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()")