【发布时间】:2019-11-19 07:14:29
【问题描述】:
我正在练习 CNN 的“英特尔图像分类”,我编写了一个函数来加载来自不同文件夹的数据。但是当我调用该函数时,我得到一个 ValueError,上面写着“太多值无法解包”。关于如何解决这个问题的任何想法?
def data_load():
datasets = ['seg_train\seg_train', 'seg_test\seg_test']
size = (150, 150)
output = []
for dataset in datasets:
directory = os.getcwd() + '/' + dataset
images = []
labels = []
for folder in os.listdir(directory):
curr_label = class_labels[folder]
for file in os.listdir(directory + '/' + folder):
img_path = directory + '/' + folder + '/' + file
curr_image = cv2.imread(img_path)
curr_image = cv2.resize(curr_image, size)
images.append(curr_image)
labels.append(curr_label)
images, labels = shuffle(images, labels)
output.append((images, labels))
return output
(X_train, y_train), (X_test, y_test) = data_load()
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-36-ec0ae2384d47> in <module>
----> 1 (X_train, y_train), (X_test, y_test) = data_load()
ValueError: too many values to unpack (expected 2)
【问题讨论】:
标签: python conv-neural-network