class DataGenerator(object):
def __init__(self, params, target_size=(228, 228)):
self.params = params
self.target_size = target_size
self.idg = ImageDataGeneratorCustom(**params)
def get_train_generator(self, batch_size):
return self.idg.flow_from_directory("./image/", batch_size=batch_size, target_size=self.target_size, shuffle=False, triplet_path="./training_data.txt")
def get_test_generator(self, batch_size):
return self.idg.flow_from_directory("./image/", batch_size=batch_size, target_size=self.target_size, shuffle=False, triplet_path="./training_data.txt")
class DataGenerator(object):
def __init__(self, params, target_size=(224, 224)):
self.params = params
self.target_size = target_size
self.idg = ImageDataGeneratorCustom(**params)
def get_train_generator(self, batch_size):
return self.idg.flow_from_directory("./dataset/",
batch_size=batch_size,
target_size=self.target_size,shuffle=False,
triplet_path = triplet_file_name
)
def get_test_generator(self, batch_size):
return self.idg.flow_from_directory("./dataset/",
batch_size=batch_size,
target_size=self.target_size, shuffle=False,
triplet_path = triplet_file_name
)
class DataGenerator(object):
def __init__(self, params, target_size=(224, 224)):
self.params = params
self.target_size = target_size
self.idg = ImageDataGeneratorCustom(**params)
def get_train_generator(self, batch_size):
return self.idg.flow_from_directory(
"/home/shared/CS341/Dataprocessing/train",
batch_size=batch_size,
target_size=self.target_size,
shuffle=False,
triplet_path='/home/shared/CS341/Dataprocessing/triplets_new.txt')
def get_test_generator(self, batch_size):
return self.idg.flow_from_directory(
"/home/shared/CS341/Dataprocessing/finaltest/train",
batch_size=batch_size,
target_size=self.target_size,
shuffle=False,
triplet_path=
'/home/shared/CS341/Dataprocessing/triplets_finaltest.txt')
def __init__(self, params, target_size=(224, 224)):
self.params = params
self.target_size = target_size
self.idg = ImageDataGeneratorCustom(**params)