Built-in Types

ProjectMetadata

Project metadata.

Bases

dataclass

Field	Type	Description
name	`str`	The name of the project, for example: `"My Cool Project"`

TagMetadata

Tag metadata.

Bases

dataclass

Field	Type	Description
name	`str`	The name of the tag
color	`str`	The color code of the tag, for example: `"#73aaff"`
description	`str`	The description of the tag.

Pagination

Pagination parameters.

Bases

dataclass

Field	Type	Description
page	`str`	A string that represents the page of results
limit	`int`	A limit on the number of objects to be returned, the Limit can range between 1 and 100, and the default is 100

AssetFilter

Asset list filter.

Bases

dataclass

Field	Type	Description
groups	`List[str]`	The filter groups.
filename	`str`	The query filename.
status	`str`	The status of the asset, enum: [`Annotated`, `Review`, `Completed`, `Tofix`, `None`]
metadata_query	`str`	The metadata query string. Please refer Here.

AssetMetadata

Asset Metadata.

📘
The custom metadata size that can be attached depends on your price plan. Please reference here for more information!

Bases

dataclass

Field	Type	Description
status	`str`	The status of the asset, enum: [`Annotated`, `Review`, `Completed`, `Tofix`, `None`]
custom_metadata	`dict`	This metadata dictionary should contain the metadata information you want to preserve or add for use on the Nexus platform.

AnnotationFilter

Annotation list filter.

Bases

dataclass

Field	Type	Description
asset_ids	`List[str]`	The list of asset ids.

AnnotationMetadata

Annotation metadata.

Bases

dataclass

Field	Type	Description
asset_id	`str`	The id of the asset, example: `"asset_9f61bab8-ec60-476f-a1cf-63eca5c313dd"`
tag	`str`	The name of the tag
bound_type	`str`	The bound type of the annotation, Enum: [`Polygon`, `Rectangle`,`Classification`,`Keypoints`]
bound	`list`	The bound of the annotation, example: `[[0.0325, 0.8436],[0.0325, 0.9094],[0.1275, 0.9094],[0.1275, 0.8431]]`

AnnotationExportOptions

Annotation export options.

Bases

dataclass

Field	Type	Description
split_ratio	`int`	The ratio used to split the data into training and validation sets
seed	`int`	The number used to initialize a pseudorandom number generator
normalized	`bool`	The boolean indication on whether the exported annotations should be shuffled

AnnotationExportMetadata

Annotation Export Metadata.

Bases

dataclass

Field	Type	Description
format	AnnotationExportFormat	The format to export the annotations.
options	AnnotationExportOptions	The options to export the annotations

AssetMetadata

Asset Metadata.

📘
The custom metadata size that can be attached depends on your price plan. Please reference here for more information!

Bases

dataclass

Field	Type	Description
status	`str`	The status of the asset, enum: [`Annotated`, `Review`, `Completed`, `Tofix`, `None`]
custom_metadata	`dict`	This metadata dictionary should contain the metadata information you want to preserve or add for use on the Nexus platform.

AnnotationExportFormat

Annotation export formats.

Bases

Enum

Type	Description
`str`	The format of the annotation. Classification: [`csv_classification`, `classification_tfrecord`] Bounding Box: [`csv_fourcorner`, `csv_widthheight`, `coco`, `pascal_voc`, `yolo_keras_pytorch`, `yolo_darknet`, `createml`, `tfrecord`] Segmentation: [`polygon_single`, `polygon_coco`] Keypoint: [`keypoints_coco`]

FlowMetadata

Workflow Metadata.

Bases

dataclass

Field	Type	Description
title	`str`	The title of the Workflow, for example: `"New workflow title"`

RunSetupMetadata

Training settings.

Bases

dataclass

Field	Type	Description
accelerator	Accelerator	The hardware accelerator to use for the training run
checkpoint	Checkpoint	The checkpoint strategy name for the training run.
limit	Limit	The limit configuration for the training
preview	`bool`	A boolean value indicating whether to enable preview for the training
matrix	`bool`	A boolean value indicating whether to enable the matrix for the training

Accelerator

Run Accelerator Metadata.

Bases

dataclass

Field	Type	Description
name	`str`	The GPU type to use for the training run, enum: [`GPU_T4`, `GPU_L4`,`GPU_P100`,`GPU_V100`,`GPU_A100_40GB`]
count	`int`	The number of GPUs to use for the training run

Checkpoint

Run Checkpoint Metadata.

Bases

dataclass

Field	Type	Description
strategy	`str`	The checkpointing strategy name for the training, enum: [ `STRAT_EVERY_N_EPOCH`, `STRAT_ALWAYS_SAVE_LATEST`, `STRAT_LOWEST_VALIDATION_LOSS`, `STRAT_HIGHEST_ACCURACY`]
metric	`str`	The checkpointing metric for the training, enum: [`Loss/total_loss`, `Loss/regularization_loss`, `Loss/localization_loss`, `Loss/classification_loss`, `DetectionBoxes_Precision/mAP`, `DetectionBoxes_Precision/[email protected]`, `DetectionBoxes_Precision/mAP (small)`, `DetectionBoxes_Precision/mAP (medium)`, `DetectionBoxes_Precision/mAP (large)`, `DetectionBoxes_Recall/AR@1`, `DetectionBoxes_Recall/AR@10`, `DetectionBoxes_Recall/AR@100`, `DetectionBoxes_Recall/AR@100 (small)`, `DetectionBoxes_Recall/AR@100 (medium)`, `DetectionBoxes_Recall/AR@100 (large)`]
evaluation_interval	`int`	The checkpoint evaluation interval value for the training

Limit

Run Limit Metadata.

Bases

dataclass

Field	Type	Description
metric	`str`	The limit metric for the training, enum: [`LIM_MINUTE`, `LIM_EPOCH`, `LIM_NONE`]
value	`int`	The limit metric value for the training

ArtifactFilters

Artifact filters data class.

Bases

dataclass

Field	Type	Description
run_ids	`List[str]`	The list of run ids.

ArtifactExportMetadata

Artifact exporting settings.

Bases

dataclass

Field	Type	Description
format	`str`	The format of the artifact exports, enum: [`ONNX`, `TensorFlow`, `PyTorch`, `TFLite`]
quantization	`str`	The quantization of the artifact exports, optional.

DeploymentMetadata

Deployment settings.

Bases

dataclass

Field	Type	Description
name	`str`	The name of the inference API instance
artifact_id	`int`	The unique identifier of the artifact to deploy
num_of_instances	`int`	The number of the inference API instances to deploy
version_tag	`str`	The current version tag of the inference instance.
resources	DeploymentResources	The resource allocation for the deployment instance, optional.
options	DeploymentOptions	The configuration options for the deployment instance, optional.

DeploymentResources

The resource allocation for the deployment instance, optional.

Bases

dataclass

Field	Type	Description
GPU_T4	`int`	The number of NVIDIA Tesla T4 GPUs to allocate to each Inference API instance, optional.

DeploymentOptions

The configuration options for creating each deployment API instance, optional.

Bases

dataclass

Field	Type	Description
evaluation_strategy	`str`	The evaluation strategy to use of each Inference API, default `entropy_score`.
evaluation_threshold	`int`	The evaluation threshold to use to trigger post-evaluation actions, default `0.5`.
evaluation_group	`str`	The asset group to which assets triggered by the active learning route will be uploaded, is a comma-separated list.