From e85eb10b47648a7187d46f948a2bdf233cab16dd Mon Sep 17 00:00:00 2001
From: Guillaume HEUSCH <guillaume.heusch@idiap.ch>
Date: Wed, 21 Mar 2018 22:48:36 +0100
Subject: [PATCH] [algorithm] added my simple implementation of One Class SVM
---
bob/pad/base/algorithm/OCSVM.py | 73 ++++++++++++++++++++++++++++++
bob/pad/base/algorithm/__init__.py | 1 +
2 files changed, 74 insertions(+)
create mode 100644 bob/pad/base/algorithm/OCSVM.py
diff --git a/bob/pad/base/algorithm/OCSVM.py b/bob/pad/base/algorithm/OCSVM.py
new file mode 100644
index 0000000..a01a858
--- /dev/null
+++ b/bob/pad/base/algorithm/OCSVM.py
@@ -0,0 +1,73 @@
+#!/usr/bin/env python
+# vim: set fileencoding=utf-8 :
+
+import numpy
+from bob.pad.base.algorithm import Algorithm
+
+import bob.learn.libsvm
+import bob.io.base
+
+class OCSVM(Algorithm):
+ """
+ This class interfaces a One Class SVM classifier used for PAD
+
+ """
+
+ def __init__(self, rescale=True, nu=0.01, gamma=0.1, **kwargs):
+
+ Algorithm.__init__(self,
+ performs_projection=True,
+ requires_projector_training=True,
+ **kwargs)
+
+ self.rescale = rescale
+ self.nu = nu
+ self.gamma = gamma
+ self.machine = None
+ self.trainer = bob.learn.libsvm.Trainer(machine_type='ONE_CLASS', kernel_type='RBF', probability=True)
+
+
+ def train_projector(self, training_features, projector_file):
+ """
+ Trains the One Class SVM
+
+ **Parameters**
+
+ training_features:
+ """
+ # training_features[0] - training features for the REAL class.
+ # training_features[1] - training features for the ATTACK class.
+
+ # The data - "positive class only"
+ pos = numpy.array(training_features[0])
+
+ if self.rescale:
+ for i in range(pos.shape[0]):
+ min_value = numpy.min(pos[i])
+ max_value = numpy.max(pos[i])
+ pos[i] = ((2 * (pos[i] - min_value))/ (max_value - min_value)) - 1
+
+ pos = [pos]
+
+ # train
+ self.machine = self.trainer.train(pos)
+
+ print(self.machine.shape)
+
+ f = bob.io.base.HDF5File(projector_file, 'w')
+ self.machine.save(f)
+
+
+ def project(self, feature):
+ """
+ Project the given feature
+ """
+ if self.rescale:
+ min_value = numpy.min(feature)
+ max_value = numpy.max(feature)
+ feature = ((2 * (feature - min_value))/ (max_value - min_value)) - 1
+
+ return self.machine(feature)
+
+ def score(self, toscore):
+ return [toscore[0]]
diff --git a/bob/pad/base/algorithm/__init__.py b/bob/pad/base/algorithm/__init__.py
index b9da7c2..86c374c 100644
--- a/bob/pad/base/algorithm/__init__.py
+++ b/bob/pad/base/algorithm/__init__.py
@@ -5,6 +5,7 @@ from .LogRegr import LogRegr
from .SVMCascadePCA import SVMCascadePCA
from .MLP import MLP
from .PadLDA import PadLDA
+from .OCSVM import OCSVM
def __appropriate__(*args):
"""Says object was actually declared here, and not in the import module.
--
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