合并keras中的图层(合并) [英] Merge layers (concatenate) in keras

问题描述

我正在尝试实施

I am trying to implement this paper (the model architecture is given below) and have two models- coarse_model and fine_model which need to be concatenated at the second step of the fine model. However, I am getting an error when I trying to concatenate using the last axis.

from keras.models import Sequential
from keras.layers import Conv2D, MaxPooling2D
from keras.layers import Activation, Dropout, Flatten, Dense, Merge
from keras.layers.core import Reshape
from keras.layers.merge import Concatenate
from keras import backend as K


# dimensions of our images
#img_width, img_height = 320, 240

img_width, img_height = 304,228


if K.image_data_format() == 'channels_first':
    input_shape = (3, img_width, img_height)
else:
    input_shape = (img_width, img_height, 3)

# coarse model
coarse_model = Sequential()
# coarse layer 1
coarse_model.add(Conv2D(96,(11,11),strides=(4,4),input_shape=input_shape,activation='relu'))
coarse_model.add(MaxPooling2D(pool_size=(2, 2)))
# coarse layer 2
coarse_model.add(Conv2D(256,(5,5),activation='relu',padding='same'))
coarse_model.add(MaxPooling2D(pool_size=(2, 2)))
# coarse layer 3
coarse_model.add(Conv2D(384,(3,3),activation='relu',padding='same'))
# coarse layer 4
coarse_model.add(Conv2D(384,(3,3),activation='relu',padding='same'))
# coarse layer 5
coarse_model.add(Conv2D(256,(3,3),activation='relu',padding='same'))
coarse_model.add(Flatten())
# coarse layer 6
coarse_model.add(Dense(4096,activation='relu'))
# coarse layer 7
coarse_model.add(Dense(4070,activation='linear'))

# fine model
fine_model = Sequential()
fine_model.add(Conv2D(63,(9,9),strides=(2,2),input_shape=input_shape,activation='relu'))
fine_model.add(MaxPooling2D(pool_size=(2, 2)))

# reshape coarse model to shape of fine model
shape = fine_model.layers[1].output_shape
shape_subset = (shape[1],shape[2])


coarse_model.add(Reshape(shape_subset))
model = Sequential()
model.add(Merge([coarse_model.layers[10],fine_model.layers[1]],mode='concat',concat_axis=3))

---

最后一行给出的错误是: *** ValueError:"concat"模式只能合并具有匹配输出形状(concat轴除外)的图层.图层形状:[(无，74，55)，(无，74，55，63)]

---

The error given on the last line is: *** ValueError: "concat" mode can only merge layers with matching output shapes except for the concat axis. Layer shapes: [(None, 74, 55), (None, 74, 55, 63)]

推荐答案

要回答我自己的问题，请将形状更改为

To answer my own question, changing the shape to

shape_subset = (shape[1],shape[2],1)

和

model.add(Merge([coarse_model.layers[10],fine_model.layers[1]],mode='concat',concat_axis=-1))

使代码正常工作.

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