Revert "Unimplemented header files for adaboost"

This reverts commit 5d001f4dba69bccdeb5e3db905b69cdaf18235dd.

Revert "Unimplemented header files for adaboost"
This reverts commit 5d001f4dba69bccdeb5e3db905b69cdaf18235dd.
JordanCheney
1 parent 5d001f4d
Showing 9 changed files with 1 additions and 177 deletions
openbr/CMakeLists.txt
openbr/learning/adaboost.cpp
openbr/learning/adaboost.h
openbr/learning/cascade.cpp
openbr/learning/cascade.h
openbr/learning/feature.cpp
openbr/learning/feature.h
openbr/learning/trainingdata.cpp
openbr/learning/trainingdata.h
@@ -11,7 +11,6 @@ add_definitions(-DJANUS_LIBRARY)
 # Collect source files
 aux_source_directory(. SRC)
 aux_source_directory(core BR_CORE)
-aux_source_directory(learning BR_LEARNING)
 include(plugins/plugins.cmake)
 # Optional GUI module
@@ -22,7 +21,7 @@ if(NOT ${BR_EMBEDDED})
   install(FILES ${HEADERS} DESTINATION include/openbr/gui)
 endif()
-add_library(openbr SHARED ${SRC} ${BR_CORE} ${BR_LEARNING} ${BR_JANUS} ${BR_GUI} ${BR_ICONS} ${BR_THIRDPARTY_SRC} ${BR_RESOURCES} ${NATURALSTRINGCOMPARE_SRC})
+add_library(openbr SHARED ${SRC} ${BR_CORE} ${BR_JANUS} ${BR_GUI} ${BR_ICONS} ${BR_THIRDPARTY_SRC} ${BR_RESOURCES} ${NATURALSTRINGCOMPARE_SRC})
 qt5_use_modules(openbr ${QT_DEPENDENCIES})
 set_target_properties(openbr PROPERTIES
                              DEFINE_SYMBOL BR_LIBRARY
-#include "adaboost.h"
-
-AdaBoost::AdaBoost()
-{
-}
-#ifndef ADABOOST_H
-#define ADABOOST_H
-
-#include "trainingdata.h"
-#include <openbr/openbr_plugin.h>
-
-namespace br
-{
-
-struct Node
-{
-    Node(int feature_idx, float threshold, int polarity, float weight) : feature_idx(feature_idx), threshold(threshold), polarity(polarity), weight(weight) {}
-    int predict(float feature_response) const { return (polarity * (feature_response - threshold)) > 0 ? 1 : -1; }
-
-    int feature_idx; // index of the feature corresponding to this weak classifier
-    float threshold; // threshold at which classifier predicts yes or no
-    int polarity; // 1 or -1. 1 if high responses correspond to positives, -1 if low values do.
-    float weight; // weight of this classifier. Higher weight = more accurate classifier
-};
-
-struct DecisionTree
-{
-    DecisionTree() {}
-    void append(Node node); // add a node to the tree
-    float predict(QList<float> responses) const; // progress down the tree. Return value should be the
-                                                 // sum of the weights of the correct nodes.
-
-    QList<Node> tree; // List of the weak classifiers
-};
-
-class AdaBoost
-{
-public:
-    AdaBoost();
-    DecisionTree train(int num_classifiers); // mostly a wrapper to call selectBestNode() and updateWeights() num_classifiers times.
-
-private:
-    Node selectBestNode(); // search through all possible features to find one that improves performance the most
-    void updateWeights(); // successful classification lowers weights, unsuccesful raises weights. After changes weights are normalized between 0 and 1
-
-    TrainingData td; // training data to train on
-    DecisionTree classifier; // classifier to be trained
-};
-
-}
-#endif // ADABOOST_H
-#include "cascade.h"
-
-Cascade::Cascade()
-{
-}
-#ifndef CASCADE_H
-#define CASCADE_H
-
-#include "feature.h"
-#include "adaboost.h"
-#include <openbr/openbr_plugin.h>
-
-namespace br
-{
-
-// I'm not sure if this class can be made general enough (i.e not just for face detection) to live here.
-// Ideally, it should handle model i/o, and probably detection as well. Perhaps it is better in plugins/cascade.cpp
-class Cascade
-{
-public:
-    Cascade(const DecisionTree &classifier, const FeatureEvaluator &evaluator) : classifier(classifier), evaluator(evaluator) {}
-    void detect(const cv::Mat &img, QList<QRectF> &detections, QList<float> &confidences);
-
-    void write(QString path);
-    static Cascade read(QString path);
-
-private:
-    DecisionTree classifier;
-    FeatureEvaluator evaluator;
-};
-
-}
-
-#endif // CASCADE_H
-#include "feature.h"
-
-Feature::Feature()
-{
-}
-#ifndef FEATURE_H
-#define FEATURE_H
-
-#include <openbr/openbr_plugin.h>
-
-// These two classes should be subclassed to handle any type of feature. In a perfect world I would like to subclass
-// only Feature, and have FeatureEvaluator just call randomize and evaluate (and thus not have to be subclassed) as
-// that would be simpler.
-namespace br
-{
-
-class Feature
-{
-public:
-    Feature();
-    QList<int> get_definition() { return definition; }
-
-    virtual void randomize(int height, int width, int channels) = 0; // Initialize the feature within these dimensions
-    virtual float evaluate(const QList<cv::Mat> &img, const cv::Size &pos) const = 0; // img is a list of mats to support multiple channels
-                                                                                      // if the image is larger than the feature model (i.e
-                                                                                      // a real image instead of a training image) pos determines
-                                                                                      // the top left corner of the feature.
-
-protected:
-    QList<int> definition; // The definition of the feature (usually these are coords)
-};
-
-class FeatureEvaluator
-{
-public:
-    FeatureEvaluator(int num_features_) : num_features(num_features_) {}
-    int get_num_features() const { return num_features; }
-    QList<Feature> get_features() const { return features; }
-
-    virtual void generateRandomFeatures(int height, int width, int channels) = 0; // initialize num_features random features within these dimensions.
-                                                                                  // will call Feature->randomize()
-    virtual QList<float> evaluate(const QList<cv::Mat> &img, cv::Size pos) const = 0; // return the response of all features on the given image
-                                                                                      // will call Feature->evaluate()
-
-private:
-    int num_features;
-    QList<Feature> features;
-};
-
-}
-
-#endif // FEATURE_H
-#include "trainingdata.h"
-
-TrainingData::TrainingData()
-{
-}
-#ifndef TRAININGDATA_H
-#define TRAININGDATA_H
-
-#include "feature.h"
-#include <openbr/openbr_plugin.h>
-
-namespace br
-{
-
-struct FeatureResponse // Feature vectors need to be sorted to do boosting. This keeps the weights and labels properly associated with the response without headaches.
-{
-    FeatureResponse(float response, int label, float weight) : response(response), label(label), weight(weight) {}
-
-    float response;
-    int label;
-    float weight;
-};
-
-typedef QList<FeatureResponse> FeatureVector;
-
-class TrainingData
-{
-public:
-    TrainingData();
-    // This can have getters and setters to make manipulating feature vectors easier
-
-private:
-    QList<FeatureVector> data;
-    QList<bool> visited_features;
-};
-
-}
-#endif // TRAININGDATA_H