mlpack_image_converter(1)

NAME
mlpack_image_converter - image converter

SYNOPSIS
 mlpack_image_converter -i vector [-c int] [-I unknown] [-H int] [-q int] [-s bool] [-V bool] [-w int] [-o unknown] [-h -v]

DESCRIPTION

This utility takes an image or an array of images and loads them to a matrix. You can optionally specify the height '--height (-H)' width '--width (-w)' and channel '--channels (-c)' of the images that needs to be loaded; otherwise, these parameters will be automatically detected from the image. There are other options too, that can be specified such as '--quality (-q)'.

You can also provide a dataset and save them as images using '--dataset_file (-I)' and '--save (-s)' as an parameter.

  An example to load an image :

$ mlpack_image_converter --input X --height 256 --width 256 --channels 3 --output_file Y.csv

    An example to save an image is :

$ mlpack_image_converter --input X --height 256 --width 256 --channels 3 --dataset_file Y.csv --save

REQUIRED INPUT OPTIONS

--input (-i) [vector]
    Image filenames which have to be loaded/saved.

OPTIONAL INPUT OPTIONS

--channels (-c) [int]
    Number of channels in the image. Default value 0.

--dataset_file (-I) [unknown]
    Input matrix to save as images.

--height (-H) [int]
    Height of the images. Default value 0.

--help (-h) [bool]
    Default help info.

--info [string]
    Print help on a specific option. Default value ''.

--quality (-q) [int]
    Compression of the image if saved as jpg (0-100). Default value 90.

--save (-s) [bool]
    Save a dataset as images.

--verbose (-v) [bool]
    Display informational messages and the full list of parameters and timers at the end of execution.

--version (-V) [bool]
    Display the version of mlpack.

--width (-w) [int]
    Width of the image. Default value 0.

OPTIONAL OUTPUT OPTIONS

--output_file (-o) [unknown] Matrix to save images data to, Onlyneeded if you are specifying 'save' option.

ADDITIONAL INFORMATION

For further information, including relevant papers, citations, and theory, consult the documentation found at http://www.mlpack.org or included with your distribution of mlpack.