​
check_response_errors

edgeimpulse.util.check_response_errors(
		request
)
Check for standard errors and raise an exception with the details if found. Parameters
  • request

​
configure_generic_client

edgeimpulse.util.configure_generic_client(
		key: str,
		key_type: str | None = 'api',
		host: str | None = 'https://studio.edgeimpulse.com/v1'
) ‑> edgeimpulse_api.api_client.ApiClient
Configure generic api client which the right key. Parameters Return edgeimpulse_api.api_client.ApiClient

​
connect_websocket

edgeimpulse.util.connect_websocket(
		token,
		host: str = None
) ‑> socketio.client.Client
Connects to the websocket server. Parameters: token (str): The authentication token. host (str, optional): The hostname. If None, API_ENDPOINT will be used. Returns: object: Websocket object. Parameters
  • token
  • host: str = None
Return socketio.client.Client

​
default_project_id_for

edgeimpulse.util.default_project_id_for(
		client: edgeimpulse_api.api_client.ApiClient
) ‑> int
Derive project id from api_key used to configure generic client. Parameters
  • client: edgeimpulse_api.api_client.ApiClient
Return int

​
encode_file_as_base64

edgeimpulse.util.encode_file_as_base64(
		filename: str
)
Encode a file as base64. Parameters
  • filename: str

​
get_organization_websocket

edgeimpulse.util.get_organization_websocket(
		client,
		organization_id: int,
		host: str = None
) ‑> socketio.client.Client
Gets a websocket to listen to organization events. Parameters
  • client
  • organization_id: int
  • host: str = None
Return socketio.client.Client

​
get_profile_devices

edgeimpulse.util.get_profile_devices(
		client: edgeimpulse_api.api_client.ApiClient,
		project_id: int | None = None
) ‑> List[str]
Pull a list of profile devices. Parameters
  • client: edgeimpulse_api.api_client.ApiClient
  • project_id: int | None = None
Return List[str]

​
get_project_deploy_targets

edgeimpulse.util.get_project_deploy_targets(
		client: edgeimpulse_api.api_client.ApiClient,
		project_id: int | None = None
) ‑> List[str]
Pull a list of deploy targets. Parameters
  • client: edgeimpulse_api.api_client.ApiClient
  • project_id: int | None = None
Return List[str]

​
get_project_websocket

edgeimpulse.util.get_project_websocket(
		client,
		project_id: int,
		host: str = None
) ‑> socketio.client.Client
Gets a websocket to listen to project events. Parameters
  • client
  • project_id: int
  • host: str = None
Return socketio.client.Client

​
get_user_agent

edgeimpulse.util.get_user_agent(
		add_platform_info=False
)
Get user agent string for API calls so we can track usage. Parameters
  • add_platform_info=False

​
inspect_model

edgeimpulse.util.inspect_model(
		model: pathlib._local.Path | str | bytes | Any,
		tempdir: str
) ‑> Tuple[str, str]
Load tflite model. Parameters
  • model: pathlib._local.Path | str | bytes | Any
  • tempdir: str
Return Tuple[str, str]

​
inspect_representative_data

edgeimpulse.util.inspect_representative_data(
		data: pathlib._local.Path | str | bytes | Any
) ‑> str | None
Ensure representative data is saved to disk for upload. Parameters
  • data: pathlib._local.Path | str | bytes | Any
Return str | None

​
is_keras_model

edgeimpulse.util.is_keras_model(
		model
)
Check if model is a keras model. Parameters
  • model

​
is_numpy_array

edgeimpulse.util.is_numpy_array(
		array
)
Check if array is a numpy array. Parameters
  • array

​
is_onnx_model

edgeimpulse.util.is_onnx_model(
		model
)
Check if given model is an onnx model. Parameters
  • model

​
is_path_to_numpy_file

edgeimpulse.util.is_path_to_numpy_file(
		path
)
Check if given path is a numpy file. Parameters
  • path

​
is_path_to_onnx_model

edgeimpulse.util.is_path_to_onnx_model(
		path
)
Check if given path is a onnx file. Parameters
  • path

​
is_path_to_tf_saved_model_directory

edgeimpulse.util.is_path_to_tf_saved_model_directory(
		model_dir
)
Check if directory contains a saved model. Parameters
  • model_dir

​
is_path_to_tf_saved_model_zipped

edgeimpulse.util.is_path_to_tf_saved_model_zipped(
		model
)
Check if path is poiting to a zipped model. Parameters
  • model

​
is_type_accepted_by_open

edgeimpulse.util.is_type_accepted_by_open(
		path
)
Check if given path is a. string or a Path. Parameters
  • path

​
make_zip_archive

edgeimpulse.util.make_zip_archive(
		saved_model_path
)
Create zip archive from a model path. Parameters
  • saved_model_path

​
numpy_installed

edgeimpulse.util.numpy_installed(
		
) ‑> bool
Return True if NumPy is installed, otherwise False. Return bool

​
onnx_installed

edgeimpulse.util.onnx_installed(
		
) ‑> bool
Return True if ONNX is installed, otherwise False. Return bool

​
pandas_installed

edgeimpulse.util.pandas_installed(
		
) ‑> bool
Return True if pandas is installed, otherwise False. Return bool

​
poll

edgeimpulse.util.poll(
		jobs_client: edgeimpulse_api.api.jobs_api.JobsApi,
		project_id: int,
		job_id: int,
		timeout_sec: float | None = None
) ‑> edgeimpulse_api.models.get_job_response.GetJobResponse
Poll a specific job within a project until done or timmeout is reached. Parameters
  • jobs_client: edgeimpulse_api.api.jobs_api.JobsApi
  • project_id: int
  • job_id: int
  • timeout_sec: float | None = None
Return edgeimpulse_api.models.get_job_response.GetJobResponse

​
run_job_until_completion

edgeimpulse.util.run_job_until_completion(
		ws,
		job_id: int,
		data_cb=None,
		timeout_sec: int | None = None
)
Runs a project or organization job until completion. Parameters
  • ws
  • job_id: int
  • data_cb=None
  • timeout_sec: int | None = None

​
run_organization_job_until_completion

edgeimpulse.util.run_organization_job_until_completion(
		organization_id: int,
		job_id: int,
		data_cb=None,
		client=None,
		timeout_sec: int | None = None
) ‑> None
Runs an organization job until completion. Parameters
  • organization_id: int
  • job_id: int
  • data_cb=None
  • client=None
  • timeout_sec: int | None = None
Return None

​
run_project_job_until_completion

edgeimpulse.util.run_project_job_until_completion(
		job_id: int,
		data_cb=None,
		client=None,
		project_id: int | None = None,
		timeout_sec: int | None = None
) ‑> None
Runs a project job until completion. Parameters
  • job_id: int
  • data_cb=None
  • client=None
  • project_id: int | None = None
  • timeout_sec: int | None = None
Return None

​
save_model

edgeimpulse.util.save_model(
		model: pathlib._local.Path | str | bytes,
		directory: str
) ‑> str
Save a machine learning model to the specified directory. Parameters
  • model: pathlib._local.Path | str | bytes
  • directory: str
Return str

​
save_representative_data

edgeimpulse.util.save_representative_data(
		data: pathlib._local.Path | str | bytes,
		directory: str
) ‑> str
Save the representive data to a directory. Parameters
  • data: pathlib._local.Path | str | bytes
  • directory: str
Return str

​
tensorflow_installed

edgeimpulse.util.tensorflow_installed(
		
) ‑> bool
Return True if TensorFlow is installed, otherwise False. Return bool

​
upload_pretrained_model_and_data

edgeimpulse.util.upload_pretrained_model_and_data(
		tempdir: str,
		client: edgeimpulse_api.api_client.ApiClient,
		project_id: int,
		model: pathlib._local.Path | str | bytes | Any,
		representative_data: pathlib._local.Path | str | bytes | Any | None = None,
		device: str | None = None,
		timeout_sec: float | None = None
) ‑> edgeimpulse_api.models.get_job_response.GetJobResponse
Upload a model and data to Edge Impulse servers. Parameters
  • tempdir: str
  • client: edgeimpulse_api.api_client.ApiClient
  • project_id: int
  • model: pathlib._local.Path | str | bytes | Any
  • representative_data: pathlib._local.Path | str | bytes | Any | None = None
  • device: str | None = None
  • timeout_sec: float | None = None
Return edgeimpulse_api.models.get_job_response.GetJobResponse