CODEWITHSUNDEEP
pythonimagetensorflowkeras
Thanh Nguyen
Thanh Nguyen

Reputation: 912

Select specific a set of RGB channel in Keras training model image input

In my Keras CNN, I add the Input layer like this:

model.add(Conv2D(32, (3, 3), input_shape=(img_width, img_height, nb_channel)))

with nb_channel = 3 for RGB input and = 1 for grayscale input and the flow_from_directory and ImageDataGenerator

However, I want to specify a set of color to channel to input to my CNN, for example, only green and red channels are permitted, how can I do so?

I'm using Keras with tensorflow Backend

Beside from the neat solution of @Minh-Tuan Nguyen, we can also do the slicing as follow 

#custom filter
def filter_layer(x):
    red_x = x[:,:,:,0]
    blue_x = x[:,:,:,2]
    green_x = x[:,:,:,1]
    red_x = tf.expand_dims(red_x, axis=3)
    blue_x = tf.expand_dims(blue_x, axis=3)
    green_x = tf.expand_dims(green_x, axis=3)
    output = tf.concat([red_x, blue_x], axis=3)
    return output
#model
input = Input(shape=(img_height, img_width, img_channels))

at the concat step we can choose the slice we want.

Upvotes: 1

Views: 3384

Answers (2)

Minh-Tuan Nguyen
Minh-Tuan Nguyen

Reputation: 358

I think it would be easier to process the slicing a bit more "naively" here since as my knowledge, Keras hasn't support slicing the tensor using a list of indices like python and numpy. Below is the example of my code for this problem. Try to see if it fit your requirement. 

indices = [0,2]

def filter_layer(input, indices=indices):
    for i in range(len(indices)):
        index = indices[i]
        x_temp = Lambda(lambda x: x[:,:,:,index][...,None])(input)

        if i==0:
            x = x_temp
        else:
            x = Concatenate(-1)([x, x_temp])
        return x

input = Input(shape=(img_height, img_width, img_channels))
x = Lambda(filter_layer)(input)

Upvotes: 2

nuric
nuric

Reputation: 11225

You can slice the input tensor inside a custom Lambda layer. Suppose you want only red and green:

model.add(Lambda(lambda x: x[:,:,:,:2], input_shape=(w, h, channels)))

TensorFlow allows for similar slicing to NumPy, for Keras you need wrap it around a Lambda layer to incorporate into your model.

Upvotes: 4

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