| from tensorflow.keras.utils import get_file | |
| import tensorflow as tf | |
| from keras_tuner import RandomSearch | |
| from keras_tuner import Objective | |
| from src.preprocessing import delete_corrupted_image | |
| from src.draw import visualize_data | |
| from src.preprocessing import get_data_augmentation | |
| from src.models import MakeHyperModel | |
| from src.config import DATASET_URL | |
| from src.config import CACHE_DIR | |
| from src.config import CACHE_SUBDIR | |
| from src.config import DATASET_PATH | |
| from src.config import IMAGE_SIZE | |
| from src.config import BATCH_SIZE | |
| from src.config import EPOCHS | |
| get_file(origin=DATASET_URL, extract=True, cache_dir=CACHE_DIR, cache_subdir=CACHE_SUBDIR) | |
| print(delete_corrupted_image(DATASET_PATH, ('Cat', 'Dog'))) | |
| train_ds = tf.keras.preprocessing.image_dataset_from_directory( | |
| DATASET_PATH, | |
| validation_split=0.2, | |
| subset='training', | |
| seed=1337, | |
| image_size=IMAGE_SIZE, | |
| batch_size=BATCH_SIZE | |
| ) | |
| val_ds = tf.keras.preprocessing.image_dataset_from_directory( | |
| DATASET_PATH, | |
| validation_split=0.2, | |
| subset='validation', | |
| seed=1337, | |
| image_size=IMAGE_SIZE, | |
| batch_size=BATCH_SIZE | |
| ) | |
| train_ds = train_ds.prefetch(buffer_size=BATCH_SIZE) | |
| val_ds = val_ds.prefetch(buffer_size=BATCH_SIZE) | |
| data_augmentation = get_data_augmentation() | |
| visualize_data(train_ds, data_augmentation=data_augmentation) | |
| hypermodel = MakeHyperModel(input_shape=IMAGE_SIZE + (3,), num_classes=2, data_augmentation=data_augmentation) | |
| tuner = RandomSearch( | |
| hypermodel, | |
| objective=Objective("val_accuracy", direction="max"), | |
| max_trials=3, | |
| executions_per_trial=2, | |
| overwrite=True, | |
| directory='tuner_model', | |
| project_name='cat-vs-dog' | |
| ) | |
| tuner.search_space_summary() | |
| tuner.search(train_ds, epochs=EPOCHS, validation_data=val_ds) | |
| tuner.get_best_hyperparameters() |