mlpack_image_converter(1) | User Commands | 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.
$ mlpack_image_converter --input X --height 256 --width 256 --channels 3 --output_file Y.csv
An example to load an image :
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.
28 January 2025 | mlpack-4.5.1 |