当我想使用 calcHist 生成图片特定范围内的像素数时，断言失败

Posted 2023-02-22

【中文标题】当我想使用 calcHist 生成图片特定范围内的像素数时，断言失败

【英文标题】：Assertion failed when I want to use calcHist to generate the number of pixels in a specific range of a picture

【发布时间】：2016-04-06 15:59:50

【问题描述】：

我想使用 calcHist 计算特定颜色范围内的像素数。但是我收到以下错误：

OpenCV Error: Assertion failed (dims <= 2 && data && (unsigned)i0 < (unsigned)(size.p[0]*size.p[1]) && elemSize() == (((((DataType<_Tp>::type) & ((512 - 1) << 3)) >> 3) + 1) << ((((sizeof(size_t)/4+1)*16384|0x3a50) >> ((DataType<_Tp>::type) & ((1 << 3) - 1))*2) & 3))) in cv::Mat::at, file e:\opencv2.4\opencv\build\include\opencv2\core\mat.hpp, line 570

ZKB_shop.exe has triggered a breakpoint.

我的代码如下所示：

#include <iostream>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>

using namespace std;
using namespace cv;

int main(int argc, const char** argv) 
    Mat image = imread("D:\\obj\\138.jpg");
    Mat img_hsv;
    cvtColor(image, img_hsv, CV_BGR2HSV);

    int hbins = 1;
    int sbins = 1;
    int vbins = 1;
    int histSize[] =  hbins,sbins,vbins ;

    //H
    float hranges[] =  0,20 ;
    //S
    float sranges[] =  100,255 ;
    //V
    float vranges[] =  107,245 ;
    const float* ranges[] =  hranges,sranges,vranges ;

    MatND hist;
    //chanels
    int channels[] =  0,1,2 ;

    calcHist(&img_hsv, 1, channels, Mat(), hist, 3, histSize, ranges);
    cout << "Hist.dims = " << hist.dims << endl;
    cout << "Value: " << hist.at<double>(0) << endl;
    cout << "Hist.rows = " << hist.rows << endl;
    cout << "Hist.cols = " << hist.cols << endl;
    return 0;

我改编了官方教程中的代码：http://docs.opencv.org/3.1.0/d6/dc7/group__imgproc__hist.html#ga4b2b5fd75503ff9e6844cc4dcdaed35d 并添加一个频道，但我不知道为什么它不起作用。

我用的是VS2015+WIN10+OPENCV2.4.11

【参考方案1】：

你过于复杂了。

要获取给定颜色范围内的像素数，您可以：

使用inRange在给定颜色范围内创建值的掩码 计算掩码中非零像素的数量，使用countNonZero

代码：

#include <opencv2/opencv.hpp>
using namespace cv;
using namespace std;

int main()

    // Read the image
    Mat image = imread("path_to_image");
    // Convert to HSV
    Mat img_hsv;
    cvtColor(image, img_hsv, CV_BGR2HSV);

    // Define lower and upper ranges
    Scalar lower(0, 100, 107);
    Scalar upper(20, 255, 245);

    // Create a mask with pixels in range
    Mat1b mask;
    inRange(img_hsv, lower, upper, mask);

    // Count the number of non-black pixels
    int cnz = countNonZero(mask);

    cout << "# pixels in range " << cnz << endl;

    return 0;