diff --git a/scripts/evalFaceRecognition-MEDS.sh b/scripts/evalFaceRecognition-MEDS.sh
index e339f92..f4dd134 100755
--- a/scripts/evalFaceRecognition-MEDS.sh
+++ b/scripts/evalFaceRecognition-MEDS.sh
@@ -1,6 +1,6 @@
 #!/bin/bash
 
-ALGORITHM=OpenBR
+ALGORITHM=FaceRecognitionHoG
 
 if [ ! -f evalFaceRecognition-MEDS.sh ]; then
   echo "Run this script from the scripts folder!"
diff --git a/scripts/trainImageRetrieval-LFW.sh b/scripts/trainImageRetrieval-LFW.sh
index b013dfc..f0f11e5 100755
--- a/scripts/trainImageRetrieval-LFW.sh
+++ b/scripts/trainImageRetrieval-LFW.sh
@@ -18,4 +18,4 @@ br -algorithm ImageRetrieval -train ~/lfw2[step=10] ../share/openbr/models/algor
 br -algorithm ImageRetrieval -compare ~/lfw2[step=10] . ImageRetrieval_LFW.mtx -eval ImageRetrieval_LFW.mtx LFW.mask Algorithm_Dataset/ImageRetrieval_LFW.csv
 br -plot Algorithm_Dataset/*_LFW.csv LFW
 
-rm -f ../share/openbr/models/algorithms/ImageRetrieval
+#rm -f ../share/openbr/models/algorithms/ImageRetrieval
diff --git a/sdk/plugins/quantize.cpp b/sdk/plugins/quantize.cpp
index 90b928d..6411e78 100644
--- a/sdk/plugins/quantize.cpp
+++ b/sdk/plugins/quantize.cpp
@@ -167,7 +167,6 @@ private:
     void train(const TemplateList &src)
     {
         Mat data = OpenCVUtils::toMat(src.data());
-        qDebug() << data.rows << data.cols;
         if (data.cols % n != 0) qFatal("Expected dimensionality to be divisible by n.");
 
         Mat &lut = ProductQuantizationLUTs[index];
@@ -186,16 +185,16 @@ private:
     void project(const Template &src, Template &dst) const
     {
         Mat m = src.m().reshape(1, 1);
-        dst = Mat(1, src.m().cols/n, CV_8UC1);
-        for (int i=0; i<m.cols/n; i++) {
-            uchar bestIndex = -1;
+        dst = Mat(1, m.cols/n, CV_8UC1);
+        for (int i=0; i<dst.m().cols; i++) {
+            int bestIndex = 0;
             double bestDistance = std::numeric_limits<double>::max();
             Mat m_i = m.colRange(i*n, (i+1)*n);
-            for (uchar i=0; i<256; i++) {
-                double distance = norm(m_i, centers[index].row(i), NORM_L2);
+            for (int j=0; j<256; j++) {
+                double distance = norm(m_i, centers[index].row(j), NORM_L2);
                 if (distance < bestDistance) {
                     bestDistance = distance;
-                    bestIndex = i;
+                    bestIndex = j;
                 }
             }
             dst.m().at<uchar>(0,i) = bestIndex;
diff --git a/sdk/plugins/regions.cpp b/sdk/plugins/regions.cpp
index 6248879..541f963 100644
--- a/sdk/plugins/regions.cpp
+++ b/sdk/plugins/regions.cpp
@@ -120,6 +120,7 @@ class MergeTransform : public UntrainableMetaTransform
 
     void project(const Template &src, Template &dst) const
     {
+        dst.file = src.file;
         std::vector<Mat> mv;
         foreach (const Mat &m, src)
             mv.push_back(m);