BEAT - Kanma/cropping_grayscale__u8_to

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_2d_uint8/1	Input
cropped_image	system/array_2d_floats/1	Output

Parameters 5

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

Name	Description	Type	Default
y	Top coordinate of the cropping area	uint32	0
x	Right coordinate of the cropping area	uint32	0
width	Width of the cropping area	uint32	1000
normalized	If true, the values are normalized between 0 and 1	bool	False
height	Height of the cropping area	uint32	1000

import numpy

class Algorithm:

def setup(self, parameters):
        self.cropping_area = dict(
            x=parameters.get('x', 0),
            y=parameters.get('y', 0),
            width=parameters.get('width', 1000),
            height=parameters.get('height', 1000)
        )
        self.normalized = parameters.get('normalized', False)
        return True

def process(self, inputs, outputs):
        image = inputs["image"].data.value

# Check that the cropping is possible
        x = self.cropping_area['x']
        y = self.cropping_area['y']
        
        if (x >= image.shape[1]) or (y >= image.shape[0]):
            return False

width = min(image.shape[1] - x, self.cropping_area['width'])
        height = min(image.shape[0] - y, self.cropping_area['height'])

cropped_image = image[y:y+height,x:x+width].astype(numpy.float64)
        if self.normalized:
            cropped_image = cropped_image / 255.0
                                                            
        outputs["cropped_image"].write({
            'value': cropped_image
        })

return True

The code for this algorithm in Python
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Could not find any documentation for this object.

No experiments are using this algorithm.

This algorithm was never executed.

algorithms Kanma cropping_grayscale__u8_to_f 1

Endpoint Groups 1

Group: main

Parameters 5

algorithms

Kanma

cropping_grayscale__u8_to_f

1