Fix android build warnings

samples/cpp/pca.cpp

@@ -1,13 +1,13 @@
 /*
 * pca.cpp
 *
-*  Author: 
+*  Author:
 *  Kevin Hughes <kevinhughes27[at]gmail[dot]com>
 *
 *  Special Thanks to:
 *  Philipp Wagner <bytefish[at]gmx[dot]de>
 *
-* This program demonstrates how to use OpenCV PCA with a 
+* This program demonstrates how to use OpenCV PCA with a
 * specified amount of variance to retain. The effect
 * is illustrated further by using a trackbar to
 * change the value for retained varaince.
@@ -17,9 +17,9 @@
 * on this list of images. The author recommends using
 * the first 15 faces of the AT&T face data set:
 * http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html
-* 
+*
 * so for example your input text file would look like this:
-* 
+*
 *        <path_to_at&t_faces>/orl_faces/s1/1.pgm
 *        <path_to_at&t_faces>/orl_faces/s2/1.pgm
 *        <path_to_at&t_faces>/orl_faces/s3/1.pgm
@@ -50,7 +50,7 @@ using namespace std;
 
 ///////////////////////
 // Functions
-void read_imgList(const string& filename, vector<Mat>& images) {
+static void read_imgList(const string& filename, vector<Mat>& images) {
     std::ifstream file(filename.c_str(), ifstream::in);
     if (!file) {
         string error_message = "No valid input file was given, please check the given filename.";
@@ -62,19 +62,19 @@ void read_imgList(const string& filename, vector<Mat>& images) {
     }
 }
 
-Mat formatImagesForPCA(const vector<Mat> &data)
+static  Mat formatImagesForPCA(const vector<Mat> &data)
 {
     Mat dst(data.size(), data[0].rows*data[0].cols, CV_32F);
     for(unsigned int i = 0; i < data.size(); i++)
     {
         Mat image_row = data[i].clone().reshape(1,1);
         Mat row_i = dst.row(i);
-        image_row.convertTo(row_i,CV_32F);    
+        image_row.convertTo(row_i,CV_32F);
     }
     return dst;
 }
 
-Mat toGrayscale(InputArray _src) {
+static Mat toGrayscale(InputArray _src) {
     Mat src = _src.getMat();
     // only allow one channel
     if(src.channels() != 1) {
@@ -95,22 +95,22 @@ struct params
     string winName;
 };
 
-void onTrackbar(int pos, void* ptr) 
-{    
+static void onTrackbar(int pos, void* ptr)
+{
     cout << "Retained Variance = " << pos << "%   ";
     cout << "re-calculating PCA..." << std::flush;
-    
+
     double var = pos / 100.0;
-    
+
     struct params *p = (struct params *)ptr;
-    
+
     p->pca = PCA(p->data, cv::Mat(), CV_PCA_DATA_AS_ROW, var);
-    
+
     Mat point = p->pca.project(p->data.row(0));
     Mat reconstruction = p->pca.backProject(point);
     reconstruction = reconstruction.reshape(p->ch, p->rows);
     reconstruction = toGrayscale(reconstruction);
-    
+
     imshow(p->winName, reconstruction);
     cout << "done!   # of principal components: " << p->pca.eigenvectors.rows << endl;
 }
@@ -118,19 +118,19 @@ void onTrackbar(int pos, void* ptr)
 
 ///////////////////////
 // Main
-int main(int argc, char** argv) 
+int main(int argc, char** argv)
 {
     if (argc != 2) {
         cout << "usage: " << argv[0] << " <image_list.txt>" << endl;
         exit(1);
     }
-    
+
     // Get the path to your CSV.
     string imgList = string(argv[1]);
-    
+
     // vector to hold the images
     vector<Mat> images;
-    
+
     // Read in the data. This can fail if not valid
     try {
         read_imgList(imgList, images);
@@ -138,29 +138,29 @@ int main(int argc, char** argv)
         cerr << "Error opening file \"" << imgList << "\". Reason: " << e.msg << endl;
         exit(1);
     }
-    
+
     // Quit if there are not enough images for this demo.
     if(images.size() <= 1) {
         string error_message = "This demo needs at least 2 images to work. Please add more images to your data set!";
         CV_Error(CV_StsError, error_message);
     }
-        
+
     // Reshape and stack images into a rowMatrix
     Mat data = formatImagesForPCA(images);
-    
+
     // perform PCA
     PCA pca(data, cv::Mat(), CV_PCA_DATA_AS_ROW, 0.95); // trackbar is initially set here, also this is a common value for retainedVariance
-    
-    // Demonstration of the effect of retainedVariance on the first image 
+
+    // Demonstration of the effect of retainedVariance on the first image
     Mat point = pca.project(data.row(0)); // project into the eigenspace, thus the image becomes a "point"
     Mat reconstruction = pca.backProject(point); // re-create the image from the "point"
     reconstruction = reconstruction.reshape(images[0].channels(), images[0].rows); // reshape from a row vector into image shape
     reconstruction = toGrayscale(reconstruction); // re-scale for displaying purposes
-    
+
     // init highgui window
     string winName = "Reconstruction | press 'q' to quit";
     namedWindow(winName, CV_WINDOW_NORMAL);
-    
+
     // params struct to pass to the trackbar handler
     params p;
     p.data = data;
@@ -168,17 +168,17 @@ int main(int argc, char** argv)
     p.rows = images[0].rows;
     p.pca = pca;
     p.winName = winName;
-    
+
     // create the tracbar
     int pos = 95;
-    createTrackbar("Retained Variance (%)", winName, &pos, 100, onTrackbar, (void*)&p); 
-    
+    createTrackbar("Retained Variance (%)", winName, &pos, 100, onTrackbar, (void*)&p);
+
     // display until user presses q
     imshow(winName, reconstruction);
-    
+
     char key = 0;
     while(key != 'q')
         key = waitKey();
-   
-   return 0; 
+
+   return 0;
 }