updated

cvpr_computedescriptors.m

@@ -23,9 +23,9 @@ OUT_FOLDER = 'descriptors';
 %% the idea is all your descriptors are in individual folders - within
 %% the folder specified as 'OUT_FOLDER'.
 % OUT_SUBFOLDER='avgRGB';
-% OUT_SUBFOLDER='globalRGBhisto';
+OUT_SUBFOLDER='globalRGBhisto';
 % OUT_SUBFOLDER='spatialColour';
-OUT_SUBFOLDER='spatialColourTexture';
+% OUT_SUBFOLDER='spatialColourTexture';
 
 allfiles=dir (fullfile([DATASET_FOLDER,'/Images/*.bmp']));
 for filenum=1:length(allfiles)
@@ -38,9 +38,9 @@ for filenum=1:length(allfiles)
     
     %% EXTRACT FUNCTION
 %     F=extractAvgRGB(img);
-%     F=extractGlobalColHist(img);
+    F=extractGlobalColHist(img);
 %     F=extractSpatialColour(img);
-    F=extractSpatialColourTexture(img);
+%     F=extractSpatialColourTexture(img);
     save(fout,'F');
     toc
 end

cvpr_visualsearch.m

@@ -105,7 +105,7 @@ for run=1:run_total
                 row = rows(n, :);
                 category = row(3);
 
-                if category == query_category
+                if category == query_category;
                     correct_results = correct_results + 1;
                 else
                     incorrect_results = incorrect_results + 1;
@@ -142,7 +142,7 @@ for run=1:run_total
         P_rel_n(i) = precision * i_result_relevant;
     end
 
-    sum_P_rel_n = sum(P_rel_n);
+    sum_P_rel_n = sum(P_rel_n)
     average_precision = sum_P_rel_n / CAT_HIST(1,query_category);
     
     AP_values(run) = average_precision;
@@ -160,8 +160,15 @@ for run=1:run_total
 end
 
 %% 7 Calculate MAP
-AP_values
+figure(4)
+histogram(AP_values);
+title('Average Precision Distribution');
+ylabel('Count');
+xlabel('Average Precision');
+xlim([0, 1]);
+
 MAP = mean(AP_values)
+AP_sd = std(AP_values)
 
 figure(2)
 plot(1:run_total, AP_values);

descriptor/extractGlobalColHist.m

@@ -1,6 +1,6 @@
 function F=extractGlobalColHist(img)
 
-divs = 4;
+divs = 8;
 
 qimg = floor(img .* divs);
 bin = qimg(:,:,1) * divs^2 + qimg(:,:,2) * divs^1 + qimg(:,:,3);

report/coursework.lyx

@@ -121,7 +121,7 @@ LatexCommand tableofcontents
 \end_layout
 
 \begin_layout Section
-Theoretical Implementations
+Theory
 \end_layout
 
 \begin_layout Section
@@ -132,5 +132,24 @@ Results
 Conclusions
 \end_layout
 
+\begin_layout Standard
+\begin_inset Newpage pagebreak
+\end_inset
+
+
+\end_layout
+
+\begin_layout Standard
+\begin_inset CommandInset bibtex
+LatexCommand bibtex
+btprint "btPrintCited"
+bibfiles "references"
+options "plain"
+
+\end_inset
+
+
+\end_layout
+
 \end_body
 \end_document

report/coursework.lyx~

@@ -96,6 +96,14 @@ Andy Pack (6420013)
 
 \end_layout
 
+\begin_layout Section*
+Abstract
+\end_layout
+
+\begin_layout Standard
+abstract
+\end_layout
+
 \begin_layout LyX-Code
 \begin_inset CommandInset toc
 LatexCommand tableofcontents

report/references.bib

@@ -0,0 +1,2 @@
+
+

scratch.m

@@ -1,10 +1,12 @@
 
 
-img = double(imread('dataset/Images/10_10_s.bmp'))./255;
+img = double(imread('dataset/Images/10_11_s.bmp'))./255;
 % imshow(img);
 
 img = getGreyscale(img);
 
 [mag, angle] = getEdgeInfo(img);
 
-F = getEdgeAngleHist(mag, angle)
+F = getEdgeAngleHist(mag, angle);
+
+imshow(mag > 0.05)

util/getEdgeAngleHist.m

@@ -1,7 +1,7 @@
 function F=getEdgeAngleHist(mag_img, angle_img)
 
 bins = 8;
-threshold = 0.1;
+threshold = 0.05;
 
 dimensions = size(angle_img);
 rows = dimensions(1);
@@ -22,4 +22,4 @@ for i = 1:rows
 end
 
 F= histogram(vals, bins, 'Normalization', 'probability').Values;
-return;
+return;