raw_data_api module
RawDataApi
class edgeimpulse_api.api.raw_data_api.RawDataApi(
api_client=None
)Parameters
api_client=None
Methods
batch_add_metadata
edgeimpulse_api.api.raw_data_api.batch_add_metadata(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
batch_add_metadata_request: edgeimpulse_api.models.batch_add_metadata_request.BatchAddMetadataRequest,
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None,
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None,
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None,
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None,
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None,
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None,
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None,
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None,
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None,
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None,
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None,
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None,
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None,
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None,
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None,
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None,
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200ResponseAdd metadata (multiple samples)
Add specific metadata for multiple samples.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
batch_add_metadata_request: edgeimpulse_api.models.batch_add_metadata_request.BatchAddMetadataRequest
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200Response
batch_clear_metadata
edgeimpulse_api.api.raw_data_api.batch_clear_metadata(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None,
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None,
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None,
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None,
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None,
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None,
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None,
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None,
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None,
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None,
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None,
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None,
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None,
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None,
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None,
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None,
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseClear all metadata (multiple samples)
Clears all metadata for multiple samples.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
batch_clear_metadata_by_key
edgeimpulse_api.api.raw_data_api.batch_clear_metadata_by_key(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
batch_clear_metadata_by_key_request: edgeimpulse_api.models.batch_clear_metadata_by_key_request.BatchClearMetadataByKeyRequest,
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None,
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None,
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None,
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None,
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None,
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None,
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None,
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None,
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None,
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None,
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None,
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None,
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None,
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None,
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None,
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None,
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200ResponseClear metadata by key (multiple samples)
Clears a specific metadata field (by key) for multiple samples.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
batch_clear_metadata_by_key_request: edgeimpulse_api.models.batch_clear_metadata_by_key_request.BatchClearMetadataByKeyRequest
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200Response
batch_delete
edgeimpulse_api.api.raw_data_api.batch_delete(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None,
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None,
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None,
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None,
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None,
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None,
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None,
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None,
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None,
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None,
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None,
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None,
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None,
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None,
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None,
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None,
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200ResponseRemove multiple samples
Deletes samples. Note that this does not delete the data from cold storage. Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200Response
batch_disable
edgeimpulse_api.api.raw_data_api.batch_disable(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None,
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None,
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None,
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None,
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None,
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None,
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None,
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None,
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None,
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None,
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None,
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None,
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None,
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None,
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None,
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None,
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200ResponseDisable multiple samples
Disables samples, ensuring that they are excluded from the dataset. Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200Response
batch_edit_labels
edgeimpulse_api.api.raw_data_api.batch_edit_labels(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
edit_sample_label_request: edgeimpulse_api.models.edit_sample_label_request.EditSampleLabelRequest,
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None,
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None,
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None,
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None,
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None,
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None,
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None,
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None,
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None,
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None,
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None,
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None,
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None,
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None,
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None,
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None,
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200ResponseEdit labels for multiple samples
Sets the label (also known as class) of multiple samples. Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
edit_sample_label_request: edgeimpulse_api.models.edit_sample_label_request.EditSampleLabelRequest
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200Response
batch_enable
edgeimpulse_api.api.raw_data_api.batch_enable(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None,
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None,
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None,
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None,
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None,
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None,
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None,
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None,
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None,
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None,
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None,
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None,
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None,
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None,
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None,
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None,
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200ResponseEnable multiple samples
Enables samples, ensuring that they are not excluded from the dataset. Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200Response
batch_move
edgeimpulse_api.api.raw_data_api.batch_move(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
move_raw_data_request: edgeimpulse_api.models.move_raw_data_request.MoveRawDataRequest,
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None,
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None,
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None,
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None,
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None,
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None,
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None,
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None,
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None,
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None,
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None,
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None,
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None,
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None,
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None,
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None,
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None,
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200ResponseMove multiple samples
Move multiple samples to another category (e.g. from test to training). Depending on the number of affected samples this will either execute immediately or return the ID of a job that will perform this action in batches.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
move_raw_data_request: edgeimpulse_api.models.move_raw_data_request.MoveRawDataRequest
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None
ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
exclude_ids: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Exclude samples with an ID within the given list of IDs, given as a JSON string', extra={})] = None
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200Response
classify_using_autolabel
edgeimpulse_api.api.raw_data_api.classify_using_autolabel(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
object_detection_auto_label_request: edgeimpulse_api.models.object_detection_auto_label_request.ObjectDetectionAutoLabelRequest,
**kwargs
) ‑> edgeimpulse_api.models.object_detection_auto_label_response.ObjectDetectionAutoLabelResponseAuto-label an image
Classify an image using another neural network.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
object_detection_auto_label_request: edgeimpulse_api.models.object_detection_auto_label_request.ObjectDetectionAutoLabelRequest
**kwargs
Return
edgeimpulse_api.models.object_detection_auto_label_response.ObjectDetectionAutoLabelResponse
clear_all_object_detection_labels
edgeimpulse_api.api.raw_data_api.clear_all_object_detection_labels(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseClear all object detection labels
Clears all object detection labels for this dataset, and places all images back in the labeling queue.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
clear_data_explorer
edgeimpulse_api.api.raw_data_api.clear_data_explorer(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseClear data explorer
Remove the current data explorer state
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
count_samples
edgeimpulse_api.api.raw_data_api.count_samples(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None,
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None,
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None,
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None,
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None,
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None,
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None,
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None,
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None,
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None,
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None,
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None,
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None,
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None,
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None,
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None,
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.count_samples_response.CountSamplesResponseCount samples
Count all raw data by category.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.count_samples_response.CountSamplesResponse
crop_sample
edgeimpulse_api.api.raw_data_api.crop_sample(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
crop_sample_request: edgeimpulse_api.models.crop_sample_request.CropSampleRequest,
**kwargs
) ‑> edgeimpulse_api.models.crop_sample_response.CropSampleResponseCrop sample
Crop a sample to within a new range.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
crop_sample_request: edgeimpulse_api.models.crop_sample_request.CropSampleRequest
**kwargs
Return
edgeimpulse_api.models.crop_sample_response.CropSampleResponse
delete_all_samples
edgeimpulse_api.api.raw_data_api.delete_all_samples(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseRemove all samples
Deletes all samples for this project over all categories. This also invalidates all DSP and learn blocks. Note that this does not delete the data from cold storage.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
delete_all_samples_by_category
edgeimpulse_api.api.raw_data_api.delete_all_samples_by_category(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to download data from', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseRemove all samples by category
Deletes all samples for this project over a single category. Note that this does not delete the data from cold storage.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to download data from', extra={})]
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
delete_sample
edgeimpulse_api.api.raw_data_api.delete_sample(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseRemove sample
Deletes the sample. Note that this does not delete the data from cold storage.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
disable_sample
edgeimpulse_api.api.raw_data_api.disable_sample(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseDisable sample
Disable a sample, ensuring that it is excluded from the dataset.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
edit_label
edgeimpulse_api.api.raw_data_api.edit_label(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
edit_sample_label_request: edgeimpulse_api.models.edit_sample_label_request.EditSampleLabelRequest,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseEdit label
Sets the label (also known as class) of the sample. Use the same label for similar types of data, as they are used during training.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
edit_sample_label_request: edgeimpulse_api.models.edit_sample_label_request.EditSampleLabelRequest
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
enable_sample
edgeimpulse_api.api.raw_data_api.enable_sample(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseEnable sample
Enable a sample, ensuring that it is not excluded from the dataset.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
find_segments_in_sample
edgeimpulse_api.api.raw_data_api.find_segments_in_sample(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
find_segment_sample_request: edgeimpulse_api.models.find_segment_sample_request.FindSegmentSampleRequest,
**kwargs
) ‑> edgeimpulse_api.models.find_segment_sample_response.FindSegmentSampleResponseFind segments
Find start and end times for all non-noise events in a sample
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
find_segment_sample_request: edgeimpulse_api.models.find_segment_sample_request.FindSegmentSampleRequest
**kwargs
Return
edgeimpulse_api.models.find_segment_sample_response.FindSegmentSampleResponse
get_ai_actions_proposed_changes
edgeimpulse_api.api.raw_data_api.get_ai_actions_proposed_changes(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
job_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Job ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.get_ai_actions_proposed_changes_response.GetAIActionsProposedChangesResponseGet AI Actions proposed changes
Get proposed changes from an AI Actions job.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
job_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Job ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.get_ai_actions_proposed_changes_response.GetAIActionsProposedChangesResponse
get_all_imported_from
edgeimpulse_api.api.raw_data_api.get_all_imported_from(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
limit: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Maximum number of results', extra={})] = None,
offset: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Offset in results, can be used in conjunction with LimitResultsParameter to implement paging.', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.get_all_imported_from_response.GetAllImportedFromResponseList data with "imported from" metadata key
Lists all data with an 'imported from' metadata key. Used to check in a data source which items are already in a project.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
limit: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Maximum number of results', extra={})] = None
offset: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Offset in results, can be used in conjunction with LimitResultsParameter to implement paging.', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.get_all_imported_from_response.GetAllImportedFromResponse
get_data_explorer_features
edgeimpulse_api.api.raw_data_api.get_data_explorer_features(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.get_data_explorer_features_response.GetDataExplorerFeaturesResponseGet data explorer features
t-SNE2 output of the raw dataset
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.get_data_explorer_features_response.GetDataExplorerFeaturesResponse
get_data_explorer_predictions
edgeimpulse_api.api.raw_data_api.get_data_explorer_predictions(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.data_explorer_predictions_response.DataExplorerPredictionsResponseGet data explorer predictions
Predictions for every data explorer point (only available when using current impulse to populate data explorer)
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.data_explorer_predictions_response.DataExplorerPredictionsResponse
get_data_explorer_settings
edgeimpulse_api.api.raw_data_api.get_data_explorer_settings(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.get_data_explorer_settings_response.GetDataExplorerSettingsResponseGet data explorer settings
Get data explorer configuration, like the type of data, and the input / dsp block to use.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.get_data_explorer_settings_response.GetDataExplorerSettingsResponse
get_dataset_ratio
edgeimpulse_api.api.raw_data_api.get_dataset_ratio(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.get_dataset_ratio_response.GetDatasetRatioResponseGet dataset ratio
Retrieve number of samples in train and test set.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.get_dataset_ratio_response.GetDatasetRatioResponse
get_diversity_data
edgeimpulse_api.api.raw_data_api.get_diversity_data(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.get_diversity_data_response.GetDiversityDataResponseGet diversity metrics data
Obtain metrics that describe the similarity and diversity of a dataset. To calculate these metrics, use the calculateDataQualityMetrics endpoint.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.get_diversity_data_response.GetDiversityDataResponse
get_label_noise_data
edgeimpulse_api.api.raw_data_api.get_label_noise_data(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.get_label_noise_data_response.GetLabelNoiseDataResponseGet label noise data
Obtain metrics that describe potential label noise issues in the dataset. To calculate these metrics, use the calculateDataQualityMetrics endpoint.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.get_label_noise_data_response.GetLabelNoiseDataResponse
get_object_detection_label_queue
edgeimpulse_api.api.raw_data_api.get_object_detection_label_queue(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.object_detection_label_queue_response.ObjectDetectionLabelQueueResponseObject detection label queue
Get all unlabeled items from the object detection queue.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.object_detection_label_queue_response.ObjectDetectionLabelQueueResponse
get_object_detection_label_queue_count
edgeimpulse_api.api.raw_data_api.get_object_detection_label_queue_count(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.object_detection_label_queue_count_response.ObjectDetectionLabelQueueCountResponseObject detection label queue count
Get count for unlabeled items from the object detection queue.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.object_detection_label_queue_count_response.ObjectDetectionLabelQueueCountResponse
get_sample
edgeimpulse_api.api.raw_data_api.get_sample(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
limit_payload_values: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Limit the number of payload values in the response', extra={})] = None,
cache_key: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='If set, then a long cache header is sent. If this is omitted then a no-cache header is sent. You can use this if you f.e. know the last modified date of a sample. Stick the last modified date in the cache key, so the sample can be stored in browser cache (and will automatically be invalidated if the modified date changes).', extra={})] = None,
impulse_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Impulse ID. If this is unset then the default impulse is used.', extra={})] = None,
proposed_actions_job_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Pass this parameter when querying samples from inside an AI Action job. If you pass this parameter in a multi-stage AI Action, previous proposed changes (from an earlier step) will be applied to the returned dataset.', extra={})] = None,
truncate_structured_labels: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='If true, only a slice of labels will be returned for samples with multiple labels.', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.get_sample_response.GetSampleResponseGet sample
Get a sample.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
limit_payload_values: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Limit the number of payload values in the response', extra={})] = None
cache_key: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='If set, then a long cache header is sent. If this is omitted then a no-cache header is sent. You can use this if you f.e. know the last modified date of a sample. Stick the last modified date in the cache key, so the sample can be stored in browser cache (and will automatically be invalidated if the modified date changes).', extra={})] = None
impulse_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Impulse ID. If this is unset then the default impulse is used.', extra={})] = None
proposed_actions_job_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Pass this parameter when querying samples from inside an AI Action job. If you pass this parameter in a multi-stage AI Action, previous proposed changes (from an earlier step) will be applied to the returned dataset.', extra={})] = None
truncate_structured_labels: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='If true, only a slice of labels will be returned for samples with multiple labels.', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.get_sample_response.GetSampleResponse
get_sample_as_audio
edgeimpulse_api.api.raw_data_api.get_sample_as_audio(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
axis_ix: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Axis index', extra={})],
slice_start: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Begin index of the slice. If not given, the whole sample is used.', extra={})] = None,
slice_end: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='End index of the slice. If not given, the whole sample is used.', extra={})] = None,
cache_key: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='If set, then a long cache header is sent. If this is omitted then a no-cache header is sent. You can use this if you f.e. know the last modified date of a sample. Stick the last modified date in the cache key, so the sample can be stored in browser cache (and will automatically be invalidated if the modified date changes).', extra={})] = None,
**kwargs
) ‑> strGet WAV file
Get a sample as a WAV file. This only applies to samples with an audio axis.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
axis_ix: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Axis index', extra={})]
slice_start: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Begin index of the slice. If not given, the whole sample is used.', extra={})] = None
slice_end: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='End index of the slice. If not given, the whole sample is used.', extra={})] = None
cache_key: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='If set, then a long cache header is sent. If this is omitted then a no-cache header is sent. You can use this if you f.e. know the last modified date of a sample. Stick the last modified date in the cache key, so the sample can be stored in browser cache (and will automatically be invalidated if the modified date changes).', extra={})] = None
**kwargs
Return
str
get_sample_as_image
edgeimpulse_api.api.raw_data_api.get_sample_as_image(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
after_input_block: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='Whether to process the image through the input block first', extra={})] = None,
cache_key: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='If set, then a long cache header is sent. If this is omitted then a no-cache header is sent. You can use this if you f.e. know the last modified date of a sample. Stick the last modified date in the cache key, so the sample can be stored in browser cache (and will automatically be invalidated if the modified date changes).', extra={})] = None,
impulse_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Impulse ID. If this is unset then the default impulse is used.', extra={})] = None,
**kwargs
) ‑> strGet image file
Get a sample as an image file. This only applies to samples with RGBA data.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
after_input_block: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='Whether to process the image through the input block first', extra={})] = None
cache_key: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='If set, then a long cache header is sent. If this is omitted then a no-cache header is sent. You can use this if you f.e. know the last modified date of a sample. Stick the last modified date in the cache key, so the sample can be stored in browser cache (and will automatically be invalidated if the modified date changes).', extra={})] = None
impulse_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Impulse ID. If this is unset then the default impulse is used.', extra={})] = None
**kwargs
Return
str
get_sample_as_raw
edgeimpulse_api.api.raw_data_api.get_sample_as_raw(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
**kwargs
) ‑> strDownload file
Download a sample in it's original format as uploaded to the ingestion service.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
**kwargs
Return
str
get_sample_as_video
edgeimpulse_api.api.raw_data_api.get_sample_as_video(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
after_input_block: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='Whether to process the image through the input block first', extra={})] = None,
cache_key: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='If set, then a long cache header is sent. If this is omitted then a no-cache header is sent. You can use this if you f.e. know the last modified date of a sample. Stick the last modified date in the cache key, so the sample can be stored in browser cache (and will automatically be invalidated if the modified date changes).', extra={})] = None,
impulse_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Impulse ID. If this is unset then the default impulse is used.', extra={})] = None,
**kwargs
) ‑> strGet video file
Get a sample as an video file. This only applies to samples with video data.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
after_input_block: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='Whether to process the image through the input block first', extra={})] = None
cache_key: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='If set, then a long cache header is sent. If this is omitted then a no-cache header is sent. You can use this if you f.e. know the last modified date of a sample. Stick the last modified date in the cache key, so the sample can be stored in browser cache (and will automatically be invalidated if the modified date changes).', extra={})] = None
impulse_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Impulse ID. If this is unset then the default impulse is used.', extra={})] = None
**kwargs
Return
str
get_sample_metadata
edgeimpulse_api.api.raw_data_api.get_sample_metadata(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.get_sample_metadata_response.GetSampleMetadataResponseGet project sample metadata
Get metadata for all samples in a project.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
**kwargs
Return
edgeimpulse_api.models.get_sample_metadata_response.GetSampleMetadataResponse
get_sample_metadata_filter_options
edgeimpulse_api.api.raw_data_api.get_sample_metadata_filter_options(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
limit: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Maximum number of results', extra={})] = None,
offset: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Offset in results, can be used in conjunction with LimitResultsParameter to implement paging.', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.get_sample_metadata_filter_options_response.GetSampleMetadataFilterOptionsResponseGet project sample metadata filter options
Get a list of unique key value pairs across all samples in a project that can be applied as filters to the /api/{projectId}/raw-data endpoint
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
limit: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Maximum number of results', extra={})] = None
offset: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Offset in results, can be used in conjunction with LimitResultsParameter to implement paging.', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.get_sample_metadata_filter_options_response.GetSampleMetadataFilterOptionsResponse
get_sample_slice
edgeimpulse_api.api.raw_data_api.get_sample_slice(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
slice_start: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Begin index of the slice', extra={})],
slice_end: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='End index of the slice. If not given, the sample will be sliced to the same length as the impulse input block window length.', extra={})] = None,
impulse_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Impulse ID. If this is unset then the default impulse is used.', extra={})] = None,
truncate_structured_labels: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='If true, only a slice of labels will be returned for samples with multiple labels.', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.get_sample_response.GetSampleResponseGet sample slice
Get a slice of a sample.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
slice_start: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Begin index of the slice', extra={})]
slice_end: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='End index of the slice. If not given, the sample will be sliced to the same length as the impulse input block window length.', extra={})] = None
impulse_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Impulse ID. If this is unset then the default impulse is used.', extra={})] = None
truncate_structured_labels: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='If true, only a slice of labels will be returned for samples with multiple labels.', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.get_sample_response.GetSampleResponse
get_uncropped_downsampled_sample
edgeimpulse_api.api.raw_data_api.get_uncropped_downsampled_sample(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
limit_payload_values: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Limit the number of payload values in the response', extra={})] = None,
zoom_start: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Zoom into the sample, with the focus starting at this index', extra={})] = None,
zoom_end: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Zoom into the sample, with the focus ending at this index', extra={})] = None,
impulse_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Impulse ID. If this is unset then the default impulse is used.', extra={})] = None,
truncate_structured_labels: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='If true, only a slice of labels will be returned for samples with multiple labels.', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.get_sample_response.GetSampleResponseGet the original downsampled data
Get the original, uncropped, downsampled data.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
limit_payload_values: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Limit the number of payload values in the response', extra={})] = None
zoom_start: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Zoom into the sample, with the focus starting at this index', extra={})] = None
zoom_end: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Zoom into the sample, with the focus ending at this index', extra={})] = None
impulse_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Impulse ID. If this is unset then the default impulse is used.', extra={})] = None
truncate_structured_labels: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='If true, only a slice of labels will be returned for samples with multiple labels.', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.get_sample_response.GetSampleResponse
has_data_explorer_features
edgeimpulse_api.api.raw_data_api.has_data_explorer_features(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.has_data_explorer_features_response.HasDataExplorerFeaturesResponseCheck data explorer features
t-SNE2 output of the raw dataset
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.has_data_explorer_features_response.HasDataExplorerFeaturesResponse
has_diversity_data
edgeimpulse_api.api.raw_data_api.has_diversity_data(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.has_data_explorer_features_response.HasDataExplorerFeaturesResponseCheck if data diversity metrics exist
Determine if data diversity metrics have been calculated. To calculate these metrics, use the calculateDataQualityMetrics endpoint.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.has_data_explorer_features_response.HasDataExplorerFeaturesResponse
has_label_noise_data
edgeimpulse_api.api.raw_data_api.has_label_noise_data(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.has_data_explorer_features_response.HasDataExplorerFeaturesResponseCheck if label noise metrics exist
Determine if label noise metrics have been calculated. To calculate these metrics, use the calculateDataQualityMetrics endpoint.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.has_data_explorer_features_response.HasDataExplorerFeaturesResponse
list_samples
edgeimpulse_api.api.raw_data_api.list_samples(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})],
limit: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Maximum number of results', extra={})] = None,
offset: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Offset in results, can be used in conjunction with LimitResultsParameter to implement paging.', extra={})] = None,
exclude_sensors: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='Whether to exclude sensors in the response (as these can slow down requests when you have large pages).', extra={})] = None,
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None,
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None,
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None,
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None,
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None,
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None,
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None,
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None,
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None,
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None,
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None,
proposed_actions_job_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Pass this parameter when querying samples from inside an AI Action job. If you pass this parameter in a multi-stage AI Action, previous proposed changes (from an earlier step) will be applied to the returned dataset.', extra={})] = None,
truncate_structured_labels: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='If true, only a slice of labels will be returned for samples with multiple labels.', extra={})] = None,
sort_by: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='If not specified, "id-desc" is used.', extra={})] = None,
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None,
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None,
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None,
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None,
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None,
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None,
**kwargs
) ‑> edgeimpulse_api.models.list_samples_response.ListSamplesResponseList samples
Retrieve all raw data by category.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
category: Annotated[edgeimpulse_api.models.raw_data_category.RawDataCategory, FieldInfo(default=Ellipsis, description='Which of the three acquisition categories to retrieve data from', extra={})]
limit: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Maximum number of results', extra={})] = None
offset: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Offset in results, can be used in conjunction with LimitResultsParameter to implement paging.', extra={})] = None
exclude_sensors: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='Whether to exclude sensors in the response (as these can slow down requests when you have large pages).', extra={})] = None
labels: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label within the given list of labels, given as a JSON string', extra={})] = None
filename: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Only include samples whose filename includes the given filename', extra={})] = None
max_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples shorter than the given length, in milliseconds', extra={})] = None
min_length: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Only include samples longer than the given length, in milliseconds', extra={})] = None
min_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with higher frequency than given frequency, in hertz', extra={})] = None
max_frequency: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with lower frequency than given frequency, in hertz', extra={})] = None
signature_validity: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include samples with either valid or invalid signatures', extra={})] = None
include_disabled: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only enabled or disabled samples (or both)', extra={})] = None
min_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label >= this value', extra={})] = None
max_label: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Only include samples with a label < this value', extra={})] = None
search: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Search query', extra={})] = None
proposed_actions_job_id: Annotated[pydantic.types.StrictInt | None, FieldInfo(default=PydanticUndefined, description='Pass this parameter when querying samples from inside an AI Action job. If you pass this parameter in a multi-stage AI Action, previous proposed changes (from an earlier step) will be applied to the returned dataset.', extra={})] = None
truncate_structured_labels: Annotated[pydantic.types.StrictBool | None, FieldInfo(default=PydanticUndefined, description='If true, only a slice of labels will be returned for samples with multiple labels.', extra={})] = None
sort_by: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='If not specified, "id-desc" is used.', extra={})] = None
data_type: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Include only samples with a particular data type', extra={})] = None
min_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID >= this value', extra={})] = None
max_id: Annotated[float | None, FieldInfo(default=PydanticUndefined, description='Include only samples with an ID < this value', extra={})] = None
metadata: Annotated[pydantic.types.StrictStr | None, FieldInfo(default=PydanticUndefined, description='Filter samples by metadata key-value pairs, provided as a JSON string. Each filter item in the list is combined using a logical OR. To include samples without any metadata, use: { "no_metadata": true }. ', extra={})] = None
min_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that where added after the date given', extra={})] = None
max_date: Annotated[datetime.datetime | None, FieldInfo(default=PydanticUndefined, description='Only include samples that were added before the date given', extra={})] = None
**kwargs
Return
edgeimpulse_api.models.list_samples_response.ListSamplesResponse
move_sample
edgeimpulse_api.api.raw_data_api.move_sample(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
move_raw_data_request: edgeimpulse_api.models.move_raw_data_request.MoveRawDataRequest,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseMove sample
Move a sample to another category (e.g. from test to training).
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
move_raw_data_request: edgeimpulse_api.models.move_raw_data_request.MoveRawDataRequest
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
move_to_labeling_queue
edgeimpulse_api.api.raw_data_api.move_to_labeling_queue(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseMove sample to labeling queue
Clears the bounding box labels and moves item back to labeling queue
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
rebalance_dataset
edgeimpulse_api.api.raw_data_api.rebalance_dataset(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.rebalance_dataset_response.RebalanceDatasetResponseRebalance dataset
This API is deprecated, use rebalanceDatasetV2 instead (/v1/api/{projectId}/classify/v2/{sampleId}). Rebalances the dataset over training / testing categories. This resets the category for all data and splits it 80%/20% between training and testing. This is a deterministic process based on the hash of the name of the data.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.rebalance_dataset_response.RebalanceDatasetResponse
rebalance_dataset_v2
edgeimpulse_api.api.raw_data_api.rebalance_dataset_v2(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200ResponseRebalance dataset
Rebalances the dataset over training / testing categories. This resets the category for all data and splits it 80%/20% between training and testing. This is a deterministic process based on the hash of the name of the data. Returns immediately on small datasets, or starts a job on larger datasets. To get the dataset ratio (as returned by the v1 endpoint), use getDatasetRatio.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200Response
rename_sample
edgeimpulse_api.api.raw_data_api.rename_sample(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
rename_sample_request: edgeimpulse_api.models.rename_sample_request.RenameSampleRequest,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseRename sample
Sets the file name of the sample. This name does not need to be unique, but it's highly recommended to do so.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
rename_sample_request: edgeimpulse_api.models.rename_sample_request.RenameSampleRequest
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
retry_processing
edgeimpulse_api.api.raw_data_api.retry_processing(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseRetry processing
If a sample failed processing, retry the processing operation.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
segment_sample
edgeimpulse_api.api.raw_data_api.segment_sample(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
segment_sample_request: edgeimpulse_api.models.segment_sample_request.SegmentSampleRequest,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseSegment sample
Slice a sample into multiple segments. The original file will be marked as deleted, but you can crop any created segment to retrieve the original file.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
segment_sample_request: edgeimpulse_api.models.segment_sample_request.SegmentSampleRequest
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
set_data_explorer_settings
edgeimpulse_api.api.raw_data_api.set_data_explorer_settings(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
data_explorer_settings: edgeimpulse_api.models.data_explorer_settings.DataExplorerSettings,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseSet data explorer settings
Set data explorer configuration, like the type of data, and the input / dsp block to use.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
data_explorer_settings: edgeimpulse_api.models.data_explorer_settings.DataExplorerSettings
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
set_sample_bounding_boxes
edgeimpulse_api.api.raw_data_api.set_sample_bounding_boxes(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
sample_bounding_boxes_request: edgeimpulse_api.models.sample_bounding_boxes_request.SampleBoundingBoxesRequest,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseSet bounding boxes
Set the bounding boxes for a sample
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
sample_bounding_boxes_request: edgeimpulse_api.models.sample_bounding_boxes_request.SampleBoundingBoxesRequest
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
set_sample_metadata
edgeimpulse_api.api.raw_data_api.set_sample_metadata(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
set_sample_metadata_request: edgeimpulse_api.models.set_sample_metadata_request.SetSampleMetadataRequest,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseSet sample metadata
Adds or updates the metadata associated to a sample.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
set_sample_metadata_request: edgeimpulse_api.models.set_sample_metadata_request.SetSampleMetadataRequest
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
set_sample_proposed_changes
edgeimpulse_api.api.raw_data_api.set_sample_proposed_changes(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
set_sample_proposed_changes_request: edgeimpulse_api.models.set_sample_proposed_changes_request.SetSampleProposedChangesRequest,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponsePropose changes
Queue up changes to an object as part of the AI Actions flow. This overwrites any previous proposed changes.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
set_sample_proposed_changes_request: edgeimpulse_api.models.set_sample_proposed_changes_request.SetSampleProposedChangesRequest
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
set_sample_structured_labels
edgeimpulse_api.api.raw_data_api.set_sample_structured_labels(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
set_sample_structured_labels_request: edgeimpulse_api.models.set_sample_structured_labels_request.SetSampleStructuredLabelsRequest,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseUpdate structured labels
Set structured labels for a sample. If a sample has structured labels the label column is ignored, and the sample is allowed to have multiple labels. An array of { startIndex, endIndex, label } needs to be passed in with labels for the complete sample (see valuesCount to get the upper bound). endIndex is inclusive. If you pass in an incorrect array (e.g. missing values) you'll get an error back.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
set_sample_structured_labels_request: edgeimpulse_api.models.set_sample_structured_labels_request.SetSampleStructuredLabelsRequest
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
set_sample_video_dimensions
edgeimpulse_api.api.raw_data_api.set_sample_video_dimensions(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
set_sample_video_dimensions_request: edgeimpulse_api.models.set_sample_video_dimensions_request.SetSampleVideoDimensionsRequest,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseSet sample video dimensions
Update the video dimensions for a sample. This is only available for video files that do not have dimensions set yet.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
set_sample_video_dimensions_request: edgeimpulse_api.models.set_sample_video_dimensions_request.SetSampleVideoDimensionsRequest
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
split_sample_in_frames
edgeimpulse_api.api.raw_data_api.split_sample_in_frames(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})],
split_sample_in_frames_request: edgeimpulse_api.models.split_sample_in_frames_request.SplitSampleInFramesRequest,
**kwargs
) ‑> edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200ResponseSplit sample into frames
Split a video sample into individual frames. Depending on the length of the video sample this will either execute immediately or return the ID of a job that will perform this action.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
sample_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Sample ID', extra={})]
split_sample_in_frames_request: edgeimpulse_api.models.split_sample_in_frames_request.SplitSampleInFramesRequest
**kwargs
Return
edgeimpulse_api.models.rebalance_dataset_v2200_response.RebalanceDatasetV2200Response
store_segment_length
edgeimpulse_api.api.raw_data_api.store_segment_length(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
store_segment_length_request: edgeimpulse_api.models.store_segment_length_request.StoreSegmentLengthRequest,
**kwargs
) ‑> edgeimpulse_api.models.generic_api_response.GenericApiResponseStore the last segment length
When segmenting a sample into smaller segments, store the segment length to ensure uniform segment lengths.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
store_segment_length_request: edgeimpulse_api.models.store_segment_length_request.StoreSegmentLengthRequest
**kwargs
Return
edgeimpulse_api.models.generic_api_response.GenericApiResponse
track_objects
edgeimpulse_api.api.raw_data_api.track_objects(
self,
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})],
track_objects_request: edgeimpulse_api.models.track_objects_request.TrackObjectsRequest,
**kwargs
) ‑> edgeimpulse_api.models.track_objects_response.TrackObjectsResponseTrack objects
Track objects between two samples. Source sample should have bounding boxes set.
Parameters
self
project_id: Annotated[pydantic.types.StrictInt, FieldInfo(default=Ellipsis, description='Project ID', extra={})]
track_objects_request: edgeimpulse_api.models.track_objects_request.TrackObjectsRequest
**kwargs
Return
edgeimpulse_api.models.track_objects_response.TrackObjectsResponse
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