CODEWITHSUNDEEP
tensorflowkerasconvolution
Jacky Liu
Jacky Liu

Reputation: 147

How to connect Conv3D output to MaxPooling2D in Keras?

I'm using Keras to implement CNN. People often use Conv2D to do classification tasks. However, I want to get relationships between two images, then I decide to try Conv3D. However, I couldn't manage the dimension output from Conv3D and match the following layers.

More specifically, I want to apply (5,5,2) filter on two stacked images which are (480, 640, 2), and output(480, 640, 1) tensor.

enter image description here

Original Conv2D code: (work fine)

model = Sequential()
model.add(Conv2D(32, (3, 3), padding='same',input_shape=(480, 640, 2)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Conv2D(64, (3, 3), padding='same'))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
...

Conv3D code: (Don't know how to concatenate Conv3D and MaxPooling2D)

model.add(Conv3D(32, 2, input_shape=(480, 640, 2, 1), data_format="channels_last"))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2,2)))


model.add(Conv2D(64, (3, 3), padding='same'))
model.add(Activation('relu'))
model.add(Conv2D(64, (3, 3), padding='same'))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
...

Upvotes: 1

Views: 1241

Answers (1)

layog
layog

Reputation: 4801

Stack both the images (remember to stack acc. to the backend you are using, theano is channels_first and tensorflow is channels_last) and pass 2 as the number of channels in Conv2D.

Or if you have many channels for each images, then again stack them up and pass the total number of channels to Conv2D.

Upvotes: 1

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