Merge branch 'master' of https://github.com/biometrics/openbr

Scott Klum
2 parents f2e360a1 a0c58d41
Showing 20 changed files with 228 additions and 212 deletions
CHANGELOG.md
app/br/CMakeLists.txt
app/br/br.cpp
data
scripts/trainAgeRegression-PCSO.sh
scripts/trainFaceRecognition-PCSO.sh
scripts/trainGenderClassification-PCSO.sh
sdk/core/bee.cpp
sdk/openbr_plugin.cpp
sdk/plugins/algorithms.cpp
sdk/plugins/ct8.cpp
sdk/plugins/draw.cpp
sdk/plugins/eyes.cpp
sdk/plugins/gallery.cpp
sdk/plugins/hist.cpp
sdk/plugins/integral.cpp
sdk/plugins/nec3.cpp
sdk/plugins/quality.cpp
sdk/plugins/regions.cpp
sdk/plugins/youtube.cpp
@@ -6,6 +6,7 @@
 * NEC3 refactored
 * Updated transform API to add support for time-varying transforms per issue (#23)
 * Refactored File class to improve point and rect storage (#22)
+* Added algorithm to show face detection results (#25)
 0.2.0 - 2/23/13
 ===============
@@ -8,3 +8,4 @@ install(TARGETS br RUNTIME DESTINATION bin)
 add_test(NAME br_initialize WORKING_DIRECTORY ${CMAKE_BINARY_DIR} COMMAND br)
 add_test(NAME br_objects WORKING_DIRECTORY ${CMAKE_BINARY_DIR} COMMAND br -objects)
+add_test(NAME br_draw_face_detection WORKING_DIRECTORY ${CMAKE_BINARY_DIR} COMMAND br -algorithm DrawFaceDetection -enroll ../data/family.jpg)
@@ -31,10 +31,20 @@
  * \endcode
  *
  * \section cli_examples Examples
+ * - \ref cli_show_face_detection
  * - \ref cli_age_estimation
  * - \ref cli_face_recognition
  * - \ref cli_face_recognition_evaluation
  * - \ref cli_gender_estimation
+ * - \ref cli_show_face_detection
+ */
+
+/*!
+ * \ingroup cli
+ * \page cli_show_face_detection Show Face Detection
+ * \code
+ * $ br -algorithm ShowFaceDetection -enrollAll -enroll ../data/family.jpg # Press 'Enter' to cycle through the results
+ * \endcode
  */
 static void help()
-Subproject commit 3501de8f90e2ec366ea418c7d5d2ef8beb612e73
+#!/bin/bash
+if [ ! -f trainAgeRegression-PCSO.sh ]; then
+  echo "Run this script from the scripts folder!"
+  exit
+fi
+
+#rm -f ../models/features/FaceClassificationRegistration
+#rm -f ../models/features/FaceClassificationExtraction
+rm -f ../models/algorithms/AgeRegression
+
+br -algorithm AgeRegression -path ../data/PCSO/Images -train "../data/PCSO/PCSO.db[query='SELECT File,Age,PersonID FROM PCSO WHERE Age >= 15 AND AGE <= 75', subset=0:200]" ../share/openbr/models/algorithms/AgeRegression
+#!/bin/bash
+if [ ! -f trainFaceRecognition-PCSO.sh ]; then
+  echo "Run this script from the scripts folder!"
+  exit
+fi
+
+#rm -f ../models/features/FaceRecognitionRegistration
+#rm -f ../models/features/FaceRecognitionExtraction
+#rm -f ../models/features/FaceRecognitionEmbedding
+#rm -f ../models/features/FaceRecognitionQuantization
+rm -f ../models/algorithms/FaceRecognition
+
+br -algorithm FaceRecognition -path ../data/PCSO/Images -train "../data/PCSO/PCSO.db[query='SELECT File,'S'||PersonID,PersonID FROM PCSO', subset=0:5:6000]" ../share/openbr/models/algorithms/FaceRecognition
+#!/bin/bash
+if [ ! -f trainGenderClassification-PCSO.sh ]; then
+  echo "Run this script from the scripts folder!"
+  exit
+fi
+
+#rm -f ../models/features/FaceClassificationRegistration
+#rm -f ../models/features/FaceClassificationExtraction
+rm -f ../models/algorithms/GenderClassification
+
+br -algorithm GenderClassification -path ../data/PCSO/Images -train "../data/PCSO/PCSO.db[query='SELECT File,Gender,PersonID FROM PCSO', subset=0:8000]" ../share/openbr/models/algorithms/GenderClassification
@@ -199,6 +199,7 @@ void writeMatrix(const Mat &amp;m, const QString &amp;matrix, const QString &amp;targetSigse
     char buff[4];
     QFile file(matrix);
+    QtUtils::touchDir(file);
     bool success = file.open(QFile::WriteOnly); if (!success) qFatal("Unable to open %s for writing.", qPrintable(matrix));
     file.write("S2\n");
     file.write(qPrintable(QFileInfo(targetSigset).fileName()));
@@ -1108,7 +1108,7 @@ private:
         QList<TemplateList> templatesList;
         foreach (const Template &t, data) {
             if ((templatesList.size() != t.size()) && !templatesList.isEmpty())
-                qWarning("Independent::train template %s of size %d differs from expected size %d.", qPrintable((QString)t.file), t.size(), templatesList.size());
+                qWarning("Independent::train template %s of size %d differs from expected size %d.", qPrintable(t.file.name), t.size(), templatesList.size());
             while (templatesList.size() < t.size())
                 templatesList.append(TemplateList());
             for (int i=0; i<t.size(); i++)
@@ -1134,11 +1134,13 @@ private:
     void project(const Template &src, Template &dst) const
     {
         dst.file = src.file;
+        QList<Mat> mats;
         for (int i=0; i<src.size(); i++) {
-            Template m;
-            transforms[i%transforms.size()]->project(Template(src.file, src[i]), m);
-            dst.merge(m);
+            transforms[i%transforms.size()]->project(Template(src.file, src[i]), dst);
+            mats.append(dst);
+            dst.clear();
         }
+        dst.append(mats);
     }
     void store(QDataStream &stream) const
@@ -38,6 +38,8 @@ class AlgorithmsInitializer : public Initializer
         Globals->abbreviations.insert("FaceQuality", "Open!Cascade(FrontalFace)+ASEFEyes+Affine(64,64,0.25,0.35)+ImageQuality+Cvt(Gray)+DFFS+Discard");
         Globals->abbreviations.insert("MedianFace", "Open!Cascade(FrontalFace)+ASEFEyes+Affine(256,256,0.37,0.45)+Center(Median)");
         Globals->abbreviations.insert("BlurredFaceDetection", "Open+LimitSize(1024)+SkinMask/(Cvt(Gray)+GradientMask)+And+Morph(Erode,16)+LargestConvexArea");
+        Globals->abbreviations.insert("DrawFaceDetection", "Open+Cascade(FrontalFace)!ASEFEyes+Draw");
+        Globals->abbreviations.insert("ShowFaceDetection", "DrawFaceDetection!Show");
         Globals->abbreviations.insert("OpenBR", "FaceRecognition");
         Globals->abbreviations.insert("GenderEstimation", "GenderClassification");
         Globals->abbreviations.insert("AgeEstimation", "AgeRegression");
@@ -48,6 +50,7 @@ class AlgorithmsInitializer : public Initializer
         Globals->abbreviations.insert("SmallSIFT", "Open+LimitSize(512)+KeyPointDetector(SIFT)+KeyPointDescriptor(SIFT):KeyPointMatcher(BruteForce)");
         Globals->abbreviations.insert("SmallSURF", "Open+LimitSize(512)+KeyPointDetector(SURF)+KeyPointDescriptor(SURF):KeyPointMatcher(BruteForce)");
         Globals->abbreviations.insert("ColorHist", "Open+LimitSize(512)!EnsureChannels(3)+SplitChannels+Hist(256,0,8)+Cat+Normalize(L1):L2");
+        Globals->abbreviations.insert("IHH", "Open+SplitChannels/(Cvt(Gray)+Gradient+Bin(0,6.283,8,true))+Integral+Merge+IntegralSampler");
         // Hash
         Globals->abbreviations.insert("FileName", "Name+Identity:Identical");
@@ -236,7 +236,6 @@ struct CT8Context
             FRsdk::SampleSet sampleSet;
             sampleSet.push_back(sample);
-
             FRsdk::EnrolOpenCVFeedback * feedback_body = new FRsdk::EnrolOpenCVFeedback(m);
             FRsdk::CountedPtr<FRsdk::Enrollment::FeedbackBody> feedback_ptr(feedback_body);
@@ -300,14 +299,14 @@ protected:
  * \author Josh Klontz \cite jklontz
  * \author Charles Otto \cite caotto
  */
-struct CT8Detect : public UntrainableTransform
-                 , public CT8Context
+class CT8DetectTransform : public UntrainableTransform
+                         , public CT8Context
 {
-public:
     Q_OBJECT
-
     Q_PROPERTY(float minRelEyeDistance READ get_minRelEyeDistance WRITE set_minRelEyeDistance RESET reset_minRelEyeDistance STORED false)
     Q_PROPERTY(float maxRelEyeDistance READ get_maxRelEyeDistance WRITE set_maxRelEyeDistance RESET reset_maxRelEyeDistance STORED false)
+    BR_PROPERTY(float, minRelEyeDistance, 0.01f)
+    BR_PROPERTY(float, maxRelEyeDistance, 0.4f)
     // Perform face, then eye detection using the facevacs SDK
     void project(const Template &src, Template &dst) const
@@ -316,57 +315,39 @@ public:
             // Build an FRsdk image from the input openCV mat
             FRsdk::CountedPtr<FRsdk::ImageBody> i(new FRsdk::OpenCVImageBody(src));
             FRsdk::Image img(i);
-            
             FRsdk::Face::LocationSet faceLocations = faceFinder->find(img, minRelEyeDistance, maxRelEyeDistance);
-            
-            // If the face finder doesn't find anything mark the output as a failure
-            if (faceLocations.empty() ) {
-                dst.file.setBool("FTE");
-                return;
-            }
-
-            QList<QRectF> ROIs;
-            QList<QPointF> landmarks;
-            FRsdk::Face::LocationSet::const_iterator faceLocationSetIterator = faceLocations.begin();
-            bool any_eyes = false;
             // Attempt to detect eyes in any face ROIs that were detected
+            QList<QRectF> rects;
+            QList<QPointF> points;
+            FRsdk::Face::LocationSet::const_iterator faceLocationSetIterator = faceLocations.begin();
             while (faceLocationSetIterator != faceLocations.end()) {
                 FRsdk::Face::Location faceLocation = *faceLocationSetIterator; faceLocationSetIterator++;
                 FRsdk::Eyes::LocationSet currentEyesLocations = eyesFinder->find(img, faceLocation);
                 if (currentEyesLocations.size() > 0) {
-                    any_eyes = true;
-                    ROIs.append(QRectF(faceLocation.pos.x(), faceLocation.pos.y(), faceLocation.width, faceLocation.width));
-                    landmarks.append(QPointF(currentEyesLocations.front().first.x(), currentEyesLocations.front().first.y()));
-                    landmarks.append(QPointF(currentEyesLocations.front().second.x(), currentEyesLocations.front().second.y()));
-
-                    dst += src;
+                    rects.append(QRectF(faceLocation.pos.x(), faceLocation.pos.y(), faceLocation.width, faceLocation.width));
+                    points.append(QPointF(currentEyesLocations.front().first.x(), currentEyesLocations.front().first.y()));
+                    points.append(QPointF(currentEyesLocations.front().second.x(), currentEyesLocations.front().second.y()));
+                    dst += src.m();
+                    if (!Globals->enrollAll) break;
                 }
-
-                if (any_eyes && !Globals->enrollAll && !dst.isEmpty()) break;
             }
             // If eye detection failed, mark the output as a failure
-            if (!any_eyes) {
-                dst.file.setBool("FTE");
-                return;
+            if (dst.isEmpty()) {
+                dst.file.set("FTE", true);
+                if (!Globals->enrollAll) dst += Mat();
             }
-
-            dst.file.setROIs(ROIs);
-            dst.file.setLandmarks(landmarks);
+            dst.file.appendRects(rects);
+            dst.file.appendPoints(points);
         } catch (std::exception &e) {
             qFatal("CT8Enroll Exception: %s", e.what());
         }
-
-        if (!Globals->enrollAll && dst.isEmpty()) dst += Mat();
-    }
-private:
-    BR_PROPERTY(float, minRelEyeDistance, 0.01f)
-    BR_PROPERTY(float, maxRelEyeDistance, 0.4f)
+    }    
 };
-BR_REGISTER(Transform, CT8Detect)
+BR_REGISTER(Transform, CT8DetectTransform)
 /*!
  * \ingroup transforms
@@ -374,10 +355,11 @@ BR_REGISTER(Transform, CT8Detect)
  * \author Josh Klontz \cite jklontz
  * \author Charles Otto \cite caotto
  */
-struct CT8Enroll : public UntrainableTransform
-                 , public CT8Context
+class CT8EnrollTransform : public UntrainableTransform
+                         , public CT8Context
 {
     Q_OBJECT
+
     // enroll an image using the facevacs sdk. Generates a facevacs "fir" which
     // is their face representation.
     void project(const Template &src, Template &dst) const
@@ -387,37 +369,31 @@ struct CT8Enroll : public UntrainableTransform
             FRsdk::Image img(i);
             // If we already have eye locations, use them 
-            QList<QPointF> landmarks = src.file.landmarks();
-            bool enroll_succeeded = false;
-            if (landmarks.size() == 2) {
-                enroll_succeeded = enroll(img, FRsdk::Eyes::Location(toPosition(landmarks[0]), toPosition(landmarks[1])), &(dst.m()));
+            QList<QPointF> points = src.file.points();
+            bool enrollSucceeded = false;
+            if (points.size() == 2) {
+                enrollSucceeded = enroll(img, FRsdk::Eyes::Location(toPosition(points[0]), toPosition(points[1])), &(dst.m()));
                 // Transfer previously detectd eye and face locations to the output dst.
-                dst.file.insert("CT8_First_Eye_X", landmarks[0].x());
-                dst.file.insert("CT8_First_Eye_Y", landmarks[0].y());
-                dst.file.insert("CT8_Second_Eye_X", landmarks[1].x());
-                dst.file.insert("CT8_Second_Eye_Y", landmarks[1].y());
-
-                QList<QRectF> ROIs = src.file.ROIs();
-                if (ROIs.size() == 1) {
-                    dst.file.insert("CT8_Face_X", ROIs.first().x());
-                    dst.file.insert("CT8_Face_Y", ROIs.first().y());
-                    dst.file.insert("CT8_Face_Width", ROIs.first().width());
-                    dst.file.insert("CT8_Face_Height", ROIs.first().height());
-                }
+                dst.file.set("First_Eye", points[0]);
+                dst.file.set("Second_Eye", points[1]);
+
+                QList<QRectF> rects = src.file.rects();
+                if (rects.size() == 1)
+                    dst.file.set("Face", rects.first());
             } else {
                 // If we don't have eye locations already, calling enroll here
                 // will cause facevacs to perform detection using default
                 // parameters (and we will not receive the detected locations
                 // as output).
-                enroll_succeeded = enroll(img, &(dst.m()));
+                enrollSucceeded = enroll(img, &(dst.m()));
             }
+
             // If enrollment failed, mark this image as a failure. This will
             // typically only happen if we aren't using pre-detected eye
             // locations
-            if (!enroll_succeeded)
-            {
-                dst.file.setBool("FTE");
+            if (!enrollSucceeded) {
+                dst.file.set("FTE", true);
                 dst.m() = Mat();
             }
         } catch (std::exception &e) {
@@ -426,7 +402,7 @@ struct CT8Enroll : public UntrainableTransform
     }
 };
-BR_REGISTER(Transform, CT8Enroll)
+BR_REGISTER(Transform, CT8EnrollTransform)
 /*!
  * \ingroup distances
@@ -32,14 +32,14 @@ namespace br
 class DrawTransform : public UntrainableTransform
 {
     Q_OBJECT
-    Q_PROPERTY(bool verbose READ get_verbose WRITE set_verbose RESET reset_verbose STORED false)
     Q_PROPERTY(bool named READ get_named WRITE set_named RESET reset_named STORED false)
-    Q_PROPERTY(bool unnamed READ get_unnamed WRITE set_unnamed RESET reset_unnamed STORED false)
-    Q_PROPERTY(bool ROI READ get_ROI WRITE set_ROI RESET reset_ROI STORED false)
-    BR_PROPERTY(bool, verbose, false)
+    Q_PROPERTY(bool verbose READ get_verbose WRITE set_verbose RESET reset_verbose STORED false)
+    Q_PROPERTY(bool points READ get_points WRITE set_points RESET reset_points STORED false)
+    Q_PROPERTY(bool rects READ get_rects WRITE set_rects RESET reset_rects STORED false)
     BR_PROPERTY(bool, named, true)
-    BR_PROPERTY(bool, unnamed, true)
-    BR_PROPERTY(bool, ROI, true)
+    BR_PROPERTY(bool, verbose, false)
+    BR_PROPERTY(bool, points, true)
+    BR_PROPERTY(bool, rects, true)
     void project(const Template &src, Template &dst) const
     {
@@ -47,26 +47,18 @@ class DrawTransform : public UntrainableTransform
         const Scalar verboseColor(255, 255, 0);
         dst = src.m().clone();
-        QList<Point2f> landmarks = OpenCVUtils::toPoints(src.file.points());
-
-        if (unnamed) {
-            foreach (const Point2f &landmark, landmarks)
-                circle(dst, landmark, 3, color, -1);
-        }
-        if (named) {
-            QList<Point2f> namedLandmarks = OpenCVUtils::toPoints(src.file.namedPoints());
-            foreach (const Point2f &landmark, namedLandmarks)
-                circle(dst, landmark, 3, color);
+        if (points) {
+            const QList<Point2f> pointsList = OpenCVUtils::toPoints(named ? src.file.namedPoints() : src.file.points());
+            for (int i=0; i<pointsList.size(); i++) {
+                const Point2f &point = pointsList[i];
+                circle(dst, point, 3, color);
+                if (verbose) putText(dst, QString::number(i).toStdString(), point, FONT_HERSHEY_SIMPLEX, 0.5, verboseColor, 1);
+            }
         }
-        if (ROI) {
-            QList<Rect> ROIs = OpenCVUtils::toRects(src.file.rects());
-            foreach (const Rect ROI, ROIs)
-                rectangle(dst, ROI, color);
+        if (rects) {
+            foreach (const Rect &rect, OpenCVUtils::toRects(named ? src.file.namedRects() : src.file.rects()))
+                rectangle(dst, rect, color);
         }
-
-        if (verbose)
-            for (int i=0; i<landmarks.size(); i++)
-                putText(dst, QString::number(i).toStdString(), landmarks[i], FONT_HERSHEY_SIMPLEX, 0.5, verboseColor, 1);
     }
 };
@@ -182,11 +182,12 @@ private:
         float second_eye_x = (right_rect.x + maxLoc.x)*gray.cols/width+roi.x;
         float second_eye_y = (right_rect.y + maxLoc.y)*gray.rows/height+roi.y;
-        dst = src;
+        dst.m() = src.m();
         dst.file.appendPoint(QPointF(first_eye_x, first_eye_y));
         dst.file.appendPoint(QPointF(second_eye_x, second_eye_y));
-        dst.file.set("ASEF_Right_Eye", QPointF(first_eye_x, first_eye_y));
-        dst.file.set("ASEF_Left_Eye", QPointF(second_eye_x, second_eye_y));
+        dst.file.set("First_Eye", QPointF(first_eye_x, first_eye_y));
+        dst.file.set("Second_Eye", QPointF(second_eye_x, second_eye_y));
+        dst.file.set("Face", QRect(roi.x, roi.y, roi.width, roi.height));
     }
 };
@@ -345,6 +345,10 @@ class csvGallery : public Gallery
                 if (!samples.contains(key))
                     samples.insert(key, file.value(key));
+        // Don't create columns in the CSV for these special fields
+        samples.remove("Points");
+        samples.remove("Rects");
+
         QStringList lines;
         lines.reserve(files.size()+1);
@@ -164,91 +164,6 @@ class IntegralHistTransform : public UntrainableTransform
 BR_REGISTER(Transform, IntegralHistTransform)
-/*!
- * \ingroup transforms
- * \brief Detects regions of low variance
- * \author Josh Klontz \cite jklontz
- */
-class VarianceChangeDetectorTransform : public UntrainableTransform
-{
-    Q_OBJECT
-    Q_PROPERTY(int bins READ get_bins WRITE set_bins RESET reset_bins STORED false)
-    Q_PROPERTY(int radius READ get_radius WRITE set_radius RESET reset_radius STORED false)
-    BR_PROPERTY(int, bins, 256)
-    BR_PROPERTY(int, radius, 16)
-
-    float stddev(const Mat &integral, int i, int j, int scale, int *buffer) const
-    {
-        const float count = scale*scale*radius*radius;
-
-        float mean = 0;
-        for (int k=0; k<bins; k++) {
-            buffer[k] = integral.at<qint32>(i+scale,(j+scale)*bins+k)
-                      - integral.at<qint32>(i+scale, j       *bins+k)
-                      - integral.at<qint32>(i      ,(j+scale)*bins+k)
-                      + integral.at<qint32>(i      , j       *bins+k);
-            mean += k*buffer[k];
-        }
-        mean /= count;
-
-        float variance = 0;
-        for (int k=0; k<bins; k++)
-            variance += buffer[k] * (k-mean) * (k-mean);
-
-        return sqrt(variance/count);
-    }
-
-    void project(const Template &src, Template &dst) const
-    {
-        const Mat &m = src.m();
-        if (m.type() != CV_32SC1) qFatal("VarianceChangeDetector requires CV_32SC1 images from IntegralHist");
-
-        int *buffer = new int[bins];
-
-        float bestRatio = -std::numeric_limits<float>::max();
-        QRectF bestRect;
-
-        const int rows = m.rows;
-        const int cols = m.cols/bins;
-        const int maxSize = min(m.rows, m.cols/bins);
-        int scale = 2;
-        while (scale < maxSize) {
-            const int step = std::max(1, scale/6);
-            for (int i=0; i+scale < rows; i+=step) {
-                for (int j=0; j+scale < cols; j+=step) {
-                    float internalStdDev = stddev(m, i, j, scale, buffer);
-                    float externalStdDev = std::numeric_limits<float>::max();
-                    externalStdDev = std::min(externalStdDev, ((i-2*scale >= 0)   && (j-2*scale >= 0))   ? stddev(m, i-2*scale, j-2*scale, scale, buffer) : 0);
-                    externalStdDev = std::min(externalStdDev,  (i-2*scale >= 0)                          ? stddev(m, i-2*scale, j        , scale, buffer) : 0);
-                    externalStdDev = std::min(externalStdDev, ((i-2*scale >= 0)   && (j+3*scale < cols)) ? stddev(m, i-2*scale, j+2*scale, scale, buffer) : 0);
-                    externalStdDev = std::min(externalStdDev,                        (j+3*scale < cols)  ? stddev(m, i        , j+2*scale, scale, buffer) : 0);
-                    externalStdDev = std::min(externalStdDev, ((i+3*scale < rows) && (j+3*scale < cols)) ? stddev(m, i+2*scale, j+2*scale, scale, buffer) : 0);
-                    externalStdDev = std::min(externalStdDev,  (i+3*scale < rows)                        ? stddev(m, i+2*scale, j        , scale, buffer) : 0);
-                    externalStdDev = std::min(externalStdDev, ((i+3*scale < rows) && (j-2*scale >= 0))   ? stddev(m, i+2*scale, j-2*scale, scale, buffer) : 0);
-                    externalStdDev = std::min(externalStdDev,                        (j-2*scale >= 0)    ? stddev(m, i        , j-2*scale, scale, buffer) : 0);
-
-                    float ratio;
-                    if      (externalStdDev == 0) ratio = 0;
-                    else if (internalStdDev == 0) ratio = std::numeric_limits<float>::max() * (float(scale)/float(maxSize));
-                    else                          ratio = scale*scale * pow(externalStdDev,2) / pow(internalStdDev, 2);
-
-                    if (ratio > bestRatio) {
-                        bestRatio = ratio;
-                        bestRect = QRect(j*radius, i*radius, scale*radius, scale*radius);
-                    }
-                }
-            }
-            scale = std::max(scale+1, int(scale*1.25));
-        }
-
-        delete[] buffer;
-        dst.file.appendRect(bestRect);
-        dst.file.setLabel(bestRatio);
-    }
-};
-
-BR_REGISTER(Transform, VarianceChangeDetectorTransform)
-
 } // namespace br
 #include "hist.moc"
 #include <opencv2/imgproc/imgproc.hpp>
+#include <Eigen/Core>
 #include <openbr_plugin.h>
+using namespace cv;
+
 namespace br
 {
@@ -15,7 +18,7 @@ class IntegralTransform : public UntrainableTransform
     void project(const Template &src, Template &dst) const
     {
-        cv::integral(src, dst);
+        integral(src, dst);
     }
 };
@@ -23,6 +26,71 @@ BR_REGISTER(Transform, IntegralTransform)
 /*!
  * \ingroup transforms
+ * \brief Sliding window object recognition from a multi-channel intergral image.
+ * \author Josh Klontz \cite jklontz
+ */
+class IntegralSampler : public UntrainableTransform
+{
+    Q_OBJECT
+    Q_PROPERTY(int scales READ get_scales WRITE set_scales RESET reset_scales STORED false)
+    Q_PROPERTY(float scaleFactor READ get_scaleFactor WRITE set_scaleFactor RESET reset_scaleFactor STORED false)
+    Q_PROPERTY(float stepFactor READ get_stepFactor WRITE set_stepFactor RESET reset_stepFactor STORED false)
+    Q_PROPERTY(int minSize READ get_minSize WRITE set_minSize RESET reset_minSize STORED false)
+    BR_PROPERTY(int, scales, 1)
+    BR_PROPERTY(float, scaleFactor, 1.25)
+    BR_PROPERTY(float, stepFactor, 0.25)
+    BR_PROPERTY(int, minSize, 8)
+
+    void project(const Template &src, Template &dst) const
+    {
+        typedef Eigen::Map< const Eigen::Matrix<qint32,Eigen::Dynamic,1> > InputDescriptor;
+        typedef Eigen::Map< Eigen::Matrix<qint32,Eigen::Dynamic,1> > OutputDescriptor;
+        const Mat &m = src.m();
+        if (m.depth() != CV_32S) qFatal("Expected CV_32S matrix depth.");
+        const int channels = m.channels();
+        const int rowStep = channels * m.cols;
+
+        int descriptors = 0;
+        int currentSize = min(m.rows, m.cols)-1;
+        for (int scale=0; scale<scales; scale++) {
+            descriptors += ceil((m.rows-currentSize)*stepFactor/currentSize) *
+                    ceil((m.cols-currentSize)*stepFactor/currentSize);
+            currentSize /= scaleFactor;
+            if (currentSize < minSize)
+                break;
+        }
+        Mat n(descriptors, channels, CV_32SC1);
+
+        const qint32 *dataIn = (qint32*)m.data;
+        qint32 *dataOut = (qint32*)n.data;
+        currentSize = min(m.rows, m.cols)-1;
+        int index = 0;
+        for (int scale=0; scale<scales; scale++) {
+            const int currentStep = currentSize * stepFactor;
+            for (int i=currentSize; i<m.rows; i+=currentStep) {
+                for (int j=currentSize; j<m.cols; j+=currentStep) {
+                    InputDescriptor a(dataIn+((i-currentSize)*rowStep+(j-currentSize)*channels), channels, 1);
+                    InputDescriptor b(dataIn+((i-currentSize)*rowStep+ j             *channels), channels, 1);
+                    InputDescriptor c(dataIn+( i             *rowStep+(j-currentSize)*channels), channels, 1);
+                    InputDescriptor d(dataIn+( i             *rowStep+ j             *channels), channels, 1);
+                    OutputDescriptor y(dataOut+(index*channels), channels, 1);
+                    y = d-b-c+a;
+                    index++;
+                }
+            }
+            currentSize /= scaleFactor;
+            if (currentSize < minSize)
+                break;
+        }
+
+        dst.m() = n;
+    }
+};
+
+BR_REGISTER(Transform, IntegralSampler)
+
+/*!
+ * \ingroup transforms
  * \brief Computes magnitude and/or angle of image.
  * \author Josh Klontz \cite jklontz
  */
@@ -41,10 +109,10 @@ private:
     void project(const Template &src, Template &dst) const
     {
         if (src.m().type() != CV_8UC1) qFatal("Requires CV_8UC1 input.");
-        cv::Mat dx, dy, magnitude, angle;
-        cv::Sobel(src, dx, CV_32F, 1, 0);
-        cv::Sobel(src, dy, CV_32F, 0, 1);
-        cv::cartToPolar(dx, dy, magnitude, angle, true);
+        Mat dx, dy, magnitude, angle;
+        Sobel(src, dx, CV_32F, 1, 0);
+        Sobel(src, dy, CV_32F, 0, 1);
+        cartToPolar(dx, dy, magnitude, angle, true);
         if ((channel == Magnitude) || (channel == MagnitudeAndAngle))
             dst.append(magnitude);
         if ((channel == Angle) || (channel == MagnitudeAndAngle))
@@ -136,13 +136,13 @@ class NEC3Enroll : public UntrainableTransform
                 NeoFacePro::CFaceFeature::FreeSerializeData(data);
             }
-            if (src.file.getBool("ForceEnrollment") && !dst.isEmpty()) break;
+            if (src.file.get<bool>("ForceEnrollment", false) && !dst.isEmpty()) break;
         }
-        dst.file.appendLandmarks(landmarks);
+        dst.file.appendPoints(landmarks);
         contexts.release(context);
-        if (!src.file.getBool("enrollAll") && dst.isEmpty()) dst += cv::Mat();
+        if (!src.file.get<bool>("enrollAll", false) && dst.isEmpty()) dst += cv::Mat();
     }
 };
@@ -79,7 +79,7 @@ struct KDE
     double mean, stddev;
     QList<float> bins;
-    KDE() : min(0), max(1) {}
+    KDE() : min(0), max(1), mean(0), stddev(1) {}
     KDE(const QList<float> &scores)
     {
         Common::MinMax(scores, &min, &max);
@@ -111,6 +111,26 @@ BR_REGISTER(Transform, CatTransform)
 /*!
  * \ingroup transforms
+ * \brief Wraps OpenCV merge
+ * \author Josh Klontz \cite jklontz
+ */
+class MergeTransform : public UntrainableMetaTransform
+{
+    Q_OBJECT
+
+    void project(const Template &src, Template &dst) const
+    {
+        std::vector<Mat> mv;
+        foreach (const Mat &m, src)
+            mv.push_back(m);
+        merge(mv, dst);
+    }
+};
+
+BR_REGISTER(Transform, MergeTransform)
+
+/*!
+ * \ingroup transforms
  * \brief Duplicates the template data.
  * \author Josh Klontz \cite jklontz
  */
+#include <QProcess>
 #include <openbr_plugin.h>
 #include "core/common.h"
@@ -16,16 +17,6 @@ class YouTubeFacesDBTransform : public UntrainableMetaTransform
     Q_PROPERTY(QString algorithm READ get_algorithm WRITE set_algorithm RESET reset_algorithm STORED false)
     BR_PROPERTY(QString, algorithm, "")
-    QSharedPointer<Transform> transform;
-    QSharedPointer<Distance> distance;
-
-    void init()
-    {
-        if (algorithm.isEmpty()) return;
-        transform = Transform::fromAlgorithm(algorithm);
-        distance = Distance::fromAlgorithm(algorithm);
-    }
-
     void project(const TemplateList &src, TemplateList &dst) const
     {
         Transform::project(src.mid(1) /* First template is the header in 'splits.txt' */, dst);
@@ -33,22 +24,19 @@ class YouTubeFacesDBTransform : public UntrainableMetaTransform
     void project(const Template &src, Template &dst) const
     {
+        static QMutex mutex;
         const QStringList words = src.file.name.split(", ");
-        dst.file.name = words[0] + "_" + words[1] + "_" + words[4] + ".mtx";
-
-        TemplateList queryTemplates = TemplateList::fromGallery(File(words[2]).resolved());
-        sort(queryTemplates);
-        queryTemplates >> *transform;
-
-        TemplateList targetTemplates = TemplateList::fromGallery(File(words[3]).resolved());
-        sort(targetTemplates);
-        targetTemplates >> *transform;
-
-        QScopedPointer<MatrixOutput> memoryOutput(MatrixOutput::make(targetTemplates.files(), queryTemplates.files()));
-        distance->compare(targetTemplates, queryTemplates, memoryOutput.data());
-
-        dst.clear();
-        dst.m() = memoryOutput.data()->data;
+        const QString matrix = "YTF-"+algorithm+"/"+words[0] + "_" + words[1] + "_" + words[4] + ".mtx";
+        const QStringList arguments = QStringList() << "-algorithm" << algorithm
+                                                    << "-parallelism" << QString::number(Globals->parallelism)
+                                                    << "-path" << Globals->path
+                                                    << "-compare" << File(words[2]).resolved() << File(words[3]).resolved() << matrix;
+        mutex.lock();
+        int result = QProcess::execute(QCoreApplication::applicationFilePath(), arguments);
+        mutex.unlock();
+        if (result != 0)
+            qWarning("Process for computing %s returned %d.", qPrintable(matrix), result);
+        dst = Template();
     }
     static void sort(TemplateList &templates)