c_nn.register_autosave( autosave_dir, example_count=10, nth_iteration=500, train_examples_nth_iteration=2000, print_loss_plot_every_nth_itr=print_loss_plot_every_nth_itr) c_nn.try_load_from_autosave(autosave_dir) # Train a loooong time # c_nn.train(1000000) # Do two tests: once on the facescrub dataset and once on the labeled faces dataset dp_lfw = LabeledFacesInTheWildDataProvider( min_cluster_count=1, max_cluster_count=5, target_img_size=(128, 128), min_element_count_per_cluster=2, additional_augmentor=lambda x: p.sample_with_array(x), min_images_per_class=10, use_all_classes_for_train_test_validation=True) dp_lfw.use_augmentation_for_test_data = False dp_lfw.use_augmentation_for_validation_data = False dp_lfw_crop = LabeledFacesInTheWildCropDataProvider( top_dir + '/../lfw_crop/', min_cluster_count=1, max_cluster_count=5, target_img_size=(128, 128), min_element_count_per_cluster=2, additional_augmentor=lambda x: p.sample_with_array(x), min_images_per_class=10, use_all_classes_for_train_test_validation=True) dp_lfw_crop.use_augmentation_for_test_data = False