monai.deploy.operators.MonaiSegInferenceOperator¶

class monai.deploy.operators.MonaiSegInferenceOperator(roi_size, pre_transforms, post_transforms, model_name='', overlap=0.5, *args, **kwargs)[source]¶

Bases: monai.deploy.operators.inference_operator.InferenceOperator

This segmentation operator uses MONAI transforms and Sliding Window Inference.

This operator preforms pre-transforms on a input image, inference using a given model, and post-transforms. The segmentation image is saved as a named Image object in memory.

If specified in the post transforms, results may also be saved to disk.

Creates a instance of this class.

Parameters

roi_size (Union[Sequence[int], int]) – The tensor size used in inference.
pre_transforms (Compose) – MONAI Compose object used for pre-transforms.
post_transforms (Compose) – MONAI Compose object used for post-transforms.
model_name (str, optional) – Name of the model. Default to “” for single model app.
overlap (float) – The overlap used in sliding window inference.

Methods

`__init__`(roi_size, pre_transforms, …[, …])	Creates a instance of this class.
`add_input`(label, data_type, storage_type)
`add_output`(label, data_type, storage_type)
`compute`(op_input, op_output, context)	Infers with the input image and save the predicted image to output
`ensure_valid`()	Ensures that the operator is valid.
`post_compute`()	This method gets executed after “compute()” of an operator is called.
`post_process`(data, args, *kwargs)	Transforms the prediction results from the model(s).
`pre_compute`()	This method gets executed before compute() of an operator is called.
`pre_process`(data, args, *kwargs)	Transforms input before being used for predicting on a model.
`predict`(data, args, *kwargs)	Predicts results using the models(s) with input tensors.

Attributes

`MODEL_LOCAL_PATH`
`env`	Gives access to the environment.
`input_dataset_key`	This is the input image key name used in dictionary based MONAI pre-transforms.
`name`	Returns the name of this operator.
`op_info`	Retrieves the operator info.
`overlap`	This is the overlap used during sliding window inference
`pred_dataset_key`	This is the prediction key name used in dictionary based MONAI post-transforms.
`roi_size`	The ROI size of tensors used in prediction.
`uid`	Gives access to the UID of the operator.

__init__(roi_size, pre_transforms, post_transforms, model_name='', overlap=0.5, *args, **kwargs)[source]¶

Creates a instance of this class.

Parameters

roi_size (Union[Sequence[int], int]) – The tensor size used in inference.
pre_transforms (Compose) – MONAI Compose object used for pre-transforms.
post_transforms (Compose) – MONAI Compose object used for post-transforms.
model_name (str, optional) – Name of the model. Default to “” for single model app.
overlap (float) – The overlap used in sliding window inference.

compute(op_input, op_output, context)[source]¶

Infers with the input image and save the predicted image to output

Parameters

op_input (InputContext) – An input context for the operator.
op_output (OutputContext) – An output context for the operator.
context (ExecutionContext) – An execution context for the operator.

ensure_valid()¶

Ensures that the operator is valid.

This method needs to be executed by add_operator() and add_flow() methods in the compose() method of the application. This sets default values for the operator in the graph if necessary. (e.g., set default value for the operator’s input port, set default value for the operator’s output port, etc.)

property env: monai.deploy.core.operator.OperatorEnv¶

Gives access to the environment.

This sets a default value for the operator’s environment if not set.

Return type: OperatorEnv
Returns: An instance of OperatorEnv.

property input_dataset_key¶: This is the input image key name used in dictionary based MONAI pre-transforms.

property name: str¶

Returns the name of this operator.

Return type: str

property op_info: monai.deploy.core.operator_info.OperatorInfo¶

Retrieves the operator info.

Args:

Return type: OperatorInfo
Returns: An instance of OperatorInfo.

property overlap¶: This is the overlap used during sliding window inference

post_compute()¶

This method gets executed after “compute()” of an operator is called.

This is a post-execution step before the operator is done doing its main action. This needs to be overridden by a base class for any meaningful action.

post_process(data, *args, **kwargs)[source]¶

Transforms the prediction results from the model(s).

This method must be overridden by a derived class. Expected return is monai.transforms.Compose.

Parameters: data (monai.transforms.Compose) – The pre-processing transforms in a Compose object.
Return type: Union[Any, Image, Tuple[Any, …], Dict[Any, Any]]
Returns: monai.transforms.Compose encapsulating post-processing transforms.
Raises: NotImplementedError – When the subclass does not override this method.

pre_compute()¶

This method gets executed before compute() of an operator is called.

This is a preperatory step before the operator executes its main job. This needs to be overridden by a base class for any meaningful action.

pre_process(data, *args, **kwargs)[source]¶

Transforms input before being used for predicting on a model.

This method must be overridden by a derived class. Expected return is monai.transforms.Compose.

Parameters: data (monai.data.ImageReader) – Reader used in LoadImage to load monai.deploy.core.Image as the input.
Return type: Union[Any, Image, Tuple[Any, …], Dict[Any, Any]]
Returns: monai.transforms.Compose encapsulating pre transforms
Raises: NotImplementedError – When the subclass does not override this method.

property pred_dataset_key¶: This is the prediction key name used in dictionary based MONAI post-transforms.

predict(data, *args, **kwargs)[source]¶

Predicts results using the models(s) with input tensors.

This method is currently not used in this class, instead monai.inferers.sliding_window_inference is used.

Raises: NotImplementedError – When the subclass does not override this method.
Return type: Union[Image, Any, Tuple[Any, …], Dict[Any, Any]]

property roi_size¶: The ROI size of tensors used in prediction.

property uid: uuid.UUID¶

Gives access to the UID of the operator.

Return type: UUID
Returns: UID of the operator.

monai.deploy.operators.MonaiBundleInferenceOperator monai.deploy.operators.PNGConverterOperator