def next_batch_test():
train = DataSet('UCF', 'train1', 25)
images, labels = train.next_batch(500)
# print(tmp.shape)
arr = []
for i in range(2):
arr.append(numpy.arange(10))
#
# for i in range(10):
# numpy.random.shuffle(arr[0])
# numpy.random.shuffle(arr[1])
# print(arr)
train = DataSet('UCF', 'train1', 25)
begin_time = time.time()
images, labels = train.next_batch(2)
print(time.time() - begin_time, 's')
print(images.shape)
print(labels.shape)
print(labels[0])
plt.imshow(images[0])
plt.show()
def next_batch_test():
train = DataSet('UCF', 'train1', 25)
images, labels = train.next_batch(500)
def next_batch_test2():
train = DataSet('UCF', 'train1', 25)
# profile.run("next_batch_test2()")
# profile.run("next_batch_test()")