xavierdcruz0

@AdrianNunez OK fair enough. But how would you go about feeding that `x` into the ResNet50's input? Something like this? ``` from keras.applications.resnet50 import ResNet50 net_output = ResNet50(weights='imagenet', include_top=False)(x) ```...

Using your first construction like so (with the `...` denoting the `locnet` definition): ``` def my_net(input_shape, num_categories): data = Input(shape=input_shape, dtype='float32', name='_input') ... x = SpatialTransformer(localization_net=locnet, downsample_factor=1, return_theta=False)(data) r50 =...