Update 2020: You can now directly call OpenCV C/C++ or Python API to use Pi Camera without any configuration now, just like use a normal USB webcam. Here is the sample code:

// Opencv needs to be installed on your Raspberry Pi
#include <opencv2/opencv.hpp>
using namespace std;
using namespace cv;

int main() {
    VideoCapture cap(0); // if you only have 1 camera connected.
    if (!cap.isOpened()) {
        cout << "Cannot open camera\n";
        return -1;
    }

    Mat frame;
    while (true) {
        bool ret = cap.read(frame); // or cap >> frame;
        if (!ret) {
            cout << "Error. Fail to receive frame.\n";
            break;
        }
        ......
        // process frame
        ......
        if (waitKey(1) == 'q') {
            break;
        }
    }

    return 0;
}

Now, using the Pi Camera in the method mentioned above is advised. But the below old way still works.

Normally OpenCV C/C++ only supports USB camera for Raspberry Pi. If you want to use OpenCV C/C++ with Pi Camera module, I have a nice guide for you.

Before we set the Pi Camera, you have to install OpenCV native library firstly, you can follow my previous guide.

I use the RaspiCam library from Rafael Muñoz Salinas (very good job, easy installation and fast speed), it provides C++ API for us, frame per second is almost 30.

Here are steps:

  1. Plug the Pi camera into Raspberry Pi (I am using Raspberry Pi 2).

  2. Download RaspiCam library into your Pi.

  3. Install the library.

// uncompress the file
tar xvzf raspicam-0.1.3.tgz
// go to the library folder
cd raspicam-0.1.3

mkdir build

cd build

cmake ..

make

sudo make install
  1. Testing.
Picam Testing

The library provides cmake to compile the program, but it’s not convenient to use for me, so I wrote makefile to compile the program. Here is the makefile:

LIBS = -I/usr/local/include/ 
CFLAGS = -lraspicam -lraspicam_cv -lopencv_core -lopencv_highgui
objects= main.o camera.o

picam: $(objects) 
	g++ $(objects) -o picam $(LIBS)$(CFLAGS)

main.o: main.cpp camera.h
	g++ main.cpp -c

camera.o: camera.cpp camera.h
	g++ camera.cpp -c
	
.PHONY: clean
clean:
	rm picam $(objects)

The library provides some examples to us, I rewrote the sample code, actually we also can use OpenCV C API (I transfer cv::Mat to IplImage in sample code).

Here is sample code, download to your Raspberry Pi, make and run the program, FPS is ~29.7(CPU usage is 22%), amazing!

–END–