PointcloudApi¶

class PointcloudApi[source]¶

Bases: supervisely.api.module_api.RemoveableBulkModuleApi

API for working with Pointcloud. PointcloudApi 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")

pcd_id = 19618654
pcd_info = api.pointcloud.get_info_by_id(pcd_id) # api usage example

Methods

`add_related_images`	Attach images to point cloud.
`check_existing_hashes`	Check if point clouds with given hashes are exist.
`download_path`	Download point cloud with given id on the given path.
`download_related_image`	Download a related context image from Supervisely to local directory by image 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 point cloud information by ID in PointcloudInfo<PointcloudInfo> 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 point cloud 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
`get_list_related_images`	Get information about related context images.
`info_sequence`	Get list of all `PointcloudInfo` field names.
`info_tuple_name`	Get string name of `PointcloudInfo` NamedTuple.
`raise_name_intersections_if_exist`	Raises error if pointclouds 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_dir`	Uploads all pointclouds with supported extensions from given directory to Supervisely.
`upload_dirs`	Uploads all pointclouds with supported extensions from given directories to Supervisely.
`upload_hash`	Upload Pointcloud from given hash to Dataset.
`upload_hashes`	Upload point clouds from given hashes to Dataset.
`upload_path`	Upload point cloud with given path to Dataset.
`upload_paths`	Upload point clouds with given paths to Dataset.
`upload_related_image`	Upload an image to the Supervisely.
`upload_related_images`	Upload a batch of related images to the Supervisely.

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.PointCloudInfo

add_related_images(images_json, camera_names=None)[source]¶

Attach images to point cloud.

Parameters

images_json : List[Dict]: List of dictionaries with dataset id, image name, hash and meta.
camera_names : List[Dict]: List of camera informations.

Returns

Response object

Return type

Dict

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()

img_paths = ["src/input/img/000001.png", "src/input/img/000002.png"]
cam_paths = ["src/input/cam_info/000001.json", "src/input/cam_info/000002.json"]

img_hashes = api.pointcloud.upload_related_images(img_paths)
img_infos = []
for i, cam_info_file in enumerate(cam_paths):
    # reading cam_info
    with open(cam_info_file, "r") as f:
        cam_info = json.load(f)
    img_info = {
        "entityId": pcd_infos[i].id,
        "name": f"img_{i}.png",
        "hash": img_hashes[i],
        "meta": cam_info,
    }
    img_infos.append(img_info)
api.pointcloud.add_related_images(img_infos)

check_existing_hashes(hashes)[source]¶

Check if point clouds with given hashes are exist.

Parameters

paths : List[str]: Point clouds hashes to check.

Returns

List of point clouds hashes that are exist.

Return type

List[str]

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()

pointcloud_id = 19618685
pcd_info = api.pointcloud.get_info_by_id(pointcloud_id)
hash = api.pointcloud.check_existing_hashes([pcd_info.hash])
print(hash)

# Output:
# ['5w69Vv1i6JrqhU0Lw1UJAJFGPhgkIhs7O3f4QSwRfmE=']

download_path(id, path)[source]¶

Download point cloud with given id on the given path.

Parameters

id : int: Point cloud ID in Supervisely.
path : str: Local save path for point cloud.

Returns

None

Return type

NoneType

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()

storage_dir = sly.app.get_data_dir()
pcd_id = 19373403
pcd_info = api.pointcloud.get_info_by_id(pcd_id)
save_path = os.path.join(storage_dir, pcd_info.name)

api.pointcloud.download_path(pcd_id, save_path)
print(os.listdir(storage_dir))

# Output: ['000063.pcd']

download_related_image(id, path)[source]¶

Download a related context image from Supervisely to local directory by image id.

Parameters

id : int: Related context imgage ID in Supervisely.
path : str: Local save path for point cloud.

Returns

List of dictionaries with informations about related images

Return type

List

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()

save_path = "src/output/img_0.png"
img_info = api.pointcloud.get_list_related_images(pcd_info.id)[0]
api.pointcloud.download_related_image(img_info["id"], save_path)
print(f"Context image has been successfully downloaded to '{save_path}'")

# Output: # Context image has been successfully downloaded to ‘src/output/img_0.png’

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 point cloud information by ID in PointcloudInfo<PointcloudInfo> format.

Parameters

id : int: Point cloud ID in Supervisely.
raise_error : bool: Return an error if the point cloud info was not received.

Returns

Information about point cloud. See info_sequence

Return type

PointcloudInfo

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()

pcd_id = 19373403
pcd_info = api.pointcloud.get_info_by_id(pcd_id)
print(pcd_info)

# Output:
# PointcloudInfo(
#     id=19373403,
#     frame=None,
#     description='',
#     name='000063.pcd',
#     team_id=435,
#     workspace_id=687,
#     project_id=17231,
#     dataset_id=55875,
#     link=None,
#     hash='7EcJCyhq15V4NnZ8oiPrKQckmXXypO4saqFN7kgH08Y=',
#     path_original='/h5unms4-public/point_clouds/Z/h/bc/roHZP5nP2.pcd',
#     cloud_mime='image/pcd',
#     figures_count=4,
#     objects_count=4,
#     tags=[],
#     meta={},
#     created_at='2023-02-07T19:36:44.897Z',
#     updated_at='2023-02-07T19:36:44.897Z'
# )

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)[source]¶

Get list of information about all point cloud 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 Pointclouds. See: https://dev.supervise.ly/api-docs/#tag/Point-Clouds/paths/~1point-clouds.list/get

Returns

List of the point clouds objects from the dataset with given id.

Return type

List[PointcloudInfo]

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 = 62664
pcd_infos = api.pointcloud_episode.get_list(dataset_id)
print(pcd_infos)
# Output: [PointcloudInfo(...), PointcloudInfo(...)]

id_list = [19618654, 19618657, 19618660]
filtered_pointcloud_infos = api.pointcloud.get_list(dataset_id, filters=[{'field': 'id', 'operator': 'in', 'value': id_list}])
print(filtered_pointcloud_infos)
# Output:
# [PointcloudInfo(id=19618654, ...), PointcloudInfo(id=19618657, ...), PointcloudInfo(id=19618660, ...)]

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_related_images(id)[source]¶

Get information about related context images.

Parameters

id : int: Point cloud ID in Supervisely.

Returns

List of dictionaries with informations about related images

Return type

List

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()

pcd_id = 19373403
img_infos = api.pointcloud.get_list_related_images(pcd_id)
img_info = img_infos[0]
print(img_info)

# Output:
# {
#     'pathOriginal': '/h5un6qgms4-public/images/original/S/j/hJ/PwMg.png',
#     'id': 473302,
#     'entityId': 19373403,
#     'createdAt': '2023-01-09T08:50:33.225Z',
#     'updatedAt': '2023-01-09T08:50:33.225Z',
#     'meta': {
#         'deviceId': 'cam_2'},
#         'fileMeta': {'mime': 'image/png',
#         'size': 893783,
#         'width': 1224,
#         'height': 370
#     },
#     'hash': 'vxA+emfDNUkFP9P6oitMB5Q0rMlnskmV2jvcf47OjGU=',
#     'link': None,
#     'preview': '/previews/q/ext:jpeg/resize:fill:50:0:0/q:50/plain/h5ad-public/images/original/S/j/hJ/PwMg.png',
#     'fullStorageUrl': 'https://dev.supervise.ly/hs4-public/images/original/S/j/hJ/PwMg.png',
#     'name': 'img00'
# }

static info_sequence()[source]¶

Get list of all PointcloudInfo field names.

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

static info_tuple_name()[source]¶

Get string name of PointcloudInfo NamedTuple.

Returns

NamedTuple name.

Return type

str

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()

tuple_name = api.pointcloud.info_tuple_name()
print(tuple_name) # PointCloudInfo

raise_name_intersections_if_exist(dataset_id, names, message=None)[source]¶

Raises error if pointclouds with given names already exist in dataset. Default error message: “Pointclouds with the following names already exist in dataset [ID={dataset_id}]: {name_intersections}. Please, rename pointclouds and try again or set change_name_if_conflict=True to rename automatically on upload.”

Parameters

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

Returns

None

Return type

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_dir(dataset_id, dir_path, recursive=True, change_name_if_conflict=True, progress_cb=None)[source]¶

Uploads all pointclouds with supported extensions from given directory to Supervisely. Optionally, uploads pointclouds from subdirectories of given directory.

Parameters

dataset_id : int: Dataset ID in Supervisely.
dir_path : str: Path to directory with pointclouds.
recursive : bool, optional: If True, will upload pointclouds from subdirectories of given directory recursively. Otherwise, will upload pointclouds only from given directory.
change_name_if_conflict : bool, optional: If True adds suffix to the end of Pointcloud name when Dataset already contains an Pointcloud with identical name, If False and pointclouds with the identical names already exist in Dataset raises error.
progress_cb : Optional[Union[tqdm, Callable]]: Function for tracking upload progress.

Returns

List of uploaded pointclouds infos

Return type

List[PointcloudInfo]

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

Uploads all pointclouds with supported extensions from given directories to Supervisely. Optionally, uploads pointclouds from subdirectories of given directories.

Parameters

dataset_id : int: Dataset ID in Supervisely.
dir_paths : List[str]: List of paths to directories with pointclouds.
recursive : bool, optional: If True, will upload pointclouds from subdirectories of given directories recursively. Otherwise, will upload pointclouds only from given directories.
change_name_if_conflict : bool, optional: If True adds suffix to the end of Pointclouds name when Dataset already contains an Pointclouds with identical name, If False and pointclouds with the identical names already exist in Dataset raises error.
progress_cb : Optional[Union[tqdm, Callable]]: Function for tracking upload progress.

Returns

List of uploaded pointclouds infos

Return type

List[Pointclouds]

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

Upload Pointcloud from given hash to Dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
name : str: Point cloud name with extension.
hash : str: Point cloud hash.
meta : dict, optional: Point cloud metadata.

Returns

Information about point cloud. See info_sequence

Return type

PointcloudInfo

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 = 62693

src_pointcloud_id = 19618685
pcd_info = api.pointcloud.get_info_by_id(src_pointcloud_id)
hash, name, meta = pcd_info.hash, pcd_info.name, pcd_info.meta

new_pcd_info = api.pointcloud.upload_hash(dst_dataset_id.id, name, hash, meta)
print(new_pcd_info)

# Output:
# PointcloudInfo(
#     id=19619507,
#     frame=None,
#     description='',
#     name='0000000031.pcd',
#     team_id=None,
#     workspace_id=None,
#     project_id=None,
#     dataset_id=62694,
#     link=None,
#     hash='5w69Vv1i6JrqhU0Lw1UJAJFGPVWUzDG7O3f4QSwRfmE=',
#     path_original='/j8a9qgms4-public/point_clouds/I/3/6U/L7YBY.pcd',
#     cloud_mime='image/pcd',
#     figures_count=None,
#     objects_count=None,
#     tags=None,
#     meta={'frame': 31},
#     created_at='2023-04-05T10:59:44.656Z',
#     updated_at='2023-04-05T10:59:44.656Z'
# )

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

Upload point clouds from given hashes to Dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
names : List[str]: Point cloud name with extension.
hashes : List[str]: Point cloud hash.
metas : Optional[List[Dict]], optional: Point cloud metadata.
progress_cb : Progress, optional: Function for tracking upload progress.

Returns

List of informations about Pointclouds. See info_sequence

Return type

List[PointcloudInfo]

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()

src_dataset_id = 62664
dst_dataset_id = 62690

src_pcd_infos = api.pointcloud.get_list(src_dataset_id)

names = [pcd.name for pcd in src_pcd_infos[:4]]
hashes = [pcd.hash for pcd in src_pcd_infos[:4]]
metas = [pcd.meta for pcd in src_pcd_infos[:4]]

dst_pcd_infos = api.pointcloud.get_list(dst_dataset_id)
print(f"{len(dst_pcd_infos)} pointcloud before upload.")
# Output:
# 0 pointcloud before upload.

new_pcd_infos = api.pointcloud.upload_hashes(dst_dataset_id, names, hashes, metas)
print(f"{len(new_pcd_infos)} pointcloud after upload.")
# Output:
# 4 pointcloud after upload.

upload_path(dataset_id, name, path, meta=None)[source]¶

Upload point cloud with given path to Dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
name : str: Point cloud name with extension.
path : str: Path to point cloud.
meta : Optional[Dict]: Dictionary with metadata for point cloud.

Returns

Information about point cloud

Return type

PointcloudInfo

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()

pcd_file = "src/input/pcd/000000.pcd"
pcd_info = api.pointcloud.upload_path(dataset.id, name="pcd_0.pcd", path=pcd_file)
print(f'Point cloud "{pcd_info.name}" uploaded to Supervisely with ID:{pcd_info.id}')

# Output:
# Point cloud "pcd_0.pcd" uploaded to Supervisely with ID:19618685

upload_paths(dataset_id, names, paths, progress_cb=None, metas=None)[source]¶

Upload point clouds with given paths to Dataset.

Parameters

dataset_id : int: Dataset ID in Supervisely.
names : List[str]: Point clouds names with extension.
paths : List[str]: Paths to point clouds.
progress_cb : Progress, optional: Function for tracking upload progress.
metas : Optional[List[Dict]]: List of dictionary with metadata for point cloud.

Returns

List of informations about point clouds

Return type

List[PointcloudInfo]

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()

paths = ["src/input/pcd/000001.pcd", "src/input/pcd/000002.pcd"]
pcd_infos = api.pointcloud.upload_paths(dataset.id, names=["pcd_1.pcd", "pcd_2.pcd"], paths=paths)
print(f'Point clouds uploaded to Supervisely with IDs: {[pcd_info.id for pcd_info in pcd_infos]}')

# Output:
# Point clouds uploaded to Supervisely with IDs: [19618685, 19618686]

upload_related_image(path)[source]¶

Upload an image to the Supervisely. It generates us a hash for image.

Parameters

path : str: Image path.

Returns

Hash for image. See info_sequence

Return type

str

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()

img_file = src/input/img/000000.png"
img_hash = api.pointcloud.upload_related_image(img_file)
print(img_hash)

# Output:
# +R6dFy8nMEq6k82vHLxuakpqVBmyTTPj5hXdPfjAv/c=

upload_related_images(paths, progress_cb=None)[source]¶

Upload a batch of related images to the Supervisely. It generates us a hashes for images.

Parameters

paths : List[str]: Images pathes.

Returns

List of hashes for images. See info_sequence

Return type

List[str]

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()

img_paths = ["src/input/img/000001.png", "src/input/img/000002.png"]
img_hashes = api.pointcloud.upload_related_images(img_paths)

# Output:
# [+R6dFy8nMEq6k82vHLxuakpqVBmyTTPjdfGdPfjAv/c=, +hfjbufnbkLhJb32vHLxuakpqVBmyTTPj5hXdPfhhj1c]