def _get_dataset(self):
dic = {}
dic["file_path"] = "%s" % self.hyper["file_path"]
dic["label_size"] = 1
dic["class_nums"] = 10
if self.hyper["dataset"] == "mnist":
dic["img_size"] = 28 * 28
dataset = mnist_dataset.MnistSet(dic)
if self.hyper["dataset"] == "cifar10":
dic["img_size"] = 32 * 32 * 3
dataset = cifar10_dataset.Cifar10Set(dic)
return dataset
def test_cifar10_test_set():
dic = get_cifar10_dic()
batch_size = 100
dataset = cifar10_dataset.Cifar10Set(dic)
data_generator = dataset.get_test_data_generator(batch_size)
count = 1
while True:
batch_img, batch_labels, status = dataset.get_a_batch_data(
data_generator)
print("count:%s status:%s " % (count, status))
if not status:
break
count += 1
def test_cifar10_test_set():
file_path = "./data/"
batch_size = 100
dataset = cifar10_dataset.Cifar10Set(file_path)
data_generator = dataset.get_test_data_generator(batch_size)
count = 1
while True:
batch_img, batch_labels, status = dataset.get_a_batch_data(data_generator)
print("count:%s status:%s " % (count, status))
if not status:
break
count += 1
print(str(batch_labels))
def _get_dataset(self):
dataset = cifar10_dataset.Cifar10Set(self.hyper["file_path"])
return dataset
def test_generator_cifar10_train_images():
dic = get_cifar10_dic()
train_img_path = "./cifar10_img/train/"
dataset = cifar10_dataset.Cifar10Set(dic)
dataset.generator_train_images(train_img_path)
def test_generator_test_images():
file_path = "./data/"
test_img_path = "./img/test/"
dataset = cifar10_dataset.Cifar10Set(file_path)
dataset.generator_test_images(test_img_path)