Resizes images to a given bounding box

Forked from anjos/rgb2gray/1

This algorithm is a legacy one. The API has changed since its implementation. New versions and forks will need to be updated.
This algorithm is splittable

Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.

Group: main

Endpoint Name Data Format Nature
input system/array_2d_uint8/1 Input
output system/array_2d_uint8/1 Output

Parameters allow users to change the configuration of an algorithm when scheduling an experiment

Name Description Type Default Range/Choices
width The width of the output image uint32 30
height The height of the output image uint32 40
interpolation The interpolation method to use for the resizing operation string bilinear nearest, bilinear, bicubic, cubic

The code for this algorithm in Python
The ruler at 80 columns indicate suggested POSIX line breaks (for readability).
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This converter will normalize input (gray-scaled) images so they all output with the same, parameterized, specifications.

Experiments

Updated Name Databases/Protocols Analyzers
anjos/anjos/livdet-lda/1/livdet-2013-biometrika-test livdet2013/1@Biometrika anjos/livdet_analysis/1

This table shows the number of times this algorithm has been successfully run using the given environment. Note this does not provide sufficient information to evaluate if the algorithm will run when submitted to different conditions.

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