preprocess_input() method in keras

Question

I am trying out sample keras code from the below keras documentation page, https://keras.io/applications/

What preprocess_input(x)

Answer 1

This loads an image and resizes the image to (224, 224):

 img = image.load_img(img_path, target_size=(224, 224))

The img_to_array() function adds channels: x.shape = (224, 224, 3) for RGB and (224, 224, 1) for gray image

 x = image.img_to_array(img) 

expand_dims() is used to add the number of images: x.shape = (1, 224, 224, 3):

x = np.expand_dims(x, axis=0)

preprocess_input subtracts the mean RGB channels of the imagenet dataset. This is because the model you are using has been trained on a different dataset: x.shape is still (1, 224, 224, 3)

x = preprocess_input(x)

If you add x to an array images, at the end of the loop, you need to add images = np.vstack(images) so that you get (n, 224, 224, 3) as the dim of images where n is the number of images processed