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Studio Client

EdgeFirst Client Library This library provides a client for the EdgeFirst API, allowing users to interact with the EdgeFirst Studio Server and perform various operations such as logging in, managing projects, and working with datasets and snapshots.

This is the Python API binding for the EdgeFirst Client Library. A Rust library and a command-line interface are also available. The CLI tool is bundgled with the Python wheel and can be called using the edgefirst-client command.

The Python API is available as the edgefirst_client module. The main class is Client, which provides methods for interacting with the EdgeFirst Studio Server. To use the Client object you need to create an instance, with an optional authentication token or username and password.

__all__ module 

__all__ = [
    "Client",
    "AnnotationType",
    "AnnotationGroup",
    "Box2d",
    "Box3d",
    "Segmentation",
]

Built-in mutable sequence.

If no argument is given, the constructor creates a new empty list. The argument must be an iterable if specified.

__cached__ module 

__cached__ = "/Users/sebastien/Documents/EdgeFirst Studio/venv/lib/python3.13/site-packages/edgefirst_client/__pycache__/__init__.cpython-313.pyc"

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__doc__ module 

__doc__ = "EdgeFirst Client Library\nThis library provides a client for the EdgeFirst API, allowing users to\ninteract with the EdgeFirst Studio Server and perform various operations\nsuch as logging in, managing projects, and working with datasets and\nsnapshots.\n\nThis is the Python API binding for the EdgeFirst Client Library.  A Rust\nlibrary and a command-line interface are also available.  The CLI tool is\nbundgled with the Python wheel and can be called using the\n`edgefirst-client` command.\n\nThe Python API is available as the `edgefirst_client` module.  The main\nclass is `Client`, which provides methods for interacting with the EdgeFirst\nStudio Server.  To use the `Client` object you need to create an instance,\nwith an optional authentication token or username and password."

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__file__ module 

__file__ = "/Users/sebastien/Documents/EdgeFirst Studio/venv/lib/python3.13/site-packages/edgefirst_client/__init__.py"

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__name__ module 

__name__ = 'edgefirst_client'

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__package__ module 

__package__ = 'edgefirst_client'

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__path__ module 

__path__ = [
    "/Users/sebastien/Documents/EdgeFirst Studio/venv/lib/python3.13/site-packages/edgefirst_client"
]

Built-in mutable sequence.

If no argument is given, the constructor creates a new empty list. The argument must be an iterable if specified.

AnnotationGroup

__doc__ class 

__doc__ = None

The type of the None singleton.

__module__ class 

__module__ = 'edgefirst_client'

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__new__ builtin 

__new__(*args, **kwargs)

Create and return a new object. See help(type) for accurate signature.

__repr__ method descriptor 

__repr__()

Return repr(self).

AnnotationType

AnnotationType is used to identify the type of annotation in the dataset.

Box2d class 

Box2d = AnnotationType.Box2d

AnnotationType is used to identify the type of annotation in the dataset.

Box3d class 

Box3d = AnnotationType.Box3d

AnnotationType is used to identify the type of annotation in the dataset.

Segmentation class 

Segmentation = AnnotationType.Segmentation

AnnotationType is used to identify the type of annotation in the dataset.

__doc__ class 

__doc__ = "AnnotationType is used to identify the type of annotation in the dataset."

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__hash__ class 

__hash__ = None

The type of the None singleton.

__module__ class 

__module__ = 'edgefirst_client'

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__eq__ method descriptor 

__eq__(value)

Return self==value.

__ge__ method descriptor 

__ge__(value)

Return self>=value.

__gt__ method descriptor 

__gt__(value)

Return self>value.

__int__ method descriptor 

__int__()

int(self)

__le__ method descriptor 

__le__(value)

Return self<=value.

__lt__ method descriptor 

__lt__(value)

Return self<value.

__ne__ method descriptor 

__ne__(value)

Return self!=value.

__new__ builtin 

__new__(*args, **kwargs)

Create and return a new object. See help(type) for accurate signature.

__repr__ method descriptor 

__repr__()

Return repr(self).

Box2d

__doc__ class 

__doc__ = None

The type of the None singleton.

__module__ class 

__module__ = 'edgefirst_client'

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__new__ builtin 

__new__(*args, **kwargs)

Create and return a new object. See help(type) for accurate signature.

Box3d

__doc__ class 

__doc__ = None

The type of the None singleton.

__module__ class 

__module__ = 'edgefirst_client'

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__new__ builtin 

__new__(*args, **kwargs)

Create and return a new object. See help(type) for accurate signature.

Client

The EdgeFirst Client handles the connection to the EdgeFirst Studio Server and manages authentication and the client RPC calls. The client also provides various utility methods for interacting with datasets and converting them to and from Polars DataFrames.

__doc__ class 

__doc__ = "The EdgeFirst Client handles the connection to the EdgeFirst Studio Server\nand manages authentication and the client RPC calls.  The client also\nprovides various utility methods for interacting with datasets and\nconverting them to and from Polars DataFrames."

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__module__ class 

__module__ = 'edgefirst_client'

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__new__ builtin 

__new__(*args, **kwargs)

Create and return a new object. See help(type) for accurate signature.

annotation_sets_sync method descriptor 

annotation_sets_sync(dataset_id)

List available annotation sets for the specified dataset.

annotations_dataframe_sync method descriptor 

annotations_dataframe_sync(
    annotation_set_id, types=Ellipsis
)

Get the AnnotationGroup for the specified annotation set with the requested annotation types. The annotation type is used to filter the annotations returned. Images which do not have any annotations are included in the result.

The result is a DataFrame following the EdgeFirst Dataset Format definition.

To get the annotations as a vector of AnnotationGroup objects, use the annotations_sync method instead.

annotations_sync method descriptor 

annotations_sync(annotation_set_id, types=Ellipsis)

Get the AnnotationGroup for the specified annotation set with the requested annotation types. The annotation type is used to filter the annotations returned. Images which do not have any annotations are included in the result.

The result is a vector of AnnotationGroup objects which contain the full dataset along with the annotations for the specified types.

To get the annotations as a DataFrame, use the annotations_dataframe_sync method instead.

artifacts_sync method descriptor 

artifacts_sync(trainer_session_id)

List the artifacts for the specified trainer session. The artifacts are returned as a vector of strings.

create_snapshot_sync method descriptor 

create_snapshot_sync(path, progress=None)

Create a new snapshot from the file at the specified path. If the path is a directory then all the files in the directory are uploaded. The snapshot name will be the specified path, either file or directory.

The progress callback can be used to monitor the progress of the upload. The callback must have the signature fn(current: int, total: int).

dataset_images_sync method descriptor 

dataset_images_sync(dataset_id)

Get image ids for the dataset with the specified dataset ID.

dataset_sync method descriptor 

dataset_sync(dataset_id)

Return the dataset with the specified dataset ID. If the dataset does not exist, an error is returned.

datasets_sync method descriptor 

datasets_sync(project_id)

Returns a list of datasets available to the user. The datasets are returned as a vector of Dataset objects.

download_artifact_sync method descriptor 

download_artifact_sync(
    trainer_session_id, modelname, filename, progress=None
)

Download the model artifact for the specified trainer session to the specified file path. A progress callback can be provided to monitor the progress of the download over a watch channel.

download_dataset_sync method descriptor 

download_dataset_sync(
    dataset_id, output=None, progress=None
)

Downloads the dataset with the specified dataset ID to the specified file path. A progress callback can be provided to monitor the progress of the download.

The callback must have the signature fn(current: int, total: int).

download_snapshot_sync method descriptor 

download_snapshot_sync(
    snapshot_id, output=None, progress=None
)

Downloads a snapshot from the server. The snapshot could be a single file or a directory of files. The snapshot is downloaded to the specified path.

A progress callback can be provided to monitor the progress of the download.

The callback must have the signature fn(current: int, total: int).

find_dataset_sync method descriptor 

find_dataset_sync(project_id, name)

Find a dataset by name within the project with the specified project ID.

find_project_sync method descriptor 

find_project_sync(name)

Find a project by name. If the project does not exist, None is returned.

find_snapshots_sync method descriptor 

find_snapshots_sync(name)

Find the snapshots containing the provided description.

find_trainer_session_sync method descriptor 

find_trainer_session_sync(trainer_id, name)

Find a trainer session by name within the trainer with the specified trainer ID. If the trainer session does not exist, None is returned.

find_trainer_sync method descriptor 

find_trainer_sync(project_id, name)

Find a trainer by name within the project with the specified project ID. If the trainer does not exist, None is returned.

image_sync method descriptor 

image_sync(image_id)

Get image metadata for the specified image ID.

login_sync method descriptor 

login_sync(username, password)

Login to the server using the specified username and password. The server will authenticate the user and return a token that can be used to authenticate future requests. The token is stored in the client and used to authenticate the client with the server.

project_sync method descriptor 

project_sync(project_id)

Return the project with the specified project ID. If the project does not exist, an error is returned.

projects_sync method descriptor 

projects_sync()

Returns a list of projects available to the user. The projects are returned as a vector of Project objects.

Projects are the top-level organizational unit in Deep View Enterprise. Projects contain datasets, trainers, and trainer sessions. Projects are used to group related datasets and trainers together.

restore_snapshot_sync method descriptor 

restore_snapshot_sync(
    project_id,
    snapshot_id,
    depth_gen,
    agtg_pipeline,
    dataset_name=None,
    dataset_description=None,
)

The snapshot restore method is used to restore a snapshot to the server. The restore method can perform a few different operations depending on the snapshot type.

For MCAP snapshots the restore function will convert the MCAP into a dataset and optionally run the auto-annotation pipeline.

snapshot_sync method descriptor 

snapshot_sync(snapshot_id)

Get the snapshot with the specified id.

snapshots_sync method descriptor 

snapshots_sync()

List available snapshots.

token_sync method descriptor 

token_sync()

Return the token used to authenticate the client with the server. When logging into the server using a username and password, the token is returned by the server and stored in the client for future interactions.

trainer_session_sync method descriptor 

trainer_session_sync(trainer_session_id)

Return the trainer session with the specified trainer session ID. If the trainer session does not exist, an error is returned.

trainer_sessions_sync method descriptor 

trainer_sessions_sync(trainer_id)

Returns a list of trainer sessions available to the user. The trainer sessions are returned as a vector of TrainerSession objects. Trainer sessions are akin to runs in MLFlow terminology. These represent an actual training session which will produce metrics and model artifacts.

trainer_sync method descriptor 

trainer_sync(trainer_id)

Return the trainer with the specified trainer ID. If the trainer does not exist, an error is returned.

trainers_sync method descriptor 

trainers_sync(project_id)

Returns a list of trainers available to the user. The trainers are returned as a vector of Trainer objects. Trainers are akin to an Experiment in MLFlow terminology. Each trainer can have multiple trainer sessions associated with it, these would be akin to runs in MLFlow.

verify_token_sync method descriptor 

verify_token_sync()

Verify the token used to authenticate the client with the server. This method is used to ensure that the token is still valid and has not expired. If the token is invalid, the server will return an error and the client will need to login again.

version_sync method descriptor 

version_sync()

Return the version of the Deep View Enterprise server for the current client connection.

Segmentation

__doc__ class 

__doc__ = None

The type of the None singleton.

__module__ class 

__module__ = 'edgefirst_client'

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to 'utf-8'. errors defaults to 'strict'.

__new__ builtin 

__new__(*args, **kwargs)

Create and return a new object. See help(type) for accurate signature.