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README.md

RaspiCam: C++ API for using Raspberry camera (with OpenCV)

This library allows to use the Raspberry Pi Camera under BSD License.

The project is started by the AVA research group (rafael Muñoz Salinas; rmsalinas@uco.es) and is now maintained on this GIT repository by Cédric Verstraeten. Please note that is NOT the OFFICIAL repository of RaspiCam, these can be found here.

This repository is used in the Kerberos.io project.

Release notes

Update 2014/03/04: version 0.1.1 released Download at SourceForge Main feaure in 0.0.7 : Still camera API. You can now use the still mode for high resolution (includes OpenCv interface). See examples for more info.

Notes: Requires to update the firmware to use shutterspeed (sudo rpi-update)

Main features

  • Provides class RaspiCam for easy and full control of the camera
  • Provides class RaspiCam_Still and RaspiCam_Still_Cv for controlling the camera in still mode
  • Provides class RaspiCam_Cv for easy control of the camera with OpenCV.
  • Provides class RaspiCam_Still and RaspiCam_Still_Cv for controlling the camera in still mode
  • Provides class RaspiCam_Still and RaspiCam_Still_Cv for using the still camera mode
  • Easy compilation/installation using cmake.
  • No need to install development file of userland. Implementation is hidden.
  • Many examples

Performance Following, we show the capture performance of the library (measured capturing 600 frames). Gray and YUV420 Mode

  • 1280x960: 29.5fps, 640x480 : 29.5fps, 320x240 : 29.5fps RGB Mode
  • 1280x960: 28 fps, 640x480 : 29.29fps, 320x240 : 29.24fps BGR Mode
  • 1280x960: 14 fps, 640x480 : 29.29fps, 320x240 : 29.24fps

Note: when using the full resolution video callbacks with the full resolution of the Raspberry Pi Camera v2, you will likely get an error such as mmal: mmal_vc_port_enable: failed to enable port vc.ril.camera:out:1(BGR3): ENOSPC. In order to fix this increase your GPU memory to at least 256MB.

Color conversion is the most time consuming part. We still need to improve that part. Go to src/private and check if you can contribute!

Note: the library is compiled with the options: -Wall -ffunction-sections -fomit-frame-pointer -O2 -ffast-math -DNDEBUG -mcpu=arm1176jzf-s -mfpu=vfp -mfloat-abi=hard -ftree-vectorize Note 2: the library is currently setting the camera in video mode. So, maximum resolution is 1280x960. I am working on the still port to enable higher resolutions.

Compiling

Clone the repository to your raspberry. Then, uncompress the file and compile

git clone https://github.com/cedricve/raspicam.git
cd raspicam
mkdir build
cd build
cmake ..

At this point you’ll see something like

-- CREATE OPENCV MODULE=1
-- CMAKE_INSTALL_PREFIX=/usr/local
-- REQUIRED_LIBRARIES=/opt/vc/lib/libmmal_core.so;/opt/vc/lib/libmmal_util.so;/opt/vc/lib/libmmal.so
-- Change a value with: cmake -D<Variable>=<Value>
-- 
-- Configuring done
-- Generating done
-- Build files have been written to: /home/pi/raspicam/trunk/build

If OpenCV development files are installed in your system, then you see following output; otherwise this option will be 0 and the opencv module of the library will not be compiled.

-- CREATE OPENCV MODULE=1

Finally compile, install and update the ldconfig:

make
sudo make install
sudo ldconfig

After that, you have the programs raspicam_test and raspicam_cv_test (if opencv was enabled) in build/utils. Run the first program to check that compilation is ok.

sudo ./raspicam_test
sudo ./raspicam_cv_test

Using it in your projects

You can learn how to use the library by taking a look at the examples in the utils directory and by analyzing the header files. In addition, we provide a some simple examples on how to use the library with cmake. First, create a directory for our own project. Then, go in and create a file with the name simpletest_raspicam.cpp and add the following code

/**
*/
#include <ctime>
#include <fstream>
#include <iostream>
#include <raspicam/raspicam.h>
using namespace std;

int main ( int argc,char **argv ) {
    raspicam::RaspiCam Camera; //Camera object
    //Open camera 
    cout<<"Opening Camera..."<<endl;
    if ( !Camera.open()) {cerr<<"Error opening camera"<<endl;return -1;}
    //wait a while until camera stabilizes
    cout<<"Sleeping for 3 secs"<<endl;
    sleep(3);
    //capture
    Camera.grab();
    //allocate memory
    unsigned char *data=new unsigned char[  Camera.getImageTypeSize ( raspicam::RASPICAM_FORMAT_RGB )];
    //extract the image in rgb format
    Camera.retrieve ( data,raspicam::RASPICAM_FORMAT_RGB );//get camera image
    //save
    std::ofstream outFile ( "raspicam_image.ppm",std::ios::binary );
    outFile<<"P6\n"<<Camera.getWidth() <<" "<<Camera.getHeight() <<" 255\n";
    outFile.write ( ( char* ) data, Camera.getImageTypeSize ( raspicam::RASPICAM_FORMAT_RGB ) );
    cout<<"Image saved at raspicam_image.ppm"<<endl;
    //free resrources    
    delete data;
    return 0;
}

For cmake users, create a file named CMakeLists.txt and add:

cmake_minimum_required (VERSION 2.8) 
project (raspicam_test)
find_package(raspicam REQUIRED)
add_executable (simpletest_raspicam simpletest_raspicam.cpp)  
target_link_libraries (simpletest_raspicam ${raspicam_LIBS})

Finally, create build dir,compile and execute

mkdir build
cd build
cmake ..
make
./simpletest_raspicam

If you do not like cmake, simply

g++ simpletest_raspicam.cpp -o simpletest_raspicam -I/usr/local/include -lraspicam -lmmal -lmmal_core -lmmal_util

OpenCV Interface

If the OpenCV is found when compiling the library, the libraspicam_cv.so module is created and the RaspiCam_Cv class available. Take a look at the examples in utils to see how to use the class. In addition, we show here how you can use the RaspiCam_Cv in your own project using cmake.

First create a file with the name simpletest_raspicam_cv.cpp and add the following code

#include <ctime>
#include <iostream>
#include <raspicam/raspicam_cv.h>
using namespace std; 

int main ( int argc,char **argv ) {

    time_t timer_begin,timer_end;
    raspicam::RaspiCam_Cv Camera;
    cv::Mat image;
    int nCount=100;
    //set camera params
    Camera.set( CV_CAP_PROP_FORMAT, CV_8UC1 );
    //Open camera
    cout<<"Opening Camera..."<<endl;
    if (!Camera.open()) {cerr<<"Error opening the camera"<<endl;return -1;}
    //Start capture
    cout<<"Capturing "<<nCount<<" frames ...."<<endl;
    time ( &timer_begin );
    for ( int i=0; i<nCount; i++ ) {
        Camera.grab();
        Camera.retrieve ( image);
        if ( i%5==0 )  cout<<"\r captured "<<i<<" images"<<std::flush;
    }
    cout<<"Stop camera..."<<endl;
    Camera.release();
    //show time statistics
    time ( &timer_end ); /* get current time; same as: timer = time(NULL)  */
    double secondsElapsed = difftime ( timer_end,timer_begin );
    cout<< secondsElapsed<<" seconds for "<< nCount<<"  frames : FPS = "<<  ( float ) ( ( float ) ( nCount ) /secondsElapsed ) <<endl;
    //save image 
    cv::imwrite("raspicam_cv_image.jpg",image);
    cout<<"Image saved at raspicam_cv_image.jpg"<<endl;
}

For cmake users, create a file named CMakeLists.txt and add:

cmake_minimum_required (VERSION 2.8) 
project (raspicam_test)
find_package(raspicam REQUIRED)
find_package(OpenCV)
IF  ( OpenCV_FOUND AND raspicam_CV_FOUND)
MESSAGE(STATUS "COMPILING OPENCV TESTS")
add_executable (simpletest_raspicam_cv simpletest_raspicam_cv.cpp)  
target_link_libraries (simpletest_raspicam_cv ${raspicam_CV_LIBS})
ELSE()
MESSAGE(FATAL_ERROR "OPENCV NOT FOUND IN YOUR SYSTEM")
ENDIF()

Finally, create,compile and execute

mkdir build
cd build
cmake ..
make
./simpletest_raspicam_cv

If you do not like cmake:

g++ simpletest_raspicam_cv.cpp -o  simpletest_raspicam_cv -I/usr/local/include/ -lraspicam -lraspicam_cv -lmmal -lmmal_core -lmmal_util -lopencv_core -lopencv_highgui