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 volume with given ID to local directory.
Download slice as NumPy from Supervisely by ID.
Checks if an entity with the given parent_id and name exists
Generates a free name for an entity with the given parent_id and name.
Get Volume information by ID in VolumeInfo<VolumeInfo> format.
Get information about an entity by its name from the Supervisely server.
Get list of information about all volumes for a given dataset ID.
Get list of all or limited quantity entities from the Supervisely server.
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 of all
VolumeInfo
field names.Get string name of
VolumeInfo
NamedTuple.Remove an entity with the specified ID from the Supervisely server.
Remove entities in batches from the Supervisely server.
Upload given DICOM series from given paths to Dataset.
Upload Volume from given hash to Dataset.
Upload Volumes from given hashes to Dataset.
Upload given Volume in numpy format with given name to Dataset.
Upload NRRD format volume from given path to Dataset.
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
- Returns
Information about Volume. See
info_sequence
- Return type
- 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
- Returns
Information about Volume. See
info_sequence
- Return type
- 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
- Returns
Returns True if entity exists, and False if not
- Return type
- 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
- Returns
Returns free name.
- Return type
- 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)[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
- 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)¶
Get information about an entity by its name from the Supervisely server.
- Parameters
- 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
- static info_tuple_name()[source]¶
Get string name of
VolumeInfo
NamedTuple.- Returns
NamedTuple name.
- Return type
- 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.
- 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
- Returns
Information about Volume. See
info_sequence
- Return type
- 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_hash(dataset_id, name, hash, meta=
None
)[source]¶ Upload Volume from given hash to Dataset.
- Parameters
- Returns
Information about Volume. See
info_sequence
- Return type
- 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
- 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
- Returns
Information about Volume. See
info_sequence
- Return type
- 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
)[source]¶ Upload NRRD format volume from given path to Dataset.
- Parameters
- Returns
Information about Volume. See
info_sequence
- Return type
- 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
- Returns
Information about Volume. See
info_sequence
- Return type
- 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]