Question

我对keras相当陌生。我现在正尝试在keras中包含conv3d_transpose层。我想使用它来进行图像分割。我的代码如下：

def vnet_model_new():
model = Sequential()
#build the first three convolutional layers
model.add(Conv3D(16, 5, input_shape=(56,56,56,1),padding = 'same', kernel_initializer = 'he_normal'))
model.add(PReLU(shared_axes=[1,2],name='prelu1'))
#first down sampling
model.add(Conv3D(32, 5, strides=(2,2,2), padding = 'same', kernel_initializer = 'he_normal'))
model.add(PReLU(shared_axes=[1,2],name='prelu2'))
model.add(Conv3D(32, 5, padding = 'same', kernel_initializer = 'he_normal'))
model.add(PReLU(shared_axes=[1,2],name='prelu3'))
model.add(Conv3D(32, 5, padding = 'same', kernel_initializer = 'he_normal'))
model.add(PReLU(shared_axes=[1,2],name='prelu4'))
model.add(Conv3D(32, 5, strides=(2,2,2), padding = 'same', kernel_initializer = 'he_normal'))
model.add(PReLU(shared_axes=[1,2],name='prelu5'))
model.add(Conv3D(64, 5, padding = 'same', kernel_initializer = 'he_normal'))
model.add(PReLU(shared_axes=[1,2],name='prelu6'))
model.add(Conv3D(64, 5, padding = 'same', kernel_initializer = 'he_normal'))
model.add(PReLU(shared_axes=[1,2],name='prelu7'))
model.add(InputLayer(input_tensor=tf.nn.conv3d_transpose(model.layers[7].output,5, output_shape=(28,28,28,1),strides=(2,2,2)))[0])
model.add(Conv3D(32, 5, padding = 'same', kernel_initializer = 'he_normal'))
model.add(PReLU(shared_axes=[1,2],name='prelu8'))
model.add(Conv3D(32, 5, padding = 'same', kernel_initializer = 'he_normal'))
model.add(PReLU(shared_axes=[1,2],name='prelu9'))
model.add(UpSampling3D(size=(2, 2, 2), data_format=None))



return model

如果我现在这样做：

model = vnet_model_new()

我得到了错误：

IndexError                                Traceback (most recent call last)
<ipython-input-42-d5a1c0f1067b> in <module>()
     33 
     34 #apply segmentation model
---> 35 model = vnet_model_new()
     36 model.compile(optimizer='adam', loss=dice_coef_loss, metrics=[dice_coef])
     37 model.fit(train_features, train_labels, validation_data=(test_features, test_labels), epochs=10, batch_size=50, verbose=2)

<ipython-input-42-d5a1c0f1067b> in vnet_model_new()
     18     model.add(Conv3D(64, 5, padding = 'same', kernel_initializer = 'he_normal'))
     19     model.add(PReLU(shared_axes=[1,2],name='prelu7'))
---> 20     model.add(InputLayer(input_tensor=tf.nn.conv3d_transpose(model.layers[7].output,5, output_shape=(28,28,28,1),strides=(2,2,2)))[0])
     21     model.add(Conv3D(32, 5, padding = 'same', kernel_initializer = 'he_normal'))
     22     model.add(PReLU(shared_axes=[1,2],name='prelu8'))

~\Anaconda2\lib\site-packages\tensorflow\python\ops\nn_ops.py in conv3d_transpose(value, filter, output_shape, strides, padding, data_format, name)
   1450     filter = ops.convert_to_tensor(filter, name="filter")
   1451     axis = 1 if data_format == "NCDHW" else 4
-> 1452     if not value.get_shape()[axis].is_compatible_with(filter.get_shape()[4]):
   1453       raise ValueError("input channels does not match filter's input channels, "
   1454                        "{} != {}".format(value.get_shape()[axis],

~\Anaconda2\lib\site-packages\tensorflow\python\framework\tensor_shape.py in __getitem__(self, key)
    522         return TensorShape(self._dims[key])
    523       else:
--> 524         return self._dims[key]
    525     else:
    526       if isinstance(key, slice):

IndexError: list index out of range

我在做什么错？提前致谢！埃拉

错误包括keras中的张量流层

0 个答案: