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