Performs a crop of the periocular region of the face

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
image system/array_3d_uint8/1 Input
eye_centers system/eye_positions/1 Input
cropped_image 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
left-eye-x Final position of the left eye (x-coord) uint32 44
left-eye-y Final position of the left eye (y-coord) uint32 12
color Final color channel string gray gray, red, green, blue
crop-height Final image height uint32 25
crop-width Final image width uint32 58
right-eye-x Final position of the right eye (x-coord) uint32 11
right-eye-y Final position of the right eye (y-coord) uint32 12

The code for this algorithm in Python
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This algorithm performs a RGB to grayscale conversion of an image followed by a periocular cropping of the face, given the eye center coordinates.

This implementation relies on the Bob library.

The inputs are:

  • image: an RGB image as a three-dimensional array of uint8, the first dimension being the number of color planes (3), and the second and third dimensions corresponding to the height and width of the original image, respectively.
  • eye_centers: the coordinates of the eye centers in the original image space

The output cropped_image is a grayscale cropped image as a two-dimensional array of floats (64 bits).

No experiments are using this algorithm.
This algorithm was never executed.
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