The answer is not necessarily in the makefile. I replaced the headers with

include <opencv2/core/core.hpp>

include <opencv2/highgui/highgui.hpp>

I also removed cout and using namespace std; with printf.

I had started using the older version of OpenCV when I began to code and switched to CV2 accidentally leaving the older headers.My original makefile with just LIBS = $(LIBPATH)/libopencv_core.so $(LIBPATH)/libopencv_highgui.so works just fine.

I want to thank everyone for the help they have given me so far.

I am a Windows person and haven't used a makefile in over 20 years so I really don't know what I'm doing.

I have developed my program in Visual Studio 2012 and it works fine but I must move it to a UNIX server for the class I'm taking. I used the sample makefile from class but when I ran it, I got the message cv.h not found.

After looking over my project in Visual Studio, I determined that I needed to include the following libraries: opencv_core249d.lib opencv_imgproc249d.lib opencv_highgui249d.lib opencv_ml249d.lib opencv_video249d.lib opencv_features2d249d.lib opencv_calib3d249d.lib

without the 249d. I found these libraries in the given directory on the UNIX server as .SO files.

I am having trouble with the LIBS statement:

CC = g++ CFLAGS = -g TARGET = objects OBJS = objects.o LIBPATH = /usr/lib64 LIBS = $(LIBPATH)/libopencv_core.so $(LIBPATH)/libopencv_highgui.so $(LIBPATH)/libopencv_imgproc.so $(LIBPATH)/libopencv_ml.so $(LIBPATH)/libopencv_video.so $(LIBPATH)/libopencv_features2d.so $(LIBPATH)/libopencv_calib3d.so

$(TARGET): $(OBJS) $(CC) -o $@ $(OBJS) $(LIBS)

.SUFFIXES: .cpp .o

.c.o: $(CC) -c $(CFLAGS) $<

.PHONY: clean

clean: /bin/rm -f core *.o $(TARGET)

When I ran make, the message was: * missing separator. Stop.

Could someone point me to a good tutorial on makefiles for OpenCV, or tell me what I'm doing wrong with this makefile, or perhaps both?

Thank you.

Thank you so much! I copied that statement from the previous one and forgot to change the array boundaries.

Thanks, I will rewrite for the real assignment since it will probably be changed. The old O'Reilly book uses cv1 and the online documentation used both cv1 and cv2. At least I can now access my way through the image pixel by pixel. Many more interesting things to come. Thanks loads for your help!

Would someone look over the following code and screen capture to see if I am calculating the Weber ratio correctly? I was very confused at first mixing cv1 and cv2. Pound signs and brackets removed on include

include opencv\cv.h

include opencv\highgui.h

using namespace cv; using namespace std;

int main() { char infilestr[255]; // input file name

int imgtype;                            // image type

int chanl;                          // number of channels

int imgdepth;
Mat img;
int diff = 0;
float weber = 0;
int totpixels = 0;
float totweber = 0;

while (!img.data)
{
    cout << "Please enter the name of the image file you wish to open:" << endl;
    cin.getline(infilestr, 255, '\n');
    img = imread(infilestr);
    if (!img.data)                          // check for valid image
    {
        cout << "The image file you specified could not be loaded, try again." << endl;
    }
}                                           // end while

Mat::MSize dim = img.size;
Mat grayimg;
imgtype = img.type();
chanl = img.channels();
imgdepth = img.depth();

cout <<  "The image type is: " << imgtype << endl;
cout << "The image depth is: " << imgdepth << endl;
if (chanl == 3)
{
    cout << "The original image was in color. Channels = :" << chanl << endl;
    cvtColor( img, grayimg, CV_BGR2GRAY );
}
else
{
    grayimg = img;
}
Scalar meanval = mean(grayimg,noArray());

Mat Web(img);
int height = img.rows;
int width = img.cols * 3;
int step = img.step;
int h = grayimg.rows;
int w = grayimg.cols;

for( int y=0; y < h; y++ ) 
{
    uchar* inp= grayimg.ptr<uchar>(y);
    for( int x=0; x < w; x++ ) 
    {
        diff = abs(meanval(0) - inp[x]);
        weber = diff/meanval(0);
        totweber += weber;
        totpixels++;
    }
}

totweber = totweber / totpixels; 
cout << "The average intensity of the grayscale image is: " << meanval(0) << endl;
cout << "The average weber ratio for the grayscale image is: " << totweber << endl;
namedWindow("Example1", CV_WINDOW_NORMAL);
imshow("Example1", grayimg);
waitKey(0);
return 0;

}

I am new to openCV and am taking a class in digital image processing. I am working through prior years assignment in preparation for our upcoming assignment.

1. Write a program to display information about an image. The information we are interested in is the dimensions of the image, its average gray scale intensity, its Weber ratio, and its format (gif/jpeg/tiff). If the input image is color, convert it to grayscale before computing the above attributes, and output a message that the input image is in color.

Is there a better way to calculate the Weber Ratio? I have used the following code so far to calculate the mean overall intensity, should I take absolute value |meanval - each point intensity| divided by meanval to get this ratio?:

CvSize dim = cvGetSize(image);
Mat img(image);
Mat grayimg;
imgtype = img.type();
chanl = img.channels();

cout <<  "The image type is: " << imgtype << endl;
if (chanl == 3)
{
    cout << "The original image was in color. Channels = :" << chanl << endl;
    cvtColor( img, grayimg, CV_BGR2GRAY );
}
else
{
    grayimg = img;
}
Scalar meanval = mean(grayimg,noArray());