ai4med.workflows.evaluators package

Bases: ai4med.workflows.evaluators.evaluator.Evaluator

The BulkEvaluator evaluates a set of data files. It can do both inference and validation.

Parameters

• data_dict_list – list of data dicts. Each dict contains an image element and a label element,

• of which are complete paths to the data files. (both) –

• model_loader – loader for loading pre-trained model file

• inferer – inferer for making inference on images

• batch_size (int) – size of batch. Images are batched for inference. Note that batch_size > 1 may not

• in all cases. Specifically (work) –

• does not currently support batch_size > 1. (ScanWindowInferer) –

• pre_transforms – transforms to be applied to image before inference

• post_transforms – transforms to be applied to result of inference

• output_writers – list of output eval_writers

• label_transforms – transforms to be applied to label

• val_metrics – list of validation metrics

• do_validation (bool) – whether or not to do validation

• output_infer_result (bool) – whether or not to write inference results to disk

• image_key_name (str) – key name for image data in data dict list

• overwrite_previous_result (bool) – whether or not to overwrite results from previous runs

• image_dtype (str) –

close()

evaluate(inputs=None)

Implements the required ‘evaluate’ method of evaluator.

Performs inference and/or validation on data samples defined in the data dict list.

Parameters

inputs – not used

Returns:

reset()

Bases: abc.ABC

abstract close()

abstract evaluate(inputs)

Evaluate the inputs to generate output :param inputs: input values to be evaluated :return: evaluation result