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,
