imagenet_preprocess_input

Preprocesses a tensor or array encoding a batch of images.

Interface to 'Keras' <https://keras.io>, a high-level neural
networks 'API'. 'Keras' was developed with a focus on enabling fast experimentation,
supports both convolution based networks and recurrent networks (as well as
combinations of the two), and runs seamlessly on both 'CPU' and 'GPU' devices.

Tomasz Kalinowski

keras

R Interface to 'Keras'

Daniel Falbel

JJ Allaire

François Chollet

RStudio 

Google 

Yuan Tang

Wouter Van Der Bijl

Martin Studer

Sigrid Keydana

imagenet_preprocess_input function

<dl><dt>x</dt>
<dd>Input Numpy or symbolic tensor, 3D or 4D.</dd>
<dt>data_format</dt>
<dd>Data format of the image tensor/array.</dd>
<dt>mode</dt>
<dd>One of "caffe", "tf", or "torch"<ul>
<li>caffe: will convert the images from RGB to BGR,
then will zero-center each color channel with
respect to the ImageNet dataset,
without scaling.</li>
<li>tf: will scale pixels between -1 and 1, sample-wise.</li>
<li>torch: will scale pixels between 0 and 1 and then
will normalize each channel with respect to the
ImageNet dataset.</li>
</ul></dd></dl>

Arguments

Preprocesses a tensor or array encoding a batch of images. — imagenet_preprocess_input

<dl>

<dt>x</dt>
<dd>Input Numpy or symbolic tensor, 3D or 4D.</dd>


<dt>data_format</dt>
<dd>Data format of the image tensor/array.</dd>


<dt>mode</dt>
<dd>One of "caffe", "tf", or "torch"<ul>
<li>caffe: will convert the images from RGB to BGR,
then will zero-center each color channel with
respect to the ImageNet dataset,
without scaling.</li>
<li>tf: will scale pixels between -1 and 1, sample-wise.</li>
<li>torch: will scale pixels between 0 and 1 and then
will normalize each channel with respect to the
ImageNet dataset.</li>
</ul></dd>

</dl>

Preprocesses a tensor or array encoding a batch of images.

imagenet_preprocess_input: Preprocesses a tensor or array encoding a batch of images.

Description

Usage

Value

Arguments