BEAT - anjos/lda/1

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

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
class	system/boolean/1	Input
subspace	tutorial/linear_machine/1	Output

import bob
import numpy

class Algorithm:

def __init__(self):
        self.data = [[], []]

def process(self, inputs, outputs):
        
        # accumulates the input data in different
        # containers for hit or miss
        flat_image = inputs["image"].data.value.astype('float64').flatten()
        if inputs["class"].data.value:
            self.data[1].append(flat_image)
        else:
            self.data[0].append(flat_image)
        
        if not(inputs.hasMoreData()):
            # trains the LDA projection
            self.data[0] = numpy.vstack(self.data[0])
            self.data[1] = numpy.vstack(self.data[1])

trainer = bob.trainer.FisherLDATrainer(use_pinv=True)
            
            machine, eigen_values = trainer.train(self.data)
            machine.resize(machine.shape[0], 1) #just to make sure

# outputs data
            outputs["subspace"].write({
                'input_subtract': machine.input_subtract,
                'input_divide':   machine.input_divide,
                'weights':        machine.weights,
                'biases':         machine.biases,
            })

return True

The code for this algorithm in Python
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This algorithm will run Linear Discriminant Analysis [LDA] for a binary classification problem using images as inputs.

The inputs handle the images and a boolean flag indicating if the data is a hit or a miss.

[LDA]

http://en.wikipedia.org/wiki/Linear_Discriminant_analysis

Experiments

Attestation:

Privacy:

Status:

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

Scientific Python 2.7 (0.0.4) 2

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 anjos lda 1

Endpoint Groups 1

Group: main

Experiments

algorithms

anjos

lda

1