我正在编写一个程序来训练一个小天鹅网，将灰度图像着色为CIELab图像。以下是我的代码：
with open('mypicklegrey.pickle','rb') as fgrey:
X_train = pickle.load(fgrey)
print ('data_grey')
with open('mypicklelab.pickle','rb') as flab:
Y_train = pickle.load(flab)
print ('data_lab')
net1 = NeuralNet(
layers=[('input', layers.InputLayer),
('conv2d1', layers.Conv2DLayer),
('maxpool1', layers.MaxPool2DLayer),
('conv2d2', layers.Conv2DLayer),
('maxpool2', layers.MaxPool2DLayer),
('dropout1', layers.DropoutLayer),
('dense', layers.DenseLayer),
('dropout2', layers.DropoutLayer),
('output', layers.DenseLayer),
],
# input layer
input_shape=(None, 1, 224,224),
# layer conv2d1
conv2d1_num_filters=32,
conv2d1_filter_size=(3, 3),
conv2d1_nonlinearity=lasagne.nonlinearities.rectify,
conv2d1_W=lasagne.init.GlorotUniform(),
# layer maxpool1
maxpool1_pool_size=(2, 2),
# layer conv2d2
conv2d2_num_filters=32,
conv2d2_filter_size=(3, 3),
conv2d2_nonlinearity=lasagne.nonlinearities.rectify,
# layer maxpool2
maxpool2_pool_size=(2, 2),
# dropout1
dropout1_p=0.5,
# dense
dense_num_units=256,
dense_nonlinearity=lasagne.nonlinearities.rectify,
# dropout2
dropout2_p=0.5,
# output
output_nonlinearity=lasagne.nonlinearities.softmax,
output_num_units=10,
# optimization method params
update=nesterov_momentum,
update_learning_rate=0.01,
update_momentum=0.9,
max_epochs=10,
verbose=1,
)
以上代码运行正常，但我在训练网时遇到错误。
nn = net1.fit(X_train, Y_train)
ERROR ------------第350行，在_check_good_input-＆gt; x_len = len（X） TypeError：类型为＆＃39; Image＆＃39;的对象没有len（）
我是编程神经网络的新手，并没有真正得到这个错误的原因究竟是什么，在这一点上被卡住了。任何帮助深表感谢。提前谢谢！