numpy normalize image

Phuong Anh Dang answered on August 1, 2022 Popularity 9/10 Helpfulness 1/10

answer numpy normalize image

numpy normalize image

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def normalize_images(images):
    # initial zero ndarray
    normalized_images = np.zeros_like(images.astype(float))

    # The first images index is number of images where the other indices indicates
    # hieight, width and depth of the image
    num_images = images.shape[0]

    # Computing the minimum and maximum value of the input image to do the normalization based on them
    maximum_value, minimum_value = images.max(), images.min()

    # Normalize all the pixel values of the images to be from 0 to 1
    for img in range(num_images):
        normalized_images[img, ...] = (images[img, ...] - float(minimum_value)) / float(maximum_value - minimum_value)

    return normalized_images


# encoding the input images. Each image will be represented by a vector of zeros except for the class index of the image
# that this vector represents. The length of this vector depends on number of classes that we have
# the dataset which is 10 in CIFAR-10

Popularity 9/10 Helpfulness 1/10 Language python

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Contributed on Aug 01 2022

Phuong Anh Dang

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numpy normalize image

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numpy normalize image

numpy normalize image