Added code for plotting accuracy

PlotValidation.m

@@ -4,7 +4,7 @@
 % PlotValidation
 % Generates traing vs validation loss plot. 
 %
-% Syntax : PlotValidation.m <train_output.csv> <validation_output.csv> <output_filepath.png>
+% Syntax : PlotValidation.m <train_output.csv> <validation_output.csv> <log dir>
 %
 % or can be run directly on a log folder of CDeep3M
 % Syntax : PlotValidation.m ~/trainingdata/1fm/log
@@ -19,23 +19,24 @@
 % {
 %   [1,1] = train_output.csv
 %   [2,1] = test_output.csv
-%   [3,1] = output_filepath.png
+%   [3,1] = output dir
 % }
 arg_list = argv ();
 
 if numel(arg_list) == 1
 logdir = arg_list{1,1};
   if exist(logdir,'dir')==7
   disp('Parsing log file');
-  train_file = fullfile(logdir, 'out.log.train'); delete(train_file);
-  test_file = fullfile(logdir, 'out.log.test');  delete(test_file);
+  train_file = fullfile(logdir, 'out.log.train'); 
+  test_file = fullfile(logdir, 'out.log.test'); 
   system(sprintf('python ~/caffe_nd_sense_segmentation/tools/extra/parse_log.py %s %s',fullfile(logdir, 'out.log'), logdir));
   else
   disp('Invalid argument');
   return
   end
 
 else
+logdir = arg_list{3,1}; 
 train_file = arg_list{1,1};
 test_file = arg_list{2,1};
 end
@@ -47,7 +48,9 @@
 % column format for test_output csv (NumIters,Seconds,LearningRate,accuracy_conv,class_Acc,loss_deconv_all)
 test_output = csvread(test_file,1,0); 
 
-plt = figure; 
+
+% Plot loss
+plt_loss = figure; 
 plot(train_output(:,1),train_output(:,4), test_output(:,1), test_output(:,6)); 
 grid on; 
 set(gca, 'xlabel', 'Number of Iterations'); 
@@ -57,11 +60,26 @@
 set(gca,'YScale','log'); 
 legend("Training","Validation"); 
 
-if numel(arg_list)==3
-outfile = arg_list{3,1};
-elseif numel(arg_list)==1
 outfile = fullfile(logdir, 'loss');
-end
-%print(plt,outfile, "-dpngcairo"); 
-print(plt,outfile, "-dpdf");
-fprintf('Your outputfile is saved as: %s.pdf\n', outfile');
+
+print(plt_loss,outfile, "-dpngcairo"); 
+%print(plt_loss,outfile, "-dpdf");
+fprintf('Your loss output file is saved as: %s.png\n', outfile);
+
+
+
+
+% Plot accuracy 
+plt_accuracy = figure; 
+plot(test_output(:,1), test_output(:,4)); 
+grid on; 
+set(gca, 'xlabel', 'Number of iterations'); 
+set(gca, 'ylabel', 'Accuracy'); 
+set(gca, 'Title', 'Validation Accuracy'); 
+
+
+
+outfile = fullfile(logdir, 'accuracy');
+print(plt_accuracy,outfile, "-dpngcairo");
+fprintf('Your accuracy output file is saved as: %s.png\n', outfile);
+

runvalidation.sh

@@ -10,16 +10,16 @@ fi
 
 function usage()
 {
-    echo "usage: $script_name log_file out_file
+    echo "usage: $script_name log_file out_dir
 
-              Script to plot training vs validation loss. 
-              Example: runvalidation.sh ~/cdeep3m/train_out/1fm/log/out.log ~/cdeep3m/train_out/1fm/train_vs_val.png
+              Script to plot training vs validation loss.
+              Example: runvalidation.sh ~/cdeep3m/train_out/1fm/log/out.log ~/cdeep3m/train_out/1fm/log/
 
               Version: $version
 
 positional arguments:
-  log_file        Log file from desired model. 
-  out_file        Filename of output png. 
+  log_file        Log file from desired model.
+  out_dir        Directory for output files
 
 
     " 1>&2;
@@ -34,7 +34,7 @@ fi
 log_dir=$(dirname $1)
 
 
-python $CAFFE_PATH/tools/extra/parse_log.py $1 $log_dir 
+python $CAFFE_PATH/tools/extra/parse_log.py $1 $log_dir
 
 
 PlotValidation.m $1.train $1.test $2