json format by image ID from API.
`download_json_batch`	Get list of AnnotationInfos for given dataset ID from API.
`exists`
`get_free_name`
`get_info_by_id`
`get_info_by_name`
`get_label_by_id`	Returns Supervisely Label object by it's ID.
`get_list`	Get list of information about all annotations for a given dataset.
`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_generator`	Get list of information about all annotations for a given dataset.
`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.
`info_sequence`	NamedTuple AnnotationInfo information about Annotation.
`info_tuple_name`	NamedTuple name - AnnotationInfo.
`update_label`	Updates label with given ID in Supervisely with new Label object.
`update_label_priority`	Updates label's priority with given ID in Supervisely.
`upload_ann`	Loads an `Annotation` to a given image ID in the API.
`upload_anns`	Loads an `Annotations` to a given images IDs in the API.
`upload_json`	Loads an annotation from dict to a given image ID in the API.
`upload_jsons`	Loads an annotations from dicts to a given images IDs in the API.
`upload_path`	Loads an annotation from a given path to a given image ID in the API.
`upload_paths`	Loads an annotations from a given paths to a given images IDs in the API.

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.AnnotationInfo

append_labels(image_id, labels, skip_bounds_validation=False)[source]¶

Append labels to image with given ID in API.

Parameters

image_id : int: Image ID to append labels.
labels : List[Label]: List of labels to append.

Returns

None

Return type

NoneType

copy(src_image_id, dst_image_id, force_metadata_for_links=True, skip_bounds_validation=False)[source]¶

Copy annotation from one image ID to another image ID in API.

Parameters

src_image_id : int: Image ID in Supervisely.
dst_image_id : int: Image ID in Supervisely.

Returns

None

Return type

NoneType

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()

src_id = 121236918
dst_id = 547837053
api.annotation.copy(src_id, dst_id)

copy_batch(src_image_ids, dst_image_ids, progress_cb=None, force_metadata_for_links=True, skip_bounds_validation=False)[source]¶

Copy annotations from one images IDs to another in API.

Parameters

src_image_ids : List[int]: Images IDs in Supervisely.
dst_image_ids : List[int]: Unique IDs of images in API.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Raises

RuntimeError, if len(src_image_ids) != len(dst_image_ids)

Returns

None

Return type

NoneType

Usage example

import supervisely as sly
from tqdm import tqdm

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

src_ids = [121236918, 121236919]
dst_ids = [547837053, 547837054]
p = tqdm(desc="Annotations copy: ", total=len(src_ids))

copy_anns = api.annotation.copy_batch(src_ids, dst_ids, progress_cb=p)
# Output:
# {"message": "progress", "event_type": "EventType.PROGRESS", "subtask": "Annotations copy: ", "current": 0, "total": 2, "timestamp": "2021-03-16T15:24:31.286Z", "level": "info"}
# {"message": "progress", "event_type": "EventType.PROGRESS", "subtask": "Annotations copy: ", "current": 2, "total": 2, "timestamp": "2021-03-16T15:24:31.288Z", "level": "info"}

copy_batch_by_ids(src_image_ids, dst_image_ids, batch_size=50, save_source_date=True)[source]¶

Copy annotations from one images IDs to another images IDs in API.

Parameters

src_image_ids : List[int]: Images IDs in Supervisely.
dst_image_ids : List[int]: Images IDs in Supervisely.

Returns

None

Return type

NoneType

Raises

RuntimeError if len(src_image_ids) != len(dst_image_ids)

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()

src_ids = [121236918, 121236919]
dst_ids = [547837053, 547837054]
api.annotation.copy_batch_by_ids(src_ids, dst_ids)

download(image_id, with_custom_data=False, force_metadata_for_links=True)[source]¶

Download AnnotationInfo by image ID from API.

Parameters

image_id : int: Image ID in Supervisely.
with_custom_data : bool, optional: Include custom data in the response.
force_metadata_for_links : bool, optional: Force metadata for links.

Returns

Information about Annotation. See info_sequence

Return type

AnnotationInfo

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()

image_id = 121236918
ann_info = api.annotation.download(image_id)
print(json.dumps(ann_info, indent=4))
# Output: [
#     121236918,
#     "IMG_0748.jpeg",
#     {
#         "description": "",
#         "tags": [],
#         "size": {
#             "height": 800,
#             "width": 1067
#         },
#         "objects": []
#     },
#     "2019-12-19T12:06:59.435Z",
#     "2021-02-06T11:07:26.080Z"
# ]

async download_async(image_id, semaphore=None, with_custom_data=False, force_metadata_for_links=True, progress_cb=None, progress_cb_type='number')[source]¶

Download AnnotationInfo by image ID from API.

Parameters

image_id : int: Image ID in Supervisely.
semaphore : asyncio.Semaphore, optional: Semaphore for limiting the number of simultaneous downloads.
with_custom_data : bool, optional: Include custom data in the response.
force_metadata_for_links : bool, optional: Force metadata for links.
progress_cb : tqdm or callable, optional: Function for tracking download progress.
progress_cb_type : str, optional: Type of progress callback. Can be “number” or “size”. Default is “number”.

Returns

Information about Annotation. See info_sequence

Return type

AnnotationInfo

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()

image_id = 121236918
loop = sly.utils.get_or_create_event_loop()
ann_info = loop.run_until_complete(api.annotation.download_async(image_id))

download_batch(dataset_id, image_ids, progress_cb=None, with_custom_data=False, force_metadata_for_links=True)[source]¶

Get list of AnnotationInfos for given dataset ID from API.

Parameters

dataset_id : int: Dataset ID in Supervisely.
image_ids : List[int]: List of integers.
progress_cb : tqdm: Function for tracking download progress.
with_custom_data : bool, optional: Include custom data in the response.
force_metadata_for_links : bool, optional: Force metadata for links.

Returns

Information about Annotations. See info_sequence

Return type

List[AnnotationInfo]

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()

dataset_id = 254737
image_ids = [121236918, 121236919]
p = tqdm(desc="Annotations downloaded: ", total=len(image_ids))

ann_infos = api.annotation.download_batch(dataset_id, image_ids, progress_cb=p)
# Output:
# {"message": "progress", "event_type": "EventType.PROGRESS", "subtask": "Annotations downloaded: ", "current": 0, "total": 2, "timestamp": "2021-03-16T15:20:06.168Z", "level": "info"}
# {"message": "progress", "event_type": "EventType.PROGRESS", "subtask": "Annotations downloaded: ", "current": 2, "total": 2, "timestamp": "2021-03-16T15:20:06.510Z", "level": "info"}

Optimizing the download process by using the context to avoid redundant API calls.:
# 1. Download the project meta
project_id = api.dataset.get_info_by_id(dataset_id).project_id
project_meta = api.project.get_meta(project_id)

# 2. Use the context to avoid redundant API calls
dataset_id = 254737
image_ids = [121236918, 121236919]
with sly.ApiContext(api, dataset_id=dataset_id, project_id=project_id, project_meta=project_meta):
    ann_infos = api.annotation.download_batch(dataset_id, image_ids)

async download_batch_async(dataset_id, image_ids, semaphore=None, with_custom_data=False, force_metadata_for_links=True, progress_cb=None, progress_cb_type='number')[source]¶

Get list of AnnotationInfos for given dataset ID from API.

Parameters

dataset_id : int: Dataset ID in Supervisely.
image_ids : List[int]: List of integers.
semaphore : asyncio.Semaphore, optional: Semaphore for limiting the number of simultaneous downloads.
with_custom_data : bool, optional: Include custom data in the response.
force_metadata_for_links : bool, optional: Force metadata for links.
progress_cb : tqdm or callable, optional: Function for tracking download progress. Total should be equal to len(image_ids) or None.
progress_cb_type : str, optional: Type of progress callback. Can be “number” or “size”. Default is “number”.

Returns

Information about Annotations. See info_sequence

Return type

List[AnnotationInfo]

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()

dataset_id = 254737
image_ids = [121236918, 121236919]
pbar = tqdm(desc="Download annotations", total=len(image_ids))

loop = sly.utils.get_or_create_event_loop()
ann_infos = loop.run_until_complete(
                    api.annotation.download_batch_async(dataset_id, image_ids, progress_cb=pbar)
                )

async download_bulk_async(dataset_id, image_ids, progress_cb=None, with_custom_data=False, force_metadata_for_links=True, semaphore=None)[source]¶

Get list of AnnotationInfos for given dataset ID from API. This method is optimized for downloading a large number of small size annotations with a single API call.

Parameters

dataset_id : int: Dataset ID in Supervisely.
image_ids : List[int]: List of integers.
progress_cb : tqdm: Function for tracking download progress.
with_custom_data : bool, optional: Include custom data in the response.
force_metadata_for_links : bool, optional: Force metadata for links.
semaphore : asyncio.Semaphore, optional: Semaphore for limiting the number of simultaneous downloads.

Returns

Information about Annotations. See info_sequence

Return type

List[AnnotationInfo]

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()

dataset_id = 254737
image_ids = [121236918, 121236919]
p = tqdm(desc="Annotations downloaded: ", total=len(image_ids))

ann_infos = await api.annotation.download_bulk_async(dataset_id, image_ids, progress_cb=p)

Optimizing the download process by using the context to avoid redundant API calls.:
# 1. Download the project meta
project_id = api.dataset.get_info_by_id(dataset_id).project_id
project_meta = api.project.get_meta(project_id)

# 2. Use the context to avoid redundant API calls
dataset_id = 254737
image_ids = [121236918, 121236919]
with sly.ApiContext(api, dataset_id=dataset_id, project_id=project_id, project_meta=project_meta):
    ann_infos = await api.annotation.download_bulk_async(dataset_id, image_ids)

download_json(image_id, with_custom_data=False, force_metadata_for_links=True)[source]¶

Download Annotation in json format by image ID from API.

Parameters

image_id : int: Image ID in Supervisely.
with_custom_data : bool, optional: Include custom data in the response.
force_metadata_for_links : bool, optional: Force metadata for links.

Returns

Annotation in json format

Return type

dict

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()

image_id = 121236918
ann_json = api.annotation.download_json(image_id)
print(ann_json)
# Output: {
#         "description": "",
#         "tags": [],
#         "size": {
#             "height": 800,
#             "width": 1067
#         },
#         "objects": []
#     }

download_json_batch(dataset_id, image_ids, progress_cb=None, force_metadata_for_links=True)[source]¶

Get list of AnnotationInfos for given dataset ID from API.

Parameters

dataset_id : int: Dataset ID in Supervisely.
image_ids : List[int]: List of integers.
progress_cb : tqdm: Function for tracking download progress.
force_metadata_for_links : bool, optional: Force metadata for links.

Returns

Information about Annotations. See info_sequence

Return type

List[Dict]

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()

dataset_id = 254737
image_ids = [121236918, 121236919]
p = tqdm(desc="Annotations downloaded: ", total=len(image_ids))

anns_jsons = api.annotation.download_json_batch(dataset_id, image_ids, progress_cb=p)
# Output:
# {"message": "progress", "event_type": "EventType.PROGRESS", "subtask": "Annotations downloaded: ", "current": 0, "total": 2, "timestamp": "2021-03-16T15:20:06.168Z", "level": "info"}
# {"message": "progress", "event_type": "EventType.PROGRESS", "subtask": "Annotations downloaded: ", "current": 2, "total": 2, "timestamp": "2021-03-16T15:20:06.510Z", "level": "info"}

exists(parent_id, name)[source]¶

get_free_name(parent_id, name)[source]¶

get_info_by_id(id)[source]¶

get_info_by_name(parent_id, name)[source]¶

get_label_by_id(label_id, project_meta, with_tags=True)[source]¶

Returns Supervisely Label object by it’s ID.

Parameters

label_id : int: ID of the label to get
project_meta : ProjectMeta: Supervisely ProjectMeta object
with_tags : bool, optional: If True, tags will be added to the Label object

Returns

Supervisely Label object

Return type

Label

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
load_dotenv(os.path.expanduser("~/supervisely.env"))
api = sly.Api.from_env()

label_id = 121236918

project_id = 254737
project_meta = sly.ProjectMeta.from_json(api.project.get_meta(project_id))

label = api.annotation.get_label_by_id(label_id, project_meta)

get_list(dataset_id, filters=None, progress_cb=None, force_metadata_for_links=True)[source]¶

Get list of information about all annotations for a given dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
filters : List[dict], optional: List of parameters to sort output Annotations.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Returns

Information about Annotations. See info_sequence

Return type

List[AnnotationInfo]

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()

dataset_id = 254737
ann_infos = api.annotation.get_list(dataset_id)
print(json.dumps(ann_infos[0], indent=4))
# Output: [
#     121236918,
#     "IMG_0748.jpeg",
#     {
#         "description": "",
#         "tags": [],
#         "size": {
#             "height": 800,
#             "width": 1067
#         },
#         "objects": []
#     },
#     "2019-12-19T12:06:59.435Z",
#     "2021-02-06T11:07:26.080Z"
# ]

ann_infos_filter = api.annotation.get_list(dataset_id, filters={ 'field': 'name', 'operator': '=', 'value': 'IMG_1836' })
print(json.dumps(ann_infos_filter, indent=4))
# Output: [
#     121236919,
#     "IMG_1836",
#     {
#         "description": "",
#         "tags": [],
#         "size": {
#             "height": 800,
#             "width": 1067
#         },
#         "objects": []
#     },
#     "2019-12-19T12:06:59.435Z",
#     "2021-02-06T11:07:26.080Z"
# ]

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_list_generator(dataset_id, filters=None, progress_cb=None, batch_size=50, force_metadata_for_links=True)[source]¶

Get list of information about all annotations for a given dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
filters : List[dict], optional: List of parameters to sort output Annotations.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Returns

Information about Annotations. See info_sequence

Return type

List[AnnotationInfo]

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()

dataset_id = 254737
ann_infos = api.annotation.get_list(dataset_id)
print(json.dumps(ann_infos[0], indent=4))
# Output: [
#     121236918,
#     "IMG_0748.jpeg",
#     {
#         "description": "",
#         "tags": [],
#         "size": {
#             "height": 800,
#             "width": 1067
#         },
#         "objects": []
#     },
#     "2019-12-19T12:06:59.435Z",
#     "2021-02-06T11:07:26.080Z"
# ]

ann_infos_filter = api.annotation.get_list(dataset_id, filters={ 'field': 'name', 'operator': '=', 'value': 'IMG_1836' })
print(json.dumps(ann_infos_filter, indent=4))
# Output: [
#     121236919,
#     "IMG_1836",
#     {
#         "description": "",
#         "tags": [],
#         "size": {
#             "height": 800,
#             "width": 1067
#         },
#         "objects": []
#     },
#     "2019-12-19T12:06:59.435Z",
#     "2021-02-06T11:07:26.080Z"
# ]

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))

static info_sequence()[source]¶

NamedTuple AnnotationInfo information about Annotation.

Example

AnnotationInfo(image_id=121236919,
               image_name='IMG_1836',
               annotation={'description': '', 'tags': [], 'size': {'height': 800, 'width': 1067}, 'objects': []},
               created_at='2019-12-19T12:06:59.435Z',
               updated_at='2021-02-06T11:07:26.080Z')

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

update_label(label_id, label)[source]¶

Updates label with given ID in Supervisely with new Label object. NOTE: This method only updates label’s geometry and tags, not class title, etc.

Parameters

label_id : int: ID of the label to update
label : Label: Supervisely Label object

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
load_dotenv(os.path.expanduser("~/supervisely.env"))
api = sly.Api.from_env()

new_label: sly.Label
label_id = 121236918

api.annotation.update_label(label_id, new_label)

Return type

None

update_label_priority(label_id, priority)[source]¶

Updates label’s priority with given ID in Supervisely. Priority increases with the number: a higher number indicates a higher priority. The higher priority means that the label will be displayed on top of the others. The lower priority means that the label will be displayed below the others.

Parameters

label_id : int: ID of the label to update
priority : int: New priority of the label

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 load_dotenv(os.path.expanduser(“~/supervisely.env”))

api = sly.Api.from_env()

label_ids = [123, 456, 789] priorities = [1, 2, 3]

for label_id, priority in zip(label_ids, priorities):: api.annotation.update_label_priority(label_id, priority)

# The label with ID 789 will be displayed on top of the others. # The label with ID 123 will be displayed below the others.

Return type

None

upload_ann(img_id, ann, skip_bounds_validation=False)[source]¶

Loads an Annotation to a given image ID in the API.

Parameters

img_id : int: Image ID in Supervisely.
ann : Annotation: Annotation object.

Returns

None

Return type

NoneType

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()

image_id = 121236918
upl_ann = api.annotation.upload_ann(image_id, ann)

upload_anns(img_ids, anns, progress_cb=None, skip_bounds_validation=False)[source]¶

Loads an Annotations to a given images IDs in the API. Images IDs must be from one dataset.

Parameters

img_ids : List[int]: Image ID in Supervisely.
anns : List[Annotation]: List of Annotation objects.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Returns

None

Return type

NoneType

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()

img_ids = [121236918, 121236919]
upl_anns = api.annotation.upload_anns(img_ids, [ann1, ann2])

# Optimizing the upload process by using the context to avoid redundant API calls.
# Usefull when uploading a large number of annotations in one dataset.
# 1. Download the project meta
dataset_id = 254737
project_id = api.dataset.get_info_by_id(dataset_id).project_id
project_meta = api.project.get_meta(project_id)

# 2. Use the context to avoid redundant API calls
with sly.ApiContext(api, dataset_id=dataset_id, project_id=project_id, project_meta=project_meta):
    api.annotation.upload_anns(img_ids, [ann1, ann2])

upload_json(img_id, ann_json, skip_bounds_validation=False)[source]¶

Loads an annotation from dict to a given image ID in the API.

Parameters

img_id : int: Image ID in Supervisely.
ann_json : dict: Annotation in JSON format.

Returns

None

Return type

NoneType

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()

image_id = 121236918
upl_json = api.annotation.upload_json(image_id, ann_json)

upload_jsons(img_ids, ann_jsons, progress_cb=None, skip_bounds_validation=False)[source]¶

Loads an annotations from dicts to a given images IDs in the API. Images IDs must be from one dataset.

Parameters

img_ids : List[int]: Image ID in Supervisely.
ann_jsons : List[dict]: Annotation in JSON format.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Returns

None

Return type

NoneType

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()

img_ids = [121236918, 121236919]
api.annotation.upload_jsons(img_ids, ann_jsons)

# Optimizing the upload process by using the context to avoid redundant API calls.
# Usefull when uploading a large number of annotations in one dataset.
# 1. Download the project meta
dataset_id = 254737
project_id = api.dataset.get_info_by_id(dataset_id).project_id
project_meta = api.project.get_meta(project_id)

# 2. Use the context to avoid redundant API calls
with sly.ApiContext(api, dataset_id=dataset_id, project_id=project_id, project_meta=project_meta):
    api.annotation.upload_jsons(img_ids, ann_jsons)

upload_path(img_id, ann_path, skip_bounds_validation=False)[source]¶

Loads an annotation from a given path to a given image ID in the API.

Parameters

img_id : int: Image ID in Supervisely.
ann_path : str: Path to annotation on host.

Returns

None

Return type

NoneType

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()

image_id = 121236918
ann_path = '/home/admin/work/supervisely/example/ann.json'
upl_path = api.annotation.upload_path(image_id, ann_path)

upload_paths(img_ids, ann_paths, progress_cb=None, skip_bounds_validation=False)[source]¶

Loads an annotations from a given paths to a given images IDs in the API. Images IDs must be from one dataset.

Parameters

img_ids : List[int]: Images IDs in Supervisely.
ann_paths : List[str]: Paths to annotations on local machine.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Returns

None

Return type

NoneType

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()

img_ids = [121236918, 121236919]
ann_pathes = ['/home/admin/work/supervisely/example/ann1.json', '/home/admin/work/supervisely/example/ann2.json']
upl_paths = api.annotation.upload_paths(img_ids, ann_pathes)

# Optimizing the upload process by using the context to avoid redundant API calls.
# Usefull when uploading a large number of annotations in one dataset.
# 1. Download the project meta
dataset_id = 254737
project_id = api.dataset.get_info_by_id(dataset_id).project_id
project_meta = api.project.get_meta(project_id)

# 2. Use the context to avoid redundant API calls
with sly.ApiContext(api, dataset_id=dataset_id, project_id=project_id, project_meta=project_meta):
    api.annotation.upload_paths(img_ids, ann_pathes)