interpretability with cats and dogs

[rijobro]

I was unsure of our implementations of GradCAM and occlusion sensitivity, so I tested on a binary dog/cat classification task.

I think these results are easier to understand than our other interpretability notebooks:

Requires PR Project-MONAI/MONAI#3543.

Status

Ready

Checks

• Notebook runs automatically ./runner [-p <regex_pattern>]

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[wyli]

perhaps exclude this file from the testing pipelines because the dataset is not automatically available

tutorials/runner.sh

Lines 61 to 66 in 1608664

	pattern="-and -name '*' -and ! -wholename '*federated_learning*'\
	-and ! -wholename '*transchex_openi*'\
	-and ! -wholename '*unetr_btcv*'\
	-and ! -wholename '*profiling_camelyon*'\
	-and ! -wholename '*profiling_train_base_nvtx*'\
	-and ! -wholename '*benchmark_global_mutual_information*'"

[rijobro]

@wyli , thanks done!