Negative dimension size caused by subtracting 3 from 1 for 'conv2d_2/convolution'

Question

I got this error message when declaring the input layer in Keras.

ValueError: Negative dimension size caused by subtracting 3 from 1 for \'conv2d_2/

Answer 1

I had the same problem, however the solution provided in this thread did not help me. In my case it was a different problem that caused this error:

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Code

imageSize=32
classifier=Sequential() 

classifier.add(Conv2D(64, (3, 3), input_shape = (imageSize, imageSize, 3), activation = 'relu'))
classifier.add(MaxPooling2D(pool_size = (2, 2)))

classifier.add(Conv2D(64, (3, 3), activation = 'relu'))
classifier.add(MaxPooling2D(pool_size = (2, 2)))

classifier.add(Conv2D(64, (3, 3), activation = 'relu')) 
classifier.add(MaxPooling2D(pool_size = (2, 2)))

classifier.add(Conv2D(64, (3, 3), activation = 'relu')) 
classifier.add(MaxPooling2D(pool_size = (2, 2)))

classifier.add(Conv2D(64, (3, 3), activation = 'relu')) 
classifier.add(MaxPooling2D(pool_size = (2, 2)))

classifier.add(Flatten())

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Error

The image size is 32 by 32. After the first convolutional layer, we reduced it to 30 by 30. (If I understood convolution correctly)

Then the pooling layer divides it, so 15 by 15...

I hope you can see where this is going: In the end, my feature map is so small that my pooling layer (or convolution layer) is too big to go over it - and that causes the error

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Solution

The easy solution to this error is to either make the image size bigger or use less convolutional or pooling layers.