OpenCV Tutorials

To manipulate pixels of an OpenCV Image (Mat) , use the C++ code below:

#include <opencv2>
#include <opencv2>
#include <opencv2>
#include <stdio.h>

using namespace cv;

int main( int argc, char** argv )
{
 char* imageName = argv[1];

 Mat image;
 image = imread( imageName, 1 );

 if( argc != 2 || !image.data )
 {
   printf( " No image data \n " );
   return -1;
 }

 // Pixel access
 uchar pixValue;
 for (int i = 0; i (j, i);
        for(int k = 0; k (j, i)[0] = 2*image.at<vec3b>(j, i)[0];
            image.at<vec3b>(j, i)[1] = 2*image.at<vec3b>(j, i)[1];
            image.at<vec3b>(j, i)[2] = 2*image.at<vec3b>(j, i)[2];
        }
     }
 }

 namedWindow( "talkera.org/opencv", CV_WINDOW_AUTOSIZE );
 imshow( "talkera.org/opencv", image );
 waitKey(0);

 return 0;
}</vec3b></vec3b></vec3b></vec3b></vec3b></stdio.h></opencv2></opencv2></opencv2>

#include

using namespace cv;

int main( int argc, char** argv )

{

char* imageName = argv[1];

Mat image;

image = imread( imageName, 1 );

if( argc != 2 || !image.data )

{

printf( " No image data \n " );

return -1;

}

// Pixel access

uchar pixValue;

for (int i = 0; i image.cols; i++) {

for (int j = 0; j image.rows; j++) {

Vec3b &intensity = image.atVec3b>(j, i);

for(int k = 0; k image.channels(); k++) {

// calculate pixValue

image.atVec3b>(j, i)[0] = 2*image.atVec3b>(j, i)[0];

image.atVec3b>(j, i)[1] = 2*image.atVec3b>(j, i)[1];

image.atVec3b>(j, i)[2] = 2*image.atVec3b>(j, i)[2];

}

namedWindow( "talkera.org/opencv", CV_WINDOW_AUTOSIZE );

imshow( "talkera.org/opencv", image );

waitKey(0);

return 0;

}

Output:

Accessing pixels in Python is more easy:

import numpy as np
import cv2

img = cv2.imread('face2.jpg')
print img[3,3]

import numpy as np

import cv2

img = cv2.imread('face2.jpg')

print img[3,3]

Generating a histogram in OpenCV is very straightforward.

C++ Generate histogram opencv

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>

using namespace std;
using namespace cv;

/**
 * @function main
 */
int main( int argc, char** argv )
{
  Mat src, dst;

  /// Load image
  src = imread( argv[1], 1 );

  if( !src.data )
    { return -1; }

  /// Separate the image in 3 places ( B, G and R )
  vector<mat> bgr_planes;
  split( src, bgr_planes );

  /// Establish the number of bins
  int histSize = 256;

  /// Set the ranges ( for B,G,R) )
  float range[] = { 0, 256 } ;
  const float* histRange = { range };

  bool uniform = true; bool accumulate = false;

  Mat b_hist, g_hist, r_hist;

  /// Compute the histograms:
  calcHist( &bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histSize, &histRange, uniform, accumulate );
  calcHist( &bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histSize, &histRange, uniform, accumulate );
  calcHist( &bgr_planes[2], 1, 0, Mat(), r_hist, 1, &histSize, &histRange, uniform, accumulate );

  // Draw the histograms for B, G and R
  int hist_w = 512; int hist_h = 400;
  int bin_w = cvRound( (double) hist_w/histSize );

  Mat histImage( hist_h, hist_w, CV_8UC3, Scalar( 0,0,0) );

  /// Normalize the result to [ 0, histImage.rows ]
  normalize(b_hist, b_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
  normalize(g_hist, g_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );
  normalize(r_hist, r_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );

  /// Draw for each channel
  for( int i = 1; i (i-1)) ) ,
                       Point( bin_w*(i), hist_h - cvRound(b_hist.at<float>(i)) ),
                       Scalar( 255, 0, 0), 2, 8, 0  );
      line( histImage, Point( bin_w*(i-1), hist_h - cvRound(g_hist.at<float>(i-1)) ) ,
                       Point( bin_w*(i), hist_h - cvRound(g_hist.at<float>(i)) ),
                       Scalar( 0, 255, 0), 2, 8, 0  );
      line( histImage, Point( bin_w*(i-1), hist_h - cvRound(r_hist.at<float>(i-1)) ) ,
                       Point( bin_w*(i), hist_h - cvRound(r_hist.at<float>(i)) ),
                       Scalar( 0, 0, 255), 2, 8, 0  );
  }

  /// Display
  namedWindow("calcHist Demo", CV_WINDOW_AUTOSIZE );
  imshow("calcHist Demo", histImage );

  waitKey(0);

  return 0;
}</float></float></float></float></float></mat></stdio.h></iostream>

#include "opencv2/highgui/highgui.hpp"

#include "opencv2/imgproc/imgproc.hpp"

#include

using namespace std;

using namespace cv;

/**

* @function main

int main( int argc, char** argv )

{

Mat src, dst;

/// Load image

src = imread( argv[1], 1 );

if( !src.data )

{ return -1; }

/// Separate the image in 3 places ( B, G and R )

vectorMat> bgr_planes;

split( src, bgr_planes );

/// Establish the number of bins

int histSize = 256;

/// Set the ranges ( for B,G,R) )

float range[] = { 0, 256 } ;

const float* histRange = { range };

bool uniform = true; bool accumulate = false;

Mat b_hist, g_hist, r_hist;

/// Compute the histograms:

calcHist( &bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histSize, &histRange, uniform, accumulate );

calcHist( &bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histSize, &histRange, uniform, accumulate );

calcHist( &bgr_planes[2], 1, 0, Mat(), r_hist, 1, &histSize, &histRange, uniform, accumulate );

// Draw the histograms for B, G and R

int hist_w = 512; int hist_h = 400;

int bin_w = cvRound( (double) hist_w/histSize );

Mat histImage( hist_h, hist_w, CV_8UC3, Scalar( 0,0,0) );

/// Normalize the result to [ 0, histImage.rows ]

normalize(b_hist, b_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );

normalize(g_hist, g_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );

normalize(r_hist, r_hist, 0, histImage.rows, NORM_MINMAX, -1, Mat() );

/// Draw for each channel

for( int i = 1; i histSize; i++ )

{

line( histImage, Point( bin_w*(i-1), hist_h - cvRound(b_hist.atfloat>(i-1)) ) ,

Point( bin_w*(i), hist_h - cvRound(b_hist.atfloat>(i)) ),

Scalar( 255, 0, 0), 2, 8, 0 );

line( histImage, Point( bin_w*(i-1), hist_h - cvRound(g_hist.atfloat>(i-1)) ) ,

Point( bin_w*(i), hist_h - cvRound(g_hist.atfloat>(i)) ),

Scalar( 0, 255, 0), 2, 8, 0 );

line( histImage, Point( bin_w*(i-1), hist_h - cvRound(r_hist.atfloat>(i-1)) ) ,

Point( bin_w*(i), hist_h - cvRound(r_hist.atfloat>(i)) ),

Scalar( 0, 0, 255), 2, 8, 0 );

}

/// Display

namedWindow("calcHist Demo", CV_WINDOW_AUTOSIZE );

imshow("calcHist Demo", histImage );

waitKey(0);

return 0;

}

Draw histogram in Python:

# draw histogram in python. talkera.org/opencv
import cv2
import numpy as np

img = cv2.imread('cat.jpg')
h = np.zeros((300,256,3))

bins = np.arange(256).reshape(256,1)
color = [ (255,0,0),(0,255,0),(0,0,255) ]

for ch, col in enumerate(color):
    hist_item = cv2.calcHist([img],[ch],None,[256],[0,255])
    cv2.normalize(hist_item,hist_item,0,255,cv2.NORM_MINMAX)
    hist=np.int32(np.around(hist_item))
    pts = np.column_stack((bins,hist))
    cv2.polylines(h,[pts],False,col)

h=np.flipud(h)

cv2.imshow('colorhist',h)
cv2.waitKey(0)

# draw histogram in python. talkera.org/opencv

import cv2

import numpy as np

img = cv2.imread('cat.jpg')

h = np.zeros((300,256,3))

bins = np.arange(256).reshape(256,1)

color = [ (255,0,0),(0,255,0),(0,0,255) ]

for ch, col in enumerate(color):

hist_item = cv2.calcHist([img],[ch],None,[256],[0,255])

cv2.normalize(hist_item,hist_item,0,255,cv2.NORM_MINMAX)

hist=np.int32(np.around(hist_item))

pts = np.column_stack((bins,hist))

cv2.polylines(h,[pts],False,col)

h=np.flipud(h)

cv2.imshow('colorhist',h)

cv2.waitKey(0)

Output:

OpenCV Pixel Access Manipulation

Histogram with OpenCV