Can Keras deal with input images with different size?

Just change your input shape to shape=(n_channels, None, None).
Where n_channels is the number of channels in your input image.

I’m using Theano backend though, so if you are using tensorflow you might have to change it to (None,None,n_channels)

You should use:

input_shape=(1, None, None)

None in a shape denotes a variable dimension. Note that not all layers
will work with such variable dimensions, since some layers require
shape information (such as Flatten).

For example, using keras’s functional API your input layer would be:

For a RGB dataset

inp = Input(shape=(3,None,None))

For a Gray dataset

inp = Input(shape=(1,None,None))

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