import numpy as np
import cv2 as cv
img = cv.imread('c:/lib/opencv/samples/data/fruits.jpg',cv.IMREAD_COLOR)
orange = img[300:380,150:220]
cv.imshow('fruits',img)
cv.imshow('orange',orange)
# calculating object histogram
c=[0,1,2]
r=[32,32,32]
rc=[  0, 256,0,256,0,256]
roihist = cv.calcHist([orange],c, None, r, rc )
# normalize histogram and apply backprojection
cv.normalize(roihist,roihist,0,255,cv.NORM_MINMAX)
dst = cv.calcBackProject([img],c,roihist,rc,1)
ret,thresh = cv.threshold(dst,10,255,0)
thresh = cv.merge((thresh,thresh,thresh))
cv.imshow('dst',dst)
cv.imshow('res',thresh)
cv.waitKey(0)
cv.destroyAllWindows()

#include <opencv2/opencv.hpp> 
#include <iostream>

using namespace cv;
using namespace std;

int main(int argc, char **argv)
{
        Mat img = imread("g:/lib/opencv/samples/data/fruits.jpg", IMREAD_COLOR);
    Mat orange = img(Rect(150,300, 70,80));
    imshow("fruits", img);
    imshow("orange", orange);
    int hBins = 32;
    int histSize[] = { hBins, hBins, hBins };
    int nbChannels = 3;
    int channels[] = { 0,1,2 };
    float h_range[] = { 0, 256 };
    const float* ranges[] = { h_range, h_range,h_range };
    cv::Mat histogramme;

    cv::calcHist(&orange, 1, channels, Mat(), histogramme, nbChannels, histSize, ranges, true, false);
    normalize(histogramme, histogramme, 0, 255, cv::NormTypes::NORM_MINMAX, -1, cv::Mat());
    cv::Mat backproj;
    Mat bk;
    cv::calcBackProject(&img, 1, channels, histogramme, bk, ranges, 1, true);
    imshow("result", bk);
    waitKey(0); // NO Problem it is good in 3d
    vector<Mat> x;
    vector<int> ch;
    vector<float> cranges;
    x.push_back(img);
    ch.push_back(0);
    ch.push_back(1);
    ch.push_back(2);
    cranges.push_back(0); cranges.push_back(256);
    cranges.push_back(0); cranges.push_back(256);
    cranges.push_back(0); cranges.push_back(256);
    calcBackProject(x, ch, histogramme, bk, cranges, 1); // Exception in 3d
    imshow("result", bk);
    waitKey(0);
   }