VolumeApi¶

class VolumeApi[source]¶

Bases: supervisely.api.module_api.RemoveableBulkModuleApi

API for working with Volume. VolumeApi 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")

volume_id = 19581134
volume_info = api.volume.get_info_by_id(volume_id) # api usage example

Methods

`download_path`	Download volume with given ID to local directory.
`download_slice_np`	Download slice as NumPy from Supervisely by ID.
`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_free_names`	Returns list of free names for given dataset.
`get_info_by_id`	Get Volume information by ID in VolumeInfo<VolumeInfo> format.
`get_info_by_name`	Get information about an entity by its name from the Supervisely server.
`get_list`	Get list of information about all volumes for a given dataset ID.
`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
`info_sequence`	Get list of all `VolumeInfo` field names.
`info_tuple_name`	Get string name of `VolumeInfo` NamedTuple.
`raise_name_intersections_if_exist`	Raises error if volumes with given names already exist in dataset.
`remove`	Remove an entity with the specified ID from the Supervisely server.
`remove_batch`	Remove entities in batches from the Supervisely server.
`upload_dicom_serie_paths`	Upload given DICOM series from given paths to Dataset.
`upload_dir`	Upload all volumes from given directory to Dataset recursively.
`upload_dirs`	Upload all volumes from given directories to Dataset recursively.
`upload_hash`	Upload Volume from given hash to Dataset.
`upload_hashes`	Upload Volumes from given hashes to Dataset.
`upload_np`	Upload given Volume in numpy format with given name to Dataset.
`upload_nrrd_serie_path`	Upload NRRD format volume from given path to Dataset.
`upload_nrrd_series_paths`	Upload NRRD format volumes from given paths to Dataset.

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.VolumeInfo

download_path(id, path, progress_cb=None)[source]¶

Download volume with given ID to local directory.

Parameters

id : int: Volume ID in Supervisely.
path : str: Local path to save volume.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Returns

Information about Volume. See info_sequence

Return type

VolumeInfo

Usage example

import supervisely as sly
from tqdm import tqdm

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

src_dataset_id = 61229
volume_infos = api.volume.get_list(src_dataset_id)
volume_id = volume_infos[0].id
volume_info = api.volume.get_info_by_id(id=volume_id)

download_dir_name = "src/download/"
path = os.path.join(download_dir_name, volume_info.name)
if os.path.exists(path):
    os.remove(path)

p = tqdm(desc="Volumes upload: ", total=volume_info.sizeb, is_size=True)
api.volume.download_path(volume_info.id, path, progress_cb=p)

if os.path.exists(path):
    print(f"Volume (ID {volume_info.id}) successfully downloaded.")

# Output:
# Volume (ID 18630603) successfully downloaded.

download_slice_np(volume_id, slice_index, plane, window_center=None, window_width=None)[source]¶

Download slice as NumPy from Supervisely by ID.

Parameters

volume_id : int: Volume ID in Supervisely.
slice_index : int: Slice index.
plane : str: Plane of the slice in volume.
window_center : float: Window center.
window_width : int: Window width.

Returns

Information about Volume. See info_sequence

Return type

VolumeInfo

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()


slice_index = 60

image_np = api.volume.download_slice_np(
    volume_id=volume_id,
    slice_index=slice_index,
    plane=sly.Plane.SAGITTAL,
)

print(f"Image downloaded as NumPy array. Image shape: {image_np.shape}")

# Output:
# Image downloaded as NumPy array. Image shape: (256, 256, 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 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_free_names(dataset_id, names)[source]¶

Returns list of free names for given dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
names : List[str]: List of names to check.

Returns

List of free names.

Return type

List[str]

get_info_by_id(id)[source]¶

Get Volume information by ID in VolumeInfo<VolumeInfo> format.

Parameters

id : int: Volume ID in Supervisely.

Returns

Information about Volume. See info_sequence

Return type

VolumeInfo

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()

volume_id = 19581134
volume_info = api.volume.get_info_by_id(volume_id)
print(volume_info)
# Output:
# VolumeInfo(
#     id=19581134,
#     name='CTChest.nrrd',
#     link=None,
#     hash='+0K2oFHpqA5dwRKQlhkvhXEh52cs=',
#     mime=None,
#     ext=None,
#     sizeb=46073411,
#     created_at='2023-03-29T12:30:37.078Z',
#     updated_at='2023-03-29T12:30:37.078Z',
#     meta={
#         'ACS': 'RAS',
#         'intensity': {'max': 3071, 'min': -3024},
#         'windowWidth': 6095,
#         'rescaleSlope': 1,
#         'windowCenter': 23.5,
#         'channelsCount': 1,
#         'dimensionsIJK': {'x': 512, 'y': 512, 'z': 139},
#         'IJK2WorldMatrix': [0.7617189884185793, 0, 0, -194.238403081894, 0, 0.7617189884185793, 0, -217.5384061336518, 0, 0, 2.5, -347.7500000000001, 0, 0, 0, 1],
#         'rescaleIntercept': 0
#     },
#     path_original='/h5af-public/images/original/M/e/7R/vs0p.nrrd',
#     full_storage_url='https://dev.supervise.ly/.../original/M/e/7R/zX0p.nrrd',
#     tags=[],
#     team_id=435,
#     workspace_id=685,
#     project_id=18949,
#     dataset_id=61803,
#     file_meta={
#             'mime': 'image/nrrd',
#             'size': 46073411,
#             'type': 'int32',
#             'extra': {'stride': [1, 512, 262144],
#             'comments': []
#         }
#         'sizes': [512, 512, 139]
#         'space': 'right-anterior-superior'
#         'endian': 'little'
#         'encoding': 'gzip'
#         'dimension': 3
#         'space origin': [-194.238403081894, -217.5384061336518, -347.7500000000001]
#         'space dimension': 3
#         'space directions': [[0.7617189884185793, 0, 0], [0, 0.7617189884185793, 0], [0, 0, 2.5]]
#     }
#     figures_count=None,
#     objects_count=None,
#     processing_path='1/1560071'
# )

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 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(dataset_id, filters=None, sort='id', sort_order='asc')[source]¶

Get list of information about all volumes for a given dataset ID.

Parameters

dataset_id : int: Dataset ID in Supervisely.
filters : List[Dict[str, str]], optional: List of parameters to sort output Volumes. See: https://dev.supervise.ly/api-docs/#tag/Volumes/paths/~1volumes.list/get
sort : str: Attribute to sort the list by. The default is “id”. Valid values are “id”, “name”, “description”, “createdAt”, “updatedAt”.
sort_order : str: Order in which to sort the list. The default is “asc”. Valid values are “asc” (ascending) and “desc” (descending).

Returns

List of information about volumes in given dataset.

Return type

List[VolumeInfo]

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()

dataset_id = 61803

volume_infos = api.volume.get_list(dataset_id)
print(volume_infos)
# Output: [VolumeInfo(id=19581134, ...), VolumeInfo(id=19581135, ...), VolumeInfo(id=19581136, ...)]

sorted_volume_infos = api.volume.get_list(dataset_id, sort="id", sort_order="desc")
# Output: [VolumeInfo(id=19581136, ...), VolumeInfo(id=19581135, ...), VolumeInfo(id=19581134, ...)]

filtered_volume_infos = api.volume.get_list(dataset_id, filters=[{'field': 'id', 'operator': '=', 'value': '19581135'}])
print(filtered_volume_infos)
# Output: [VolumeInfo(id=19581135, ...)]

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

static info_sequence()[source]¶

Get list of all VolumeInfo field names.

Returns: List of VolumeInfo field names.`
Return type: list

static info_tuple_name()[source]¶

Get string name of VolumeInfo NamedTuple.

Returns: NamedTuple name.
Return type: str

raise_name_intersections_if_exist(dataset_id, names, message=None)[source]¶: Raises error if volumes with given names already exist in dataset. Default error message: “Volumes with the following names already exist in dataset [ID={dataset_id}]: {name_intersections}. Please, rename volumes and try again or set change_name_if_conflict=True to rename automatically on upload.” :type dataset_id: int :param dataset_id: Dataset ID in Supervisely. :type dataset_id: int :type names: List[str] :param names: List of names to check. :type names: List[str] :type message: Optional[str] :param message: Error message. :type message: str, optional :return: None :rtype: None

remove(id)¶

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

Parameters

id : int: Entity ID in Supervisely.

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()


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 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()


image_ids = [19369645, 19369646, 19369647]
api.image.remove_batch(image_ids)

upload_dicom_serie_paths(dataset_id, name, paths, log_progress=True, anonymize=True)[source]¶

Upload given DICOM series from given paths to Dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
name : str: Volume name with extension.
paths : List[str]: Local volumes paths.
log_progress : bool, optional: Determine if additional technical logs are displaying.
anonymize : bool, optional: Determine whether to hide PatientID and PatientName fields.

Returns

Information about Volume. See info_sequence

Return type

VolumeInfo

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()


dicom_dir_name = "src/upload/MRHead_dicom/"
series_infos = sly.volume.inspect_dicom_series(root_dir=dicom_dir_name)

for serie_id, files in series_infos.items():
    item_path = files[0]
    name = f"{sly.fs.get_file_name(path=item_path)}.nrrd"
    dicom_info = api.volume.upload_dicom_serie_paths(
        dataset_id=dataset.id,
        name=name,
        paths=files,
        anonymize=True,
    )
    print(f"DICOM volume has been uploaded to Supervisely with ID: {dicom_info.id}")

# Output:
# DICOM volume has been uploaded to Supervisely with ID: 18630608

upload_dir(dataset_id, dir_path, progress_cb=None, log_progress=False, change_name_if_conflict=True)[source]¶

Upload all volumes from given directory to Dataset recursively.

Parameters

dataset_id : int: Dataset ID in Supervisely.
dir_path : str: Local directory path.
progress_cb : tqdm or callable, optional: Function for tracking download progress.
log_progress : bool, optional: Determine if additional technical logs are displaying.
change_name_if_conflict : bool, optional: Determine if names are changing if conflict.

Returns

List with information about Volumes. See info_sequence

Return type

List[VolumeInfo]

Usage example

import supervisely as sly
from tqdm import tqdm

os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'

api = sly.Api.from_env()

dataset_id = 61958
dir_path = "src/upload/volumes/"
volume_infos = api.volume.upload_dir(dataset_id, dir_path)
print(f"All volumes has been uploaded with IDs: {[x.id for x in volume_infos]}")

# Output:
# All volumes has been uploaded with IDs: [18630605, 18630606, 18630607]

upload_dirs(dataset_id, dir_paths, progress_cb=None, log_progress=False, change_name_if_conflict=True)[source]¶

Upload all volumes from given directories to Dataset recursively.

Parameters

dataset_id : int: Dataset ID in Supervisely.
dir_paths : List[str]: List of local directory paths.
progress_cb : tqdm or callable, optional: Function for tracking download progress.
log_progress : bool, optional: Determine if additional technical logs are displaying.
change_name_if_conflict : bool, optional: Determine if names are changing if conflict.

Returns

List with information about Volumes. See info_sequence

Return type

List[VolumeInfo]

Usage example

import supervisely as sly
from tqdm import tqdm

os.environ['SERVER_ADDRESS'] = 'https://app.supervise.ly'
os.environ['API_TOKEN'] = 'Your Supervisely API Token'

api = sly.Api.from_env()

dataset_id = 61958
dir_paths = ["src/upload/volumes1/", "src/upload/volumes2/"]
volume_infos = api.volume.upload_dirs(dataset_id, dir_paths)
print(f"All volumes has been uploaded with IDs: {[x.id for x in volume_infos]}")

# Output:
# All volumes has been uploaded with IDs: [18630605, 18630606, 18630607]

upload_hash(dataset_id, name, hash, meta=None)[source]¶

Upload Volume from given hash to Dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
name : str: Volume name with extension.
hash : str: Volume hash.
meta : dict: A dictionary containing data associated with the volume.

Returns

Information about Volume. See info_sequence

Return type

VolumeInfo

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_dataset_id = 61958
src_volume_id = 19581134
volume_info = api.volume.get_info_by_id(src_volume_id)
hash = volume_info.hash
# It is necessary to upload volume with the same extention as in src dataset
name = volume_info.name
meta = volume_info.meta
new_volume_info = api.volume.upload_hash(dst_dataset_id, name, hash, meta)
print(new_volume_info)
# Output:
# VolumeInfo(
#     id=19613940,
#     name='CTACardio.nrrd',
#     link=None,
#     hash='+0K2oFHpqA5dwRKQlh5bDUA0jkPsEE52cs=',
#     mime=None,
#     ext=None,
#     sizeb=67614735,
#     created_at='2023-03-29T12:30:37.078Z',
#     updated_at='2023-03-29T12:30:37.078Z',
#     meta={
#         'ACS': 'RAS',
#         'intensity': {'max': 3532, 'min': -1024},
#         'windowWidth': 4556,
#         'rescaleSlope': 1,
#         'windowCenter': 1254,
#         'channelsCount': 1,
#         'dimensionsIJK': {'x': 512, 'y': 512, 'z': 321}
#         'IJK2WorldMatrix': [0.9335939999999999, 0, 0, -238.53326699999997, 0, 0.9335939999999999, 0, -238.53326699999994, 0, 0, 1.25, -200.0000000000001, 0, 0, 0, 1],
#         'rescaleIntercept': 0
#     },
#     path_original='/h5af-public/images/original/M/e/7R/zfsfX0p.nrrd',
#     full_storage_url='https://dev.supervise.ly/h5un-public/images/original/M/e/7R/zXdd0p.nrrd',
#     tags=[],
#     team_id=435,
#     workspace_id=685,
#     project_id=18949,
#     dataset_id=61958,
#     file_meta={
#             'mime': 'image/nrrd',
#             'size': 46073411,
#             'type': 'int32',
#             'extra': {'stride': [1, 512, 262144],
#             'comments': []
#         }
#         'sizes': [512, 512, 139]
#         'space': 'right-anterior-superior'
#         'endian': 'little'
#         'encoding': 'gzip'
#         'dimension': 3
#         'space origin': [-194.238403081894, -217.5384061336518, -347.7500000000001]
#         'space dimension': 3
#         'space directions': [[0.7617189884185793, 0, 0], [0, 0.7617189884185793, 0], [0, 0, 2.5]]
#     }
#     figures_count=None,
#     objects_count=None,
#     processing_path='1/1560071'
# )

upload_hashes(dataset_id, names, hashes, progress_cb=None, metas=None)[source]¶

Upload Volumes from given hashes to Dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
names : List[str]: Volumes names with extension.
hashes : List[str]: Volumes hashes.
progress_cb : tqdm or callable, optional: Function for tracking download progress.
metas : List[dict], optional: Volumes metadata.

Returns

List with information about Volumes. See info_sequence

Return type

List[VolumeInfo]

Usage example

import supervisely as sly
from tqdm import tqdm

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

src_dataset_id = 61958
dst_dataset_id = 55853

hashes = []
names = []
metas = []
volume_infos = api.volume.get_list(src_dataset_id)

# Create lists of hashes, volumes names and meta information for each volume
for volume_info in volume_infos:
    hashes.append(volume_info.hash)
    # It is necessary to upload volumes with the same names(extentions) as in src dataset
    names.append(volume_info.name)
    metas.append(volume_info.meta)

p = tqdm(desc="api.volume.upload_hashes", total=len(hashes))
new_volumes_info = api.volume.upload_hashes(
    dataset_id=dst_dataset_id,
    names=names,
    hashes=hashes,
    progress_cb=p,
    metas=metas,
)

# Output:
# {"message": "progress", "event_type": "EventType.PROGRESS", "subtask": "Volumes upload: ", "current": 0, "total": 2, "timestamp": "2023-04-04T07:47:11.506Z", "level": "info"}
# {"message": "progress", "event_type": "EventType.PROGRESS", "subtask": "Volumes upload: ", "current": 2, "total": 2, "timestamp": "2023-04-04T07:47:11.563Z", "level": "info"}

upload_np(dataset_id, name, np_data, meta, progress_cb=None, batch_size=30)[source]¶

Upload given Volume in numpy format with given name to Dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
name : str: Volume name with extension.
np_data : np.ndarray: image in RGB format(numpy matrix)
meta : dict, optional: Volume metadata.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Returns

Information about Volume. See info_sequence

Return type

VolumeInfo

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()

np_volume, meta = sly.volume.read_nrrd_serie_volume_np(local_path)
nrrd_info_np = api.volume.upload_np(
    dataset.id,
    "MRHead_np.nrrd",
    np_volume,
    meta,
)
print(f"Volume uploaded as NumPy array to Supervisely with ID:{nrrd_info_np.id}")

# Output:
# Volume uploaded as NumPy array to Supervisely with ID:18562982

upload_nrrd_serie_path(dataset_id, name, path, log_progress=True, progress_cb=None)[source]¶

Upload NRRD format volume from given path to Dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
name : str: Volume name with extension.
path : str: Local volume path.
log_progress : bool, optional: Determine if additional technical logs are displaying.

Returns

Information about Volume. See info_sequence

Return type

VolumeInfo

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()


local_path = "src/upload/nrrd/MRHead.nrrd"

nrrd_info = api.volume.upload_nrrd_serie_path(
    dataset.id,
    "MRHead.nrrd",
    local_path,
)
print(f'"{nrrd_info.name}" volume uploaded to Supervisely with ID:{nrrd_info.id}')

# Output:
# "NRRD_1.nrrd" volume uploaded to Supervisely with ID:18562981

upload_nrrd_series_paths(dataset_id, names, paths, progress_cb=None, log_progress=True)[source]¶

Upload NRRD format volumes from given paths to Dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
names : List[str]: Volumes names with extensions.
paths : List[str]: Local volumes paths.
log_progress : bool, optional: Determine if additional technical logs are displaying.
progress_cb : tqdm or callable, optional: Function for tracking download progress.

Returns

Information about Volume. See info_sequence

Return type

VolumeInfo

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()


local_dir_name = "src/upload/nrrd/"
all_nrrd_names = os.listdir(local_dir_name)
names = [f"1_{name}" for name in all_nrrd_names]
paths = [os.path.join(local_dir_name, name) for name in all_nrrd_names]

volume_infos = api.volume.upload_nrrd_series_paths(dataset.id, names, paths)
print(f"All volumes has been uploaded with IDs: {[x.id for x in volume_infos]}")

# Output:
# All volumes has been uploaded with IDs: [18630605, 18630606, 18630607]