Output top impostor matches and bottom genuine matches from eval, plot the matches in pdf.

bhklein
1 parent 33dd7d19
Showing 6 changed files with 99 additions and 19 deletions
app/br/br.cpp
openbr/core/eval.cpp
openbr/core/eval.h
openbr/core/plot.cpp
openbr/openbr.cpp
openbr/openbr.h
@@ -98,14 +98,27 @@ public:
                 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 <= 3), "Incorrect parameter count for 'eval'.");
+                check((parc >= 1) && (parc <= 4), "Incorrect parameter count for 'eval'.");
                 if (parc == 1) {
-                    br_eval(parv[0], "", "");
+                    br_eval(parv[0], "", "", 0);
                 } else if (parc == 2) {
-                    if (br::File(parv[1]).suffix() == "csv") br_eval(parv[0], "", parv[1]);
-                    else                                     br_eval(parv[0], parv[1], "");
+                    if (br::File(parv[1]).suffix() == "csv") {
+                        br_eval(parv[0], "", parv[1], 0);
+                    } else if (br::File(parv[1]).suffix() == "mask") {
+                        br_eval(parv[0], parv[1], "", 0);
+                    } else {
+                        br_eval(parv[0], "", "", atoi(parv[1]));
+                    }
+                } else if (parc == 3) {
+                    if (br::File(parv[2]).suffix() == "csv") {
+                        br_eval(parv[0], parv[1], parv[2], 0);
+                    } else if ( br::File(parv[1]).suffix() == "csv") {
+                        br_eval(parv[0], "", parv[1], atoi(parv[2]));
+                    } else {
+                        br_eval(parv[0], parv[1], "", atoi(parv[2]));
+                    }
                 } else {
-                    br_eval(parv[0], parv[1], parv[2]);
+                    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'.");
@@ -235,7 +248,7 @@ private:
                "-train <gallery> ... <gallery> [{model}]\n"
                "-enroll <input_gallery> ... <input_gallery> {output_gallery}\n"
                "-compare <target_gallery> <query_gallery> [{output}]\n"
-               "-eval <simmat> [<mask>] [{csv}]\n"
+               "-eval <simmat> [<mask>] [{csv}] [{matches}]\n"
                "-plot <file> ... <file> {destination}\n"
                "\n"
                "==== Other Commands ====\n"
@@ -100,10 +100,10 @@ static cv::Mat constructMatchingMask(const cv::Mat &amp;scores, const FileList &amp;targ
 float Evaluate(const cv::Mat &scores, const FileList &target, const FileList &query, const QString &csv, int partition)
 {
-    return Evaluate(scores, constructMatchingMask(scores, target, query, partition), csv);
+    return Evaluate(scores, constructMatchingMask(scores, target, query, partition), target, query, csv, true);
 }
-float Evaluate(const QString &simmat, const QString &mask, const QString &csv)
+float Evaluate(const QString &simmat, const QString &mask, const QString &csv, bool matches)
 {
     qDebug("Evaluating %s%s%s",
            qPrintable(simmat),
@@ -137,10 +137,10 @@ float Evaluate(const QString &amp;simmat, const QString &amp;mask, const QString &amp;csv)
         truth = format->read();
     }
-    return Evaluate(scores, truth, csv);
+    return Evaluate(scores, truth, TemplateList::fromGallery(target).files(), TemplateList::fromGallery(query).files(), csv, matches);
 }
-float Evaluate(const Mat &simmat, const Mat &mask, const QString &csv)
+float Evaluate(const Mat &simmat, const Mat &mask, const FileList &target, const FileList &query, const QString &csv, bool matches)
 {
     if (simmat.size() != mask.size())
         qFatal("Similarity matrix (%ix%i) differs in size from mask matrix (%ix%i).",
@@ -154,6 +154,10 @@ float Evaluate(const Mat &amp;simmat, const Mat &amp;mask, const QString &amp;csv)
     float result = -1;
+    // Lists of top impostors and worst genuine
+    QList<Comparison> topImpostors; topImpostors.reserve(10);
+    QList<Comparison> botGenuines; botGenuines.reserve(10);
+    
     // Make comparisons
     QList<Comparison> comparisons; comparisons.reserve(simmat.rows*simmat.cols);
     int genuineCount = 0, impostorCount = 0, numNaNs = 0;
@@ -163,9 +167,30 @@ float Evaluate(const Mat &amp;simmat, const Mat &amp;mask, const QString &amp;csv)
             const BEE::SimmatValue simmat_val = simmat.at<BEE::SimmatValue>(i,j);
             if (mask_val == BEE::DontCare) continue;
             if (simmat_val != simmat_val) { numNaNs++; continue; }
-            comparisons.append(Comparison(simmat_val, j, i, mask_val == BEE::Match));
-            if (comparisons.last().genuine) genuineCount++;
-            else                            impostorCount++;
+            Comparison comparison(simmat_val, j, i, mask_val == BEE::Match);
+            comparisons.append(comparison);
+            if (comparison.genuine) {
+                genuineCount++;
+                if (botGenuines.size() < 10) {
+                    botGenuines.append(comparison);
+                    std::sort(botGenuines.begin(), botGenuines.end());
+                } else if (comparison.score < botGenuines.first().score) {
+                    botGenuines.removeFirst();
+                    botGenuines.append(comparison);
+                    std::sort(botGenuines.begin(), botGenuines.end());
+                }
+            } else {
+                impostorCount++;
+                if (topImpostors.size() < 10) {
+                    topImpostors.append(comparison);
+                    std::sort(topImpostors.begin(), topImpostors.end());
+                } else if (topImpostors.last().score < comparison.score) {
+                    topImpostors.removeLast();
+                    topImpostors.append(comparison);
+                    std::sort(topImpostors.begin(), topImpostors.end());
+                }
+
+            }                           
         }
     }
@@ -234,6 +259,18 @@ float Evaluate(const Mat &amp;simmat, const Mat &amp;mask, const QString &amp;csv)
     lines.append("Metadata,"+QString::number(impostorCount)+",Impostor");
     lines.append("Metadata,"+QString::number(simmat.cols*simmat.rows-(genuineCount+impostorCount))+",Ignored");
+    QString filePath = Globals->path;
+    if (matches) {
+        for (int i=0; i<topImpostors.size(); i++) {
+            lines.append("TI,"+QString::number(topImpostors[i].score)+","+target[topImpostors[i].target].get<QString>("Label")+":"
+                +filePath+"/"+target[topImpostors[i].target].name+":"+query[topImpostors[i].query].get<QString>("Label")+":"+filePath+"/"+query[topImpostors[i].query].name);
+        }
+        for (int i=0; i<botGenuines.size(); i++) {
+            lines.append("BG,"+QString::number(botGenuines[i].score)+","+target[botGenuines[i].target].get<QString>("Label")+":"
+                +filePath+"/"+target[botGenuines[i].target].name+":"+query[botGenuines[i].query].get<QString>("Label")+":"+filePath+"/"+query[botGenuines[i].query].name);
+        }
+    }
+
     // Write Detection Error Tradeoff (DET), PRE, REC
     int points = qMin(operatingPoints.size(), Max_Points);
     for (int i=0; i<points; i++) {
@@ -292,7 +329,13 @@ float Evaluate(const Mat &amp;simmat, const Mat &amp;mask, const QString &amp;csv)
     }
     QtUtils::writeFile(csv, lines);
-    qDebug("TAR @ FAR = 0.01: %.3f\nRetrieval Rate @ Rank = %d: %.3f", result, Report_Retrieval, getCMC(firstGenuineReturns, Report_Retrieval));
+    qDebug("TAR @ FAR = 0.01:    %.3f",getTAR(operatingPoints, 0.01));
+    qDebug("TAR @ FAR = 0.001:   %.3f",getTAR(operatingPoints, 0.001));
+    qDebug("TAR @ FAR = 0.0001:  %.3f",getTAR(operatingPoints, 0.0001));
+    qDebug("TAR @ FAR = 0.00001: %.3f",getTAR(operatingPoints, 0.00001));
+
+    qDebug("\nRetrieval Rate @ Rank = %d: %.3f", Report_Retrieval, getCMC(firstGenuineReturns, Report_Retrieval));
+    
     return result;
 }
@@ -23,9 +23,9 @@
 namespace br
 {
-    float Evaluate(const QString &simmat, const QString &mask = "", const QString &csv = ""); // Returns TAR @ FAR = 0.001
+    float Evaluate(const QString &simmat, const QString &mask = "", const QString &csv = "", bool matches = false); // Returns TAR @ FAR = 0.001
     float Evaluate(const cv::Mat &scores, const FileList &target, const FileList &query, const QString &csv = "", int parition = 0);
-    float Evaluate(const cv::Mat &scores, const cv::Mat &masks, const QString &csv = "");
+    float Evaluate(const cv::Mat &scores, const cv::Mat &masks, const FileList &target, const FileList &query, const QString &csv = "", bool matches = false);
     float InplaceEval(const QString & simmat, const QString & target, const QString & query, const QString & csv = "");
     void EvalClassification(const QString &predictedGallery, const QString &truthGallery, QString predictedProperty = "", QString truthProperty = "");
@@ -148,6 +148,8 @@ struct RPlot
                        "# Split data into individual plots\n"
                        "plot_index = which(names(data)==\"Plot\")\n"
                        "Metadata <- data[grep(\"Metadata\",data$Plot),-c(1)]\n"
+                       "TI <- data[grep(\"TI\",data$Plot),-c(1)]\n"
+                       "BG <- data[grep(\"BG\",data$Plot),-c(1)]\n"
                        "DET <- data[grep(\"DET\",data$Plot),-c(1)]\n"
                        "FAR <- data[grep(\"FAR\",data$Plot),-c(1)]\n"
                        "FRR <- data[grep(\"FRR\",data$Plot),-c(1)]\n"
@@ -163,6 +165,8 @@ struct RPlot
                        "\n"
                        "# Format data\n"
                        "Metadata$Y<-factor(Metadata$Y, levels=c(\"Genuine\",\"Impostor\",\"Ignored\",\"Gallery\",\"Probe\"))\n"
+                       "TI$Y <- as.character(TI$Y)\n"
+                       "BG$Y <- as.character(BG$Y)\n"
                        "DET$Y <- as.numeric(as.character(DET$Y))\n"
                        "ERR$Y <- as.numeric(as.character(ERR$Y))\n"
                        "SD$Y <- as.factor(unique(as.character(SD$Y)))\n"
@@ -317,6 +321,25 @@ bool Plot(const QStringList &amp;files, const File &amp;destination, bool show)
                             ((p.flip ? p.minor.size : p.major.size) > 1 ? QString(" + facet_wrap(~ %1, scales=\"free_x\")").arg(p.flip ? p.minor.header : p.major.header) : QString()) +
                             QString(" + theme(aspect.ratio=1)\n\n")));
+    p.file.write(qPrintable(QString("if (nrow(TI) != 0) {\n\tlibrary(jpeg)\n\tlibrary(png)\n\tlibrary(grid)\n\t") +
+                            QString("multiplot <- function(..., plotlist=NULL, cols) {\n\t") +
+                            QString("\trequire(grid)\n\n\t\t# Make a list from the ... arguments and plotlist\n\t\tplots <- c(list(...), plotlist)\n") + 
+                            QString("\t\tnumPlots = length(plots)\n\n\t\t# Make the panel\n\t\tplotCols = cols\n\t\tplotRows = ceiling(numPlots/plotCols)\n\n") +
+                            QString("\t\t# Set up the page\n\t\tgrid.newpage()\n\t\tpushViewport(viewport(layout = grid.layout(plotRows, plotCols)))\n\t\tvplayout <- function(x, y)\n\t\t\tviewport(layout.pos.row = x, layout.pos.col = y)\n\n") +
+                            QString("\t\t# Make each plot, in the correct location\n\t\tfor (i in 1:numPlots) {\n\t\t\tcurRow = ceiling(i/plotCols)\n\t\t\tcurCol = (i-1) %% plotCols + 1\n\t\t\tprint(plots[[i]], vp = vplayout(curRow, curCol))\n\t\t}\n\t}\n\n")));
+    
+    p.file.write(qPrintable(QString("\t# Print top impostor matches\n\tfor (i in 1:nrow(TI)) {\n\t\tscore <- TI[i,1]\n\t\tfiles <- TI[i,2]\n\t\talg <- TI[i,3]\n\t\tfiles <- unlist(strsplit(files, \"[:]\"))\n\n\t\t") +
+                            QString("name1 <- files[1]\n\t\timg1 <- readJPEG(files[2])\n\t\tname2 <- files[3]\n\t\timg2 <- readJPEG(files[4])\n\n\t\tg1 <- rasterGrob(img1, interpolate=TRUE)\n\t\tg2 <- rasterGrob(img2, interpolate=TRUE)\n\n\t\t") +
+                            QString("plot1 <- qplot(1:10, 1:10, geom=\"blank\") + annotation_custom(g1, xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) + theme(axis.line=element_blank(), axis.text.x=element_blank(), axis.text.y=element_blank(), axis.ticks=element_blank(), panel.background=element_blank()) + labs(title=alg) + ylab(files[2]) + xlab(name1)\n\t\t") +
+                            QString("plot2 <- qplot(1:10, 1:10, geom=\"blank\") + annotation_custom(g2, xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) + theme(axis.line=element_blank(), axis.text.x=element_blank(), axis.text.y=element_blank(), axis.ticks=element_blank(), panel.background=element_blank()) + labs(title=paste(\"Impostor score =\", score)) + ylab(files[4]) + xlab(name2)\n\n\t\t") +
+                            QString("multiplot(plot1, plot2, cols=2)\n\t}")));
+
+    p.file.write(qPrintable(QString("\n\n\t# Print worst genuine matches\n\tfor (i in 1:nrow(BG)) {\n\t\tscore <- BG[i,1]\n\t\tfiles <- BG[i,2]\n\t\talg <- BG[i,3]\n\t\tfiles <- unlist(strsplit(files, \"[:]\"))\n\n\t\t") +
+                            QString("name1 <- files[1]\n\t\timg1 <- readJPEG(files[2])\n\t\tname2 <- files[3]\n\t\timg2 <- readJPEG(files[4])\n\n\t\tg1 <- rasterGrob(img1, interpolate=TRUE)\n\t\tg2 <- rasterGrob(img2, interpolate=TRUE)\n\n\t\t") +
+                            QString("plot1 <- qplot(1:10, 1:10, geom=\"blank\") + annotation_custom(g1, xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) + theme(axis.line=element_blank(), axis.text.x=element_blank(), axis.text.y=element_blank(), axis.ticks=element_blank(), panel.background=element_blank()) + labs(title=alg) + ylab(files[2]) + xlab(name1)\n\t\t") +
+                            QString("plot2 <- qplot(1:10, 1:10, geom=\"blank\") + annotation_custom(g2, xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) + theme(axis.line=element_blank(), axis.text.x=element_blank(), axis.text.y=element_blank(), axis.ticks=element_blank(), panel.background=element_blank()) + labs(title=paste(\"Genuine score =\", score)) + ylab(files[4]) + xlab(name2)\n\n\t\t") +
+                            QString("multiplot(plot1, plot2, cols=2)\n\t}\n}\n\n")));
+
     return p.finalize(show);
 }
@@ -104,9 +104,9 @@ void br_project(const char *input, const char *gallery)
     Project(File(input), File(gallery));
 }
-float br_eval(const char *simmat, const char *mask, const char *csv)
+float br_eval(const char *simmat, const char *mask, const char *csv, bool matches)
 {
-    return Evaluate(simmat, mask, csv);
+    return Evaluate(simmat, mask, csv, matches);
 }
 float br_inplace_eval(const char *simmat, const char *target, const char *query, const char *csv)
@@ -154,10 +154,11 @@ BR_EXPORT void br_project(const char *input, const char *output);
  * \param simmat The \ref simmat to use.
  * \param mask The \ref mask to use.
  * \param csv Optional \c .csv file to contain performance metrics.
+ * \param matches Optional bool flag to output top impostor matches and bottom genuine matches.
  * \return True accept rate at a false accept rate of one in one thousand.
  * \see br_plot
  */
-BR_EXPORT float br_eval(const char *simmat, const char *mask, const char *csv = "");
+BR_EXPORT float br_eval(const char *simmat, const char *mask, const char *csv = "", bool matches = false);
 /*!
  * \brief Creates a \c .csv file containing performance metrics from evaluating the similarity matrix using galleries containing ground truth labels