signxai.tf_signxai.methods_impl.innvestigate.applications package

Submodules

signxai.tf_signxai.methods_impl.innvestigate.applications.imagenet module

Example applications for image classifcation.

Each function returns a pretrained ImageNet model. The models are based on keras.applications models and contain additionally pretrained patterns.

The returned dictionary contains the following keys: model, in, sm_out, out, image_shape, color_coding, preprocess_f, patterns.

Function parameters:

param load_weights:

Download or access cached weights.

param load_patterns:

Download or access cached patterns.

signxai.tf_signxai.methods_impl.innvestigate.applications.imagenet.vgg16(load_weights=False, load_patterns=False)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.imagenet.vgg19(load_weights=False, load_patterns=False)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.imagenet.resnet50(load_weights=False, load_patterns=False)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.imagenet.inception_v3(load_weights=False, load_patterns=False)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.imagenet.inception_resnet_v2(load_weights=False, load_patterns=False)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.imagenet.densenet121(load_weights=False, load_patterns=False)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.imagenet.densenet169(load_weights=False, load_patterns=False)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.imagenet.densenet201(load_weights=False, load_patterns=False)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.imagenet.nasnet_large(load_weights=False, load_patterns=False)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.imagenet.nasnet_mobile(load_weights=False, load_patterns=False)[source]

signxai.tf_signxai.methods_impl.innvestigate.applications.mnist module

Example applications for image classifcation.

Each function returns a pretrained MNIST model. The models are based on https://doi.org/10.1371/journal.pone.0130140 and http://jmlr.org/papers/v17/15-618.html.

signxai.tf_signxai.methods_impl.innvestigate.applications.mnist.pretrained_plos_long_relu(input_shape, **kwargs)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.mnist.pretrained_plos_short_relu(input_shape, **kwargs)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.mnist.pretrained_plos_long_tanh(input_shape, **kwargs)[source]
signxai.tf_signxai.methods_impl.innvestigate.applications.mnist.pretrained_plos_short_tanh(input_shape, **kwargs)[source]

Module contents