Peter M. Groen / openbr

Commit fcb1bcac0dd72c4c1d63e70838f4ed5e156f81d8

Authored by Josh Klontz
1 parent f76fe526

removed adaboost

Inline Side-by-side
Showing 1 changed file with 0 additions and 135 deletions
openbr/plugins/classification/adaboost.cpp deleted
View file @f76fe52
1   -/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
2   - * Copyright 2012 The MITRE Corporation *
3   - * *
4   - * Licensed under the Apache License, Version 2.0 (the "License"); *
5   - * you may not use this file except in compliance with the License. *
6   - * You may obtain a copy of the License at *
7   - * *
8   - * http://www.apache.org/licenses/LICENSE-2.0 *
9   - * *
10   - * Unless required by applicable law or agreed to in writing, software *
11   - * distributed under the License is distributed on an "AS IS" BASIS, *
12   - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. *
13   - * See the License for the specific language governing permissions and *
14   - * limitations under the License. *
15   - * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
16   -
17   -#include <openbr/plugins/openbr_internal.h>
18   -#include <openbr/core/opencvutils.h>
19   -
20   -using namespace cv;
21   -
22   -namespace br
23   -{
24   -
25   -/*!
26   - * \ingroup transforms
27   - * \brief Wraps OpenCV's Ada Boost framework
28   - * \author Scott Klum \cite sklum
29   - * \br_link http://docs.opencv.org/modules/ml/doc/boosting.html
30   - * \br_property type enum Type of Adaboost to perform. Options are: [Discrete, Real, Logit, Gentle] Default is Real.
31   - * \br_property splitCriteria enum Splitting criteria used to choose optimal splits during a weak tree construction. Options are: [Default, Gini, Misclass, Sqerr] Default is Default.
32   - * \br_property weakCount int Maximum number of weak classifiers per stage. Default is 100.
33   - * \br_property trimRate float A threshold between 0 and 1 used to save computational time. Samples with summary weight \leq 1 - weight\_trim\_rate do not participate in the next iteration of training. Set this parameter to 0 to turn off this functionality. Default is 0.95.
34   - * \br_property folds int OpenCV parameter variable. Default value is 0.
35   - * \br_property maxDepth int Maximum height of each weak classifier tree. Default is 1 (stumps).
36   - * \br_property returnConfidence bool Return the confidence value of the classification or the class value of the classification. Default is true (return confidence value).
37   - * \br_property overwriteMat bool If true, the output template will be a 1x1 matrix with value equal to the confidence or classification (depending on returnConfidence). If false the output template will be the same as the input template. Default is true.
38   - * \br_property inputVariable QString Metadata variable storing the label for each template. Default is "Label".
39   - * \br_property outputVariable QString Metadata variable to store the confidence or classification of each template (depending on returnConfidence). If overwriteMat is true nothing will be written here. Default is "".
40   - */
41   -class AdaBoostTransform : public Transform
42   -{
43   - Q_OBJECT
44   - Q_ENUMS(Type)
45   - Q_ENUMS(SplitCriteria)
46   -
47   - Q_PROPERTY(Type type READ get_type WRITE set_type RESET reset_type STORED false)
48   - Q_PROPERTY(int weakCount READ get_weakCount WRITE set_weakCount RESET reset_weakCount STORED false)
49   - Q_PROPERTY(float trimRate READ get_trimRate WRITE set_trimRate RESET reset_trimRate STORED false)
50   - Q_PROPERTY(int folds READ get_folds WRITE set_folds RESET reset_folds STORED false)
51   - Q_PROPERTY(int maxDepth READ get_maxDepth WRITE set_maxDepth RESET reset_maxDepth STORED false)
52   - Q_PROPERTY(bool returnConfidence READ get_returnConfidence WRITE set_returnConfidence RESET reset_returnConfidence STORED false)
53   - Q_PROPERTY(bool overwriteMat READ get_overwriteMat WRITE set_overwriteMat RESET reset_overwriteMat STORED false)
54   - Q_PROPERTY(QString inputVariable READ get_inputVariable WRITE set_inputVariable RESET reset_inputVariable STORED false)
55   - Q_PROPERTY(QString outputVariable READ get_outputVariable WRITE set_outputVariable RESET reset_outputVariable STORED false)
56   -
57   -public:
58   - enum Type { Discrete = ml::Boost::DISCRETE,
59   - Real = ml::Boost::REAL,
60   - Logit = ml::Boost::LOGIT,
61   - Gentle = ml::Boost::GENTLE};
62   -
63   -private:
64   - BR_PROPERTY(Type, type, Real)
65   - BR_PROPERTY(int, weakCount, 100)
66   - BR_PROPERTY(float, trimRate, .95)
67   - BR_PROPERTY(int, folds, 0)
68   - BR_PROPERTY(int, maxDepth, 1)
69   - BR_PROPERTY(bool, returnConfidence, true)
70   - BR_PROPERTY(bool, overwriteMat, true)
71   - BR_PROPERTY(QString, inputVariable, "Label")
72   - BR_PROPERTY(QString, outputVariable, "")
73   -
74   - Ptr<ml::Boost> boost;
75   -
76   - void init()
77   - {
78   - boost = ml::Boost::create();
79   -
80   - if (outputVariable.isEmpty())
81   - outputVariable = inputVariable;
82   - }
83   -
84   - void train(const TemplateList &data)
85   - {
86   - Mat samples = OpenCVUtils::toMat(data.data());
87   - Mat labels = OpenCVUtils::toMat(File::get<float>(data, inputVariable));
88   -
89   - Mat types = Mat(samples.cols + 1, 1, CV_8U);
90   - types.setTo(Scalar(ml::VAR_NUMERICAL));
91   - types.at<char>(samples.cols, 0) = ml::VAR_CATEGORICAL;
92   -
93   - boost->setBoostType(type);
94   - boost->setWeakCount(weakCount);
95   - boost->setWeightTrimRate(trimRate);
96   - boost->setCVFolds(folds);
97   - boost->setMaxDepth(maxDepth);
98   -
99   - boost->train(ml::TrainData::create(samples, ml::ROW_SAMPLE, labels, noArray(), noArray(), types, noArray()));
100   - }
101   -
102   - void project(const Template &src, Template &dst) const
103   - {
104   - dst = src;
105   - float response;
106   - if (returnConfidence) {
107   - response = boost->predict(src.m().reshape(1,1), noArray(), ml::StatModel::RAW_OUTPUT) / weakCount;
108   - } else {
109   - response = boost->predict(src.m().reshape(1,1));
110   - }
111   -
112   - if (overwriteMat) {
113   - dst.m() = Mat(1, 1, CV_32F);
114   - dst.m().at<float>(0, 0) = response;
115   - } else {
116   - dst.file.set(outputVariable, response);
117   - }
118   - }
119   -
120   - void load(QDataStream &stream)
121   - {
122   - OpenCVUtils::loadModel(boost,stream);
123   - }
124   -
125   - void store(QDataStream &stream) const
126   - {
127   - OpenCVUtils::storeModel(boost,stream);
128   - }
129   -};
130   -
131   -BR_REGISTER(Transform, AdaBoostTransform)
132   -
133   -} // namespace br
134   -
135   -#include "classification/adaboost.moc"