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

Endpoint Groups 1

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_floats/1	Output

Parameters 6

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

Name	Type	Default
left-eye-x	uint32	48
left-eye-y	uint32	16
crop-height	uint32	80
crop-width	uint32	64
right-eye-x	uint32	15
right-eye-y	uint32	16

import bob
import numpy

class Algorithm:

def __init__(self):
        self.crop_height = 80
        self.crop_width  = 64
        self.right_eye_y = 16
        self.right_eye_x = 15
        self.left_eye_y  = 16
        self.left_eye_x  = 48

def setup(self, parameters):
        self.crop_height = parameters.get('crop-height', self.crop_height)
        self.crop_width  = parameters.get('crop-width',  self.crop_width)
        self.right_eye_y = parameters.get('right-eye-y', self.right_eye_y)
        self.right_eye_x = parameters.get('right-eye-x', self.right_eye_x)
        self.left_eye_y  = parameters.get('left-eye-y',  self.left_eye_y)
        self.left_eye_x  = parameters.get('left-eye-x',  self.left_eye_x)

self.cropper = bob.ip.FaceEyesNorm(self.crop_height, self.crop_width,
                self.right_eye_y, self.right_eye_x, self.left_eye_y, self.left_eye_x)

return True

def process(self, inputs, outputs):
        image = bob.ip.rgb_to_gray(inputs["image"].data.value)
        eye_positions = inputs["eye_centers"].data

outputs["cropped_image"].write({
            'value': self.cropper(image, float(eye_positions.right.y), float(eye_positions.right.x),
                                   float(eye_positions.left.y), float(eye_positions.left.x)).astype("float64")
        })

return True

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 face cropping, given the eye center coordinates.

The difference between this algorithm with the one published here (https://www.beat-eu.org/platform/algorithms/tutorial/cropping_rgb/8/) is that for this one the output is system/array_2d_floats/1

This implementation relies on the `Bob <http://www.idiap.ch/software/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).

Docutils System Messages

System Message: ERROR/3 (<string>, line 6); backlink

Unknown target name: "bob <http://www.idiap.ch/software/bob>".

Experiments

Attestation:

Privacy:

Status:

Name	Databases/Protocols	Analyzers
smarcel/tpereira/full_isv_multi/2/btas2015_face-periocular_mobio-female_det	mobio/1@female	tutorial/eerhter_postperf_iso/1
tpereira/tpereira/full_isv_multi/2/btas2015_face-periocular_cpqd-smartphone-male_det	cpqd/1@smartphone_male	tutorial/eerhter_postperf_iso/1
tpereira/tpereira/full_isv/2/btas2015_face_cpqd-smartphone-male_det	cpqd/1@smartphone_male	tutorial/eerhter_postperf_iso/1
tpereira/tpereira/full_isv_multi/2/btas2015_face-periocular_mobio-male_det	mobio/1@male	tutorial/eerhter_postperf_iso/1
tpereira/tpereira/full_isv/2/btas2015_face_mobio-male_det	mobio/1@male	tutorial/eerhter_postperf_iso/1
tpereira/tpereira/full_isv_multi/2/btas2015_face-periocular_cpqd-smartphone-female_det	cpqd/1@smartphone_female	tutorial/eerhter_postperf_iso/1
tpereira/tpereira/full_isv/2/btas2015_face_cpqd-smartphone-female_det	cpqd/1@smartphone_female	tutorial/eerhter_postperf_iso/1
tpereira/tpereira/full_isv_multi/2/btas2015_face-periocular_mobio-female_det	mobio/1@female	tutorial/eerhter_postperf_iso/1
tpereira/tpereira/full_isv/2/btas2015_face_mobio-female_det	mobio/1@female	tutorial/eerhter_postperf_iso/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.

algorithms tpereira cropping_rgb_floats 1

Endpoint Groups 1

Group: main

Parameters 6

Docutils System Messages

Experiments

algorithms

tpereira

cropping_rgb_floats

1