eda_plugin.examples.analysers.KerasTester

class eda_plugin.examples.analysers.KerasTester(*args: Any, **kwargs: Any)

Bases: KerasWorker

__init__(*args, **kwargs)

QRunnable, so the signals are stored in a subclass.

Methods

__init__(*args, **kwargs)	QRunnable, so the signals are stored in a subclass.
extract_decision_parameter(network_output)	Return the a value of the ndarray.
post_process_output(data, network_input)	To be implemented by subclass if necessary for the specific model.
prepare_images(images)	To be implemented by subclass if necessary for the specific model.
run()	Run the model.

extract_decision_parameter(network_output: numpy.ndarray)

Return the a value of the ndarray.

post_process_output(data: numpy.ndarray, network_input)

To be implemented by subclass if necessary for the specific model.

prepare_images(images: numpy.ndarray)

To be implemented by subclass if necessary for the specific model.

run()

Run the model.

Prepare the images, infer the model, calculate the decision parameter and construct the image that will be displayed in the GUI. Preparation and postprocessing are optional and can be implemented by subclasses as necessary for the specific model. Specific implementations can be found in examples.analysers.keras