def load_data(output="label_bbox", batch_size=32, channels=1, tl_preprocess=False, model_type="resnet", seed=23): data = DataLoader('./data/cars_train', './data/cars_test', './data/devkit', batch_size=batch_size) n_classes = len(data.df_train['label'].unique()) labels = data.labels print(f'{n_classes} CLASSES, Random Chance: {1/n_classes}') train_gen = data.get_pipeline(type='train', output=output, apply_aug=True, channels=channels, tl_preprocess=tl_preprocess, model_type=model_type, seed=seed) steps_per_epoch = np.ceil(len(data.df_train) / data.batch_size) valid_gen = data.get_pipeline(type='validation', output=output, channels=channels, apply_aug=False, tl_preprocess=tl_preprocess, model_type=model_type, seed=seed) validation_steps = np.ceil(len(data.df_valid) / data.batch_size) return (labels, n_classes, train_gen, steps_per_epoch, valid_gen, validation_steps)
def data(): output = "label_bbox" channels = 3 BATCH_SIZE = 32 SEED = 23 data = DataLoader('./data/cars_train', './data/cars_test', './data/devkit', batch_size=BATCH_SIZE) train_gen = data.get_pipeline(type='train', output=output, apply_aug=True, channels=channels, seed=SEED) valid_gen = data.get_pipeline(type='validation', output=output, channels=channels, apply_aug=True, seed=SEED) return train_gen, valid_gen
from models.one_hidden_layer import Simple_NN clear_session() # Clear models from previous sessions # Constants BATCH_SIZE = 32 SEED = 23 # Initialize Pipeline data = DataLoader('./data/cars_train', './data/cars_test', './data/devkit', batch_size=BATCH_SIZE) n_classes = len(data.df_train['label'].unique()) train_gen_clf = data.get_pipeline(type='train', output='label', seed=SEED) train_gen_localize = data.get_pipeline(type='train', output='bbox', seed=SEED) train_gen_clf_localize = data.get_pipeline(type='train', seed=SEED) steps_per_epoch = tf.math.ceil(len(data.df_train) / data.batch_size) tf.cast(steps_per_epoch, tf.int16).numpy() valid_gen_clf = data.get_pipeline(type='validation', output='label', apply_aug=False, seed=SEED) valid_gen_localize = data.get_pipeline(type='validation', output='bbox', apply_aug=False, seed=SEED) valid_gen_clf_localize = data.get_pipeline(type='validation', apply_aug=False,