Module monk.tf_keras_1.transforms.return_transform
Expand source code
from tf_keras_1.transforms.imports import *
from system.imports import *
def set_transform_estimate(system_dict):
'''
Load training and validation transforms in main state
Args:
system_dict (dict): System dictionary storing experiment state and set variables
Returns:
dict: updated system dict
'''
if(system_dict["local"]["transforms_train"]["featurewise_center"]):
rescale_train = 1/256;
else:
rescale_train = 0;
if(system_dict["local"]["transforms_val"]["featurewise_center"]):
rescale_val = 1/256;
else:
rescale_val = 0;
system_dict["local"]["data_generators"]["estimate"] = keras.preprocessing.image.ImageDataGenerator(
featurewise_center=system_dict["local"]["transforms_train"]["featurewise_center"],
featurewise_std_normalization=system_dict["local"]["transforms_train"]["featurewise_std_normalization"],
rotation_range=system_dict["local"]["transforms_train"]["rotation_range"],
width_shift_range=system_dict["local"]["transforms_train"]["width_shift_range"],
height_shift_range=system_dict["local"]["transforms_train"]["height_shift_range"],
shear_range=system_dict["local"]["transforms_train"]["shear_range"],
zoom_range=system_dict["local"]["transforms_train"]["zoom_range"],
brightness_range=system_dict["local"]["transforms_train"]["brightness_range"],
horizontal_flip=system_dict["local"]["transforms_train"]["horizontal_flip"],
vertical_flip=system_dict["local"]["transforms_train"]["vertical_flip"],
validation_split=0.9,
rescale=0
);
if(system_dict["local"]["transforms_train"]["featurewise_center"]):
system_dict["local"]["data_generators"]["estimate"].mean = system_dict["local"]["transforms_train"]["mean"];
if(system_dict["local"]["transforms_train"]["featurewise_std_normalization"]):
system_dict["local"]["data_generators"]["estimate"].std = system_dict["local"]["transforms_train"]["std"];
return system_dict;
def set_transform_trainval(system_dict):
'''
Load testing transforms in main state
Args:
system_dict (dict): System dictionary storing experiment state and set variables
Returns:
dict: updated system dict
'''
if("train-val" in system_dict["dataset"]["dataset_type"]):
if(system_dict["local"]["transforms_train"]["featurewise_center"]):
rescale_train = 1/256;
else:
rescale_train = 0;
if(system_dict["local"]["transforms_val"]["featurewise_center"]):
rescale_val = 1/256;
else:
rescale_val = 0;
system_dict["local"]["data_generators"]["train"] = keras.preprocessing.image.ImageDataGenerator(
featurewise_center=system_dict["local"]["transforms_train"]["featurewise_center"],
featurewise_std_normalization=system_dict["local"]["transforms_train"]["featurewise_std_normalization"],
rotation_range=system_dict["local"]["transforms_train"]["rotation_range"],
width_shift_range=system_dict["local"]["transforms_train"]["width_shift_range"],
height_shift_range=system_dict["local"]["transforms_train"]["height_shift_range"],
shear_range=system_dict["local"]["transforms_train"]["shear_range"],
zoom_range=system_dict["local"]["transforms_train"]["zoom_range"],
brightness_range=system_dict["local"]["transforms_train"]["brightness_range"],
horizontal_flip=system_dict["local"]["transforms_train"]["horizontal_flip"],
vertical_flip=system_dict["local"]["transforms_train"]["vertical_flip"],
rescale = 0
);
system_dict["local"]["data_generators"]["val"] = keras.preprocessing.image.ImageDataGenerator(
featurewise_center=system_dict["local"]["transforms_val"]["featurewise_center"],
featurewise_std_normalization=system_dict["local"]["transforms_val"]["featurewise_std_normalization"],
rotation_range=system_dict["local"]["transforms_val"]["rotation_range"],
width_shift_range=system_dict["local"]["transforms_val"]["width_shift_range"],
height_shift_range=system_dict["local"]["transforms_val"]["height_shift_range"],
shear_range=system_dict["local"]["transforms_val"]["shear_range"],
zoom_range=system_dict["local"]["transforms_val"]["zoom_range"],
brightness_range=system_dict["local"]["transforms_val"]["brightness_range"],
horizontal_flip=system_dict["local"]["transforms_val"]["horizontal_flip"],
vertical_flip=system_dict["local"]["transforms_val"]["vertical_flip"],
rescale = 0
);
if(system_dict["local"]["transforms_train"]["featurewise_center"]):
system_dict["local"]["data_generators"]["train"].mean = system_dict["local"]["transforms_train"]["mean"];
if(system_dict["local"]["transforms_val"]["featurewise_center"]):
system_dict["local"]["data_generators"]["val"].mean = system_dict["local"]["transforms_val"]["mean"];
if(system_dict["local"]["transforms_train"]["featurewise_std_normalization"]):
system_dict["local"]["data_generators"]["train"].std = system_dict["local"]["transforms_train"]["std"];
if(system_dict["local"]["transforms_val"]["featurewise_std_normalization"]):
system_dict["local"]["data_generators"]["val"].std = system_dict["local"]["transforms_val"]["std"];
else:
if(system_dict["local"]["transforms_train"]["featurewise_center"]):
rescale_train = 1/256;
else:
rescale_train = 0;
system_dict["local"]["data_generators"]["train"] = keras.preprocessing.image.ImageDataGenerator(
featurewise_center=system_dict["local"]["transforms_train"]["featurewise_center"],
featurewise_std_normalization=system_dict["local"]["transforms_train"]["featurewise_std_normalization"],
rotation_range=system_dict["local"]["transforms_train"]["rotation_range"],
width_shift_range=system_dict["local"]["transforms_train"]["width_shift_range"],
height_shift_range=system_dict["local"]["transforms_train"]["height_shift_range"],
shear_range=system_dict["local"]["transforms_train"]["shear_range"],
zoom_range=system_dict["local"]["transforms_train"]["zoom_range"],
brightness_range=system_dict["local"]["transforms_train"]["brightness_range"],
horizontal_flip=system_dict["local"]["transforms_train"]["horizontal_flip"],
vertical_flip=system_dict["local"]["transforms_train"]["vertical_flip"],
validation_split=1-system_dict["dataset"]["params"]["train_val_split"],
rescale = 0
);
if(system_dict["local"]["transforms_train"]["featurewise_center"]):
system_dict["local"]["data_generators"]["train"].mean = system_dict["local"]["transforms_train"]["mean"];
if(system_dict["local"]["transforms_train"]["featurewise_std_normalization"]):
system_dict["local"]["data_generators"]["train"].std = system_dict["local"]["transforms_train"]["std"];
return system_dict;
def set_transform_test(system_dict):
if(system_dict["local"]["transforms_test"]["featurewise_center"]):
rescale_val = 1/256;
else:
rescale_val = 0;
system_dict["local"]["data_generators"]["test"] = keras.preprocessing.image.ImageDataGenerator(
featurewise_center=system_dict["local"]["transforms_test"]["featurewise_center"],
featurewise_std_normalization=system_dict["local"]["transforms_test"]["featurewise_std_normalization"],
rotation_range=system_dict["local"]["transforms_test"]["rotation_range"],
width_shift_range=system_dict["local"]["transforms_test"]["width_shift_range"],
height_shift_range=system_dict["local"]["transforms_test"]["height_shift_range"],
shear_range=system_dict["local"]["transforms_test"]["shear_range"],
zoom_range=system_dict["local"]["transforms_test"]["zoom_range"],
brightness_range=system_dict["local"]["transforms_test"]["brightness_range"],
horizontal_flip=system_dict["local"]["transforms_test"]["horizontal_flip"],
vertical_flip=system_dict["local"]["transforms_test"]["vertical_flip"],
rescale = 0
);
if(system_dict["local"]["transforms_test"]["featurewise_center"]):
system_dict["local"]["data_generators"]["test"].mean = system_dict["local"]["transforms_test"]["mean"];
if(system_dict["local"]["transforms_test"]["featurewise_std_normalization"]):
system_dict["local"]["data_generators"]["test"].std = system_dict["local"]["transforms_test"]["std"];
return system_dict;
Functions
def set_transform_estimate(system_dict)
-
Load training and validation transforms in main state
Args
system_dict
:dict
- System dictionary storing experiment state and set variables
Returns
dict
- updated system dict
Expand source code
def set_transform_estimate(system_dict): ''' Load training and validation transforms in main state Args: system_dict (dict): System dictionary storing experiment state and set variables Returns: dict: updated system dict ''' if(system_dict["local"]["transforms_train"]["featurewise_center"]): rescale_train = 1/256; else: rescale_train = 0; if(system_dict["local"]["transforms_val"]["featurewise_center"]): rescale_val = 1/256; else: rescale_val = 0; system_dict["local"]["data_generators"]["estimate"] = keras.preprocessing.image.ImageDataGenerator( featurewise_center=system_dict["local"]["transforms_train"]["featurewise_center"], featurewise_std_normalization=system_dict["local"]["transforms_train"]["featurewise_std_normalization"], rotation_range=system_dict["local"]["transforms_train"]["rotation_range"], width_shift_range=system_dict["local"]["transforms_train"]["width_shift_range"], height_shift_range=system_dict["local"]["transforms_train"]["height_shift_range"], shear_range=system_dict["local"]["transforms_train"]["shear_range"], zoom_range=system_dict["local"]["transforms_train"]["zoom_range"], brightness_range=system_dict["local"]["transforms_train"]["brightness_range"], horizontal_flip=system_dict["local"]["transforms_train"]["horizontal_flip"], vertical_flip=system_dict["local"]["transforms_train"]["vertical_flip"], validation_split=0.9, rescale=0 ); if(system_dict["local"]["transforms_train"]["featurewise_center"]): system_dict["local"]["data_generators"]["estimate"].mean = system_dict["local"]["transforms_train"]["mean"]; if(system_dict["local"]["transforms_train"]["featurewise_std_normalization"]): system_dict["local"]["data_generators"]["estimate"].std = system_dict["local"]["transforms_train"]["std"]; return system_dict;
def set_transform_test(system_dict)
-
Expand source code
def set_transform_test(system_dict): if(system_dict["local"]["transforms_test"]["featurewise_center"]): rescale_val = 1/256; else: rescale_val = 0; system_dict["local"]["data_generators"]["test"] = keras.preprocessing.image.ImageDataGenerator( featurewise_center=system_dict["local"]["transforms_test"]["featurewise_center"], featurewise_std_normalization=system_dict["local"]["transforms_test"]["featurewise_std_normalization"], rotation_range=system_dict["local"]["transforms_test"]["rotation_range"], width_shift_range=system_dict["local"]["transforms_test"]["width_shift_range"], height_shift_range=system_dict["local"]["transforms_test"]["height_shift_range"], shear_range=system_dict["local"]["transforms_test"]["shear_range"], zoom_range=system_dict["local"]["transforms_test"]["zoom_range"], brightness_range=system_dict["local"]["transforms_test"]["brightness_range"], horizontal_flip=system_dict["local"]["transforms_test"]["horizontal_flip"], vertical_flip=system_dict["local"]["transforms_test"]["vertical_flip"], rescale = 0 ); if(system_dict["local"]["transforms_test"]["featurewise_center"]): system_dict["local"]["data_generators"]["test"].mean = system_dict["local"]["transforms_test"]["mean"]; if(system_dict["local"]["transforms_test"]["featurewise_std_normalization"]): system_dict["local"]["data_generators"]["test"].std = system_dict["local"]["transforms_test"]["std"]; return system_dict;
def set_transform_trainval(system_dict)
-
Load testing transforms in main state
Args
system_dict
:dict
- System dictionary storing experiment state and set variables
Returns
dict
- updated system dict
Expand source code
def set_transform_trainval(system_dict): ''' Load testing transforms in main state Args: system_dict (dict): System dictionary storing experiment state and set variables Returns: dict: updated system dict ''' if("train-val" in system_dict["dataset"]["dataset_type"]): if(system_dict["local"]["transforms_train"]["featurewise_center"]): rescale_train = 1/256; else: rescale_train = 0; if(system_dict["local"]["transforms_val"]["featurewise_center"]): rescale_val = 1/256; else: rescale_val = 0; system_dict["local"]["data_generators"]["train"] = keras.preprocessing.image.ImageDataGenerator( featurewise_center=system_dict["local"]["transforms_train"]["featurewise_center"], featurewise_std_normalization=system_dict["local"]["transforms_train"]["featurewise_std_normalization"], rotation_range=system_dict["local"]["transforms_train"]["rotation_range"], width_shift_range=system_dict["local"]["transforms_train"]["width_shift_range"], height_shift_range=system_dict["local"]["transforms_train"]["height_shift_range"], shear_range=system_dict["local"]["transforms_train"]["shear_range"], zoom_range=system_dict["local"]["transforms_train"]["zoom_range"], brightness_range=system_dict["local"]["transforms_train"]["brightness_range"], horizontal_flip=system_dict["local"]["transforms_train"]["horizontal_flip"], vertical_flip=system_dict["local"]["transforms_train"]["vertical_flip"], rescale = 0 ); system_dict["local"]["data_generators"]["val"] = keras.preprocessing.image.ImageDataGenerator( featurewise_center=system_dict["local"]["transforms_val"]["featurewise_center"], featurewise_std_normalization=system_dict["local"]["transforms_val"]["featurewise_std_normalization"], rotation_range=system_dict["local"]["transforms_val"]["rotation_range"], width_shift_range=system_dict["local"]["transforms_val"]["width_shift_range"], height_shift_range=system_dict["local"]["transforms_val"]["height_shift_range"], shear_range=system_dict["local"]["transforms_val"]["shear_range"], zoom_range=system_dict["local"]["transforms_val"]["zoom_range"], brightness_range=system_dict["local"]["transforms_val"]["brightness_range"], horizontal_flip=system_dict["local"]["transforms_val"]["horizontal_flip"], vertical_flip=system_dict["local"]["transforms_val"]["vertical_flip"], rescale = 0 ); if(system_dict["local"]["transforms_train"]["featurewise_center"]): system_dict["local"]["data_generators"]["train"].mean = system_dict["local"]["transforms_train"]["mean"]; if(system_dict["local"]["transforms_val"]["featurewise_center"]): system_dict["local"]["data_generators"]["val"].mean = system_dict["local"]["transforms_val"]["mean"]; if(system_dict["local"]["transforms_train"]["featurewise_std_normalization"]): system_dict["local"]["data_generators"]["train"].std = system_dict["local"]["transforms_train"]["std"]; if(system_dict["local"]["transforms_val"]["featurewise_std_normalization"]): system_dict["local"]["data_generators"]["val"].std = system_dict["local"]["transforms_val"]["std"]; else: if(system_dict["local"]["transforms_train"]["featurewise_center"]): rescale_train = 1/256; else: rescale_train = 0; system_dict["local"]["data_generators"]["train"] = keras.preprocessing.image.ImageDataGenerator( featurewise_center=system_dict["local"]["transforms_train"]["featurewise_center"], featurewise_std_normalization=system_dict["local"]["transforms_train"]["featurewise_std_normalization"], rotation_range=system_dict["local"]["transforms_train"]["rotation_range"], width_shift_range=system_dict["local"]["transforms_train"]["width_shift_range"], height_shift_range=system_dict["local"]["transforms_train"]["height_shift_range"], shear_range=system_dict["local"]["transforms_train"]["shear_range"], zoom_range=system_dict["local"]["transforms_train"]["zoom_range"], brightness_range=system_dict["local"]["transforms_train"]["brightness_range"], horizontal_flip=system_dict["local"]["transforms_train"]["horizontal_flip"], vertical_flip=system_dict["local"]["transforms_train"]["vertical_flip"], validation_split=1-system_dict["dataset"]["params"]["train_val_split"], rescale = 0 ); if(system_dict["local"]["transforms_train"]["featurewise_center"]): system_dict["local"]["data_generators"]["train"].mean = system_dict["local"]["transforms_train"]["mean"]; if(system_dict["local"]["transforms_train"]["featurewise_std_normalization"]): system_dict["local"]["data_generators"]["train"].std = system_dict["local"]["transforms_train"]["std"]; return system_dict;