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

Scott Klum
2 parents 84472ab9 36c800db
Showing 7 changed files with 79 additions and 21 deletions
app/br/br.cpp
openbr/core/core.cpp
openbr/janus
openbr/janus.cpp
openbr/plugins/imgproc/cropfromlandmarks.cpp
openbr/plugins/metadata/cascade.cpp
scripts/evalFaceRecognition-LFW.sh
@@ -100,9 +100,6 @@ public:
             } else if (!strcmp(fun, "compare")) {
                 check((parc >= 2) && (parc <= 3), "Incorrect parameter count for 'compare'.");
                 br_compare(parv[0], parv[1], parc == 3 ? parv[2] : "");
-            } else if (!strcmp(fun, "pairwiseCompare")) {
-                check((parc >= 2) && (parc <= 3), "Incorrect parameter count for 'pairwiseCompare'.");
-                br_pairwise_compare(parv[0], parv[1], parc == 3 ? parv[2] : "");
             } else if (!strcmp(fun, "eval")) {
                 check((parc >= 1) && (parc <= 4), "Incorrect parameter count for 'eval'.");
                 if (parc == 1) {
@@ -126,9 +123,6 @@ public:
                 } else {
                     br_eval(parv[0], parv[1], parv[2], atoi(parv[3]));
                 }
-            } else if (!strcmp(fun, "inplaceEval")) {
-                check((parc >= 3) && (parc <= 4), "Incorrect parameter count for 'inplaceEval'.");
-                br_inplace_eval(parv[0], parv[1], parv[2], parc == 4 ? parv[3] : "");
             } else if (!strcmp(fun, "plot")) {
                 check(parc >= 2, "Incorrect parameter count for 'plot'.");
                 br_plot(parc-1, parv, parv[parc-1], true);
@@ -174,6 +168,12 @@ public:
             } else if (!strcmp(fun, "evalRegression")) {
                 check(parc >= 2 && parc <= 4, "Incorrect parameter count for 'evalRegression'.");
                 br_eval_regression(parv[0], parv[1], parc >= 3 ? parv[2] : "", parc >= 4 ? parv[3] : "");
+            } else if (!strcmp(fun, "pairwiseCompare")) {
+                check((parc >= 2) && (parc <= 3), "Incorrect parameter count for 'pairwiseCompare'.");
+                br_pairwise_compare(parv[0], parv[1], parc == 3 ? parv[2] : "");
+            } else if (!strcmp(fun, "inplaceEval")) {
+                check((parc >= 3) && (parc <= 4), "Incorrect parameter count for 'inplaceEval'.");
+                br_inplace_eval(parv[0], parv[1], parv[2], parc == 4 ? parv[3] : "");
             } else if (!strcmp(fun, "plotDetection")) {
                 check(parc >= 2, "Incorrect parameter count for 'plotDetection'.");
                 br_plot_detection(parc-1, parv, parv[parc-1], true);
@@ -257,10 +257,8 @@ private:
                "-train <gallery> ... <gallery> [{model}]\n"
                "-enroll <input_gallery> ... <input_gallery> {output_gallery}\n"
                "-compare <target_gallery> <query_gallery> [{output}]\n"
-               "-pairwiseCompare <target_gallery> <query_gallery> [{output}]\n"
                "-eval <simmat> [<mask>] [{csv}] [{matches}]\n"
-               "-inplaceEval <simmat> <target> <query> [{csv}]\n"
-               "-plot <file> ... <file> {destination}\n"
+               "-plot <csv> ... <csv> {destination}\n"
                "\n"
                "==== Other Commands ====\n"
                "-fuse <simmat> ... <simmat> (None|MinMax|ZScore|WScore) (Min|Max|Sum[W1:W2:...:Wn]|Replace|Difference|None) {simmat}\n"
@@ -275,6 +273,8 @@ private:
                "-evalDetection <predicted_gallery> <truth_gallery> [{csv}] [{normalize}] [{minSize}] [{maxSize}]\n"
                "-evalLandmarking <predicted_gallery> <truth_gallery> [{csv} [<normalization_index_a> <normalization_index_b>] [sample_index] [total_examples]]\n"
                "-evalRegression <predicted_gallery> <truth_gallery> <predicted property name> <ground truth property name>\n"
+               "-pairwiseCompare <target_gallery> <query_gallery> [{output}]\n"
+               "-inplaceEval <simmat> <target> <query> [{csv}]\n"
                "-assertEval <simmat> <mask> <accuracy>\n"
                "-plotDetection <file> ... <file> {destination}\n"
                "-plotLandmarking <file> ... <file> {destination}\n"
@@ -266,7 +266,7 @@ struct AlgorithmCore
     void retrieveOrEnroll(const File &file, QScopedPointer<Gallery> &gallery, FileList &galleryFiles)
     {
-        if (!file.getBool("enroll") && (QStringList() << "gal" << "mem" << "template" << "ut").contains(file.suffix())) {
+        if (!file.getBool("enroll") && (QStringList() << "gal" << "mem" << "template" << "t").contains(file.suffix())) {
             // Retrieve it
             gallery.reset(Gallery::make(file));
             galleryFiles = gallery->files();
@@ -443,7 +443,7 @@ struct AlgorithmCore
             colEnrolledGallery = colGallery.baseName() + colGallery.hash() + '.' + targetExtension;
             // Check if we have to do real enrollment, and not just convert the gallery's type.
-            if (!(QStringList() << "gal" << "template" << "mem" << "ut").contains(colGallery.suffix()))
+            if (!(QStringList() << "gal" << "template" << "mem" << "t").contains(colGallery.suffix()))
                 enroll(colGallery, colEnrolledGallery);
             // If the gallery does have enrolled templates, but is not the right type, we do a simple
@@ -465,7 +465,7 @@ struct AlgorithmCore
         // which compares incoming templates against a gallery, we will handle enrollment of the row set by simply
         // building a transform that does enrollment (using the current algorithm), then does the comparison in one
         // step. This way, we don't have to retain the complete enrolled row gallery in memory, or on disk.
-        else if (!(QStringList() << "gal" << "mem" << "template" << "ut").contains(rowGallery.suffix()))
+        else if (!(QStringList() << "gal" << "mem" << "template" << "t").contains(rowGallery.suffix()))
             needEnrollRows = true;
         // At this point, we have decided how we will structure the comparison (either in transpose mode, or not), 
-Subproject commit 8cdda77000209ea279093b0d4fad3988f22f0548
+Subproject commit bab25ea9b9f26791859415abe953f6df82ace86e
@@ -24,13 +24,13 @@ janus_error janus_initialize(const char *sdk_path, const char *temp_path, const 
     Globals->enrollAll = true;
     Globals->file.set(QString("temp_path"), QString(temp_path));
     const QString algorithm = model_file;
+    detect.reset(Transform::make("Cvt(Gray)+Cascade(FrontalFace,ROCMode=true)", NULL));
     if (algorithm.isEmpty()) {
-        detect.reset(Transform::make("Cvt(Gray)+Cascade(FrontalFace,ROCMode=true)", NULL));
         augment.reset(Transform::make("Cvt(Gray)+Affine(88,88,0.25,0.35)+<FaceRecognitionExtraction>+<FaceRecognitionEmbedding>+<FaceRecognitionQuantization>", NULL));
         distance = Distance::fromAlgorithm("FaceRecognition");
     } else {
-        augment.reset(Transform::make(algorithm + "Enroll", NULL));
-        distance.reset(Distance::make(algorithm + "Compare", NULL));
+        augment = Transform::fromAlgorithm(algorithm);
+        distance = Distance::fromAlgorithm(algorithm);
     }
     return JANUS_SUCCESS;
 }
+#include <openbr/plugins/openbr_internal.h>
+
+using namespace cv;
+
+namespace br
+{
+
+/*!
+ * \ingroup transforms
+ * \brief Crops around the landmarks numbers provided.
+ * \author Brendan Klare \cite bklare
+ * \param padding Percentage of height and width to pad the image.
+ */
+class CropFromLandmarksTransform : public UntrainableTransform
+{
+    Q_OBJECT
+
+    Q_PROPERTY(QList<int> indices READ get_indices WRITE set_indices RESET reset_indices STORED false)
+    Q_PROPERTY(float paddingHorizontal READ get_paddingHorizontal WRITE set_paddingHorizontal RESET reset_paddingHorizontal STORED false)
+    Q_PROPERTY(float paddingVertical READ get_paddingVertical WRITE set_paddingVertical RESET reset_paddingVertical STORED false)
+    BR_PROPERTY(QList<int>, indices, QList<int>())
+    BR_PROPERTY(float, paddingHorizontal, .1)
+    BR_PROPERTY(float, paddingVertical, .1)
+
+    void project(const Template &src, Template &dst) const
+    {
+        int minX = src.m().cols - 1,
+            maxX = 1,
+            minY = src.m().rows - 1,
+            maxY = 1;
+
+        for (int i = 0; i <indices.size(); i++) {
+            if (minX > src.file.points()[indices[i]].x())
+                minX = src.file.points()[indices[i]].x();
+            if (minY > src.file.points()[indices[i]].y())
+                minY = src.file.points()[indices[i]].y();
+            if (maxX < src.file.points()[indices[i]].x())
+                maxX = src.file.points()[indices[i]].x();
+            if (maxY < src.file.points()[indices[i]].y())
+                maxY = src.file.points()[indices[i]].y();
+        }
+
+        int padW = qRound((maxX - minX) * (paddingHorizontal / 2));
+        int padH = qRound((maxY - minY) * (paddingVertical / 2));
+
+        dst = Mat(src, Rect(minX - padW, minY - padH, (maxX - minX + 1) + padW * 2, (maxY - minY + 1) + padH * 2));
+    }
+};
+
+BR_REGISTER(Transform, CropFromLandmarksTransform)
+
+} // namespace br
+
+#include "imgproc/cropfromlandmarks.moc"
@@ -401,18 +401,22 @@ class CascadeTransform : public MetaTransform
             }
             for (int i=0; i<t.size(); i++) {
+                const int maxDetections = t.file.get<int>("MaxDetections", std::numeric_limits<int>::max());
+                const int flags = (enrollAll && (maxDetections != 1)) ? 0 : CASCADE_FIND_BIGGEST_OBJECT;
+
                 Mat m;
                 OpenCVUtils::cvtUChar(t[i], m);
                 std::vector<Rect> rects;
                 std::vector<int> rejectLevels;
                 std::vector<double> levelWeights;
-                if (ROCMode) cascade->detectMultiScale(m, rects, rejectLevels, levelWeights, 1.2, minNeighbors, (enrollAll ? 0 : CASCADE_FIND_BIGGEST_OBJECT) | CASCADE_SCALE_IMAGE, Size(minSize, minSize), Size(), true);
-                else         cascade->detectMultiScale(m, rects, 1.2, minNeighbors, enrollAll ? 0 : CASCADE_FIND_BIGGEST_OBJECT, Size(minSize, minSize));
+                if (ROCMode) cascade->detectMultiScale(m, rects, rejectLevels, levelWeights, 1.2, minNeighbors, flags | CASCADE_SCALE_IMAGE, Size(minSize, minSize), Size(), true);
+                else         cascade->detectMultiScale(m, rects, 1.2, minNeighbors, flags, Size(minSize, minSize));
                 if (!enrollAll && rects.empty())
                     rects.push_back(Rect(0, 0, m.cols, m.rows));
-                for (size_t j=0; j<rects.size(); j++) {
+                const size_t detections = std::min(size_t(maxDetections), rects.size());
+                for (size_t j=0; j<detections; j++) {
                     Template u(t.file, m);
                     if (rejectLevels.size() > j)
                         u.file.set("Confidence", rejectLevels[j]*levelWeights[j]);
@@ -20,7 +20,7 @@ if [ ! -e Algorithm_Dataset ]; then
 fi
 # Run the LFW test protocol
-br -algorithm $ALGORITHM -path ../data/LFW/img/ -crossValidate 10 -pairwiseCompare ../data/LFW/sigset/test_image_restricted_target.xml ../data/LFW/sigset/test_image_restricted_query.xml ${ALGORITHM}_LFW.mtx -convert Output ${ALGORITHM}_lfw.mtx Algorithm_Dataset/${ALGORITHM}_LFW%1.eval
+br -algorithm $ALGORITHM -path ../data/LFW/img/ -crossValidate 10 -pairwiseCompare ../data/LFW/sigset/test_image_restricted_target.xml ../data/LFW/sigset/test_image_restricted_query.xml ${ALGORITHM}_LFW.mtx -convert Output ${ALGORITHM}_LFW.mtx Algorithm_Dataset/${ALGORITHM}_LFW%1.eval
 # Plot results
-br -plot Algorithm_Dataset/* 'lfw_results.pdf[smooth=Dataset,rocOptions[yLimits=(0,1)]]'
+br -plot Algorithm_Dataset/* 'lfw_results.pdf[smooth=Dataset,rocOptions=[yLimits=(0,1)]]'