CODEWITHSUNDEEP
machine-learningtensorflowdeep-learningkerastensor
user1159517
user1159517

Reputation: 6320

How to subtract channel wise mean in keras?

I have implemented a lambda function to resize an image from 28x28x1 to 224x224x3. I need to subtract the VGG mean from all the channels. When i try this, i get an error

TypeError: 'Tensor' object does not support item assignment 

def try_reshape_to_vgg(x):
    x = K.repeat_elements(x, 3, axis=3)
    x = K.resize_images(x, 8, 8, data_format="channels_last")
    x[:, :, :, 0] = x[:, :, :, 0] - 103.939
    x[:, :, :, 1] = x[:, :, :, 1] - 116.779
    x[:, :, :, 2] = x[:, :, :, 2] - 123.68
    return x[:, :, :, ::-1]

What's the recommended solution to do element wise subtraction of tensors?

Upvotes: 0

Views: 2081

Answers (1)

Yu-Yang
Yu-Yang

Reputation: 14619

You can use keras.applications.imagenet_utils.preprocess_input on tensors after Keras 2.1.2. It will subtract the VGG mean from x under the default mode 'caffe'.

from keras.applications.imagenet_utils import preprocess_input

def try_reshape_to_vgg(x):
    x = K.repeat_elements(x, 3, axis=3)
    x = K.resize_images(x, 8, 8, data_format="channels_last")
    x = preprocess_input(x)
    return x

If you would like to stay in an older version of Keras, maybe you can check how it is implemented in Keras 2.1.2, and extract useful lines into try_reshape_to_vgg.

def _preprocess_symbolic_input(x, data_format, mode):
    global _IMAGENET_MEAN

    if mode == 'tf':
        x /= 127.5
        x -= 1.
        return x

    if data_format == 'channels_first':
        # 'RGB'->'BGR'
        if K.ndim(x) == 3:
            x = x[::-1, ...]
        else:
            x = x[:, ::-1, ...]
    else:
        # 'RGB'->'BGR'
        x = x[..., ::-1]

    if _IMAGENET_MEAN is None:
        _IMAGENET_MEAN = K.constant(-np.array([103.939, 116.779, 123.68]))
    # Zero-center by mean pixel
    if K.dtype(x) != K.dtype(_IMAGENET_MEAN):
        x = K.bias_add(x, K.cast(_IMAGENET_MEAN, K.dtype(x)), data_format)
    else:
        x = K.bias_add(x, _IMAGENET_MEAN, data_format)
    return x

Upvotes: 4

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