array(2) { ["docs"]=> array(10) { [0]=> array(10) { ["id"]=> string(3) "428" ["text"]=> string(77) "Visual Studio 2017 单独启动MSDN帮助(Microsoft Help Viewer)的方法" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(8) "DonetRen" ["tagsname"]=> string(55) "Visual Studio 2017|MSDN帮助|C#程序|.NET|Help Viewer" ["tagsid"]=> string(23) "[401,402,403,"300",404]" ["catesname"]=> string(0) "" ["catesid"]=> string(2) "[]" ["createtime"]=> string(10) "1511400964" ["_id"]=> string(3) "428" } [1]=> array(10) { ["id"]=> string(3) "427" ["text"]=> string(42) "npm -v;报错 cannot find module "wrapp"" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(4) "zzty" ["tagsname"]=> string(50) "node.js|npm|cannot find module "wrapp“|node" ["tagsid"]=> string(19) "[398,"239",399,400]" 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["_id"]=> string(3) "423" } [6]=> array(10) { ["id"]=> string(3) "422" ["text"]=> string(64) "JavaScript数据可视化编程学习(二)Flotr2,雷达图" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(7) "chengxs" ["tagsname"]=> string(28) "数据可视化|前端学习" ["tagsid"]=> string(9) "[396,397]" ["catesname"]=> string(18) "前端基本知识" ["catesid"]=> string(5) "[198]" ["createtime"]=> string(10) "1511397800" ["_id"]=> string(3) "422" } [7]=> array(10) { ["id"]=> string(3) "421" ["text"]=> string(36) "C#表达式目录树(Expression)" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(4) "wwym" ["tagsname"]=> string(0) "" ["tagsid"]=> string(2) "[]" ["catesname"]=> string(4) ".NET" ["catesid"]=> string(7) "["119"]" ["createtime"]=> string(10) "1511397474" ["_id"]=> string(3) "421" } [8]=> array(10) { ["id"]=> string(3) "420" ["text"]=> string(47) "数据结构 队列_队列实例:事件处理" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(7) "idreamo" ["tagsname"]=> string(40) "C语言|数据结构|队列|事件处理" ["tagsid"]=> string(23) "["246","247","248",395]" ["catesname"]=> string(12) "数据结构" ["catesid"]=> string(7) "["133"]" ["createtime"]=> string(10) "1511397279" ["_id"]=> string(3) "420" } [9]=> array(10) { ["id"]=> string(3) "419" ["text"]=> string(47) "久等了,博客园官方Android客户端发布" ["intro"]=> string(288) "目录 ECharts 异步加载 ECharts 数据可视化在过去几年中取得了巨大进展。开发人员对可视化产品的期望不再是简单的图表创建工具,而是在交互、性能、数据处理等方面有更高的要求。 chart.setOption({ color: [ " ["username"]=> string(3) "cmt" ["tagsname"]=> string(0) "" ["tagsid"]=> string(2) "[]" ["catesname"]=> string(0) "" ["catesid"]=> string(2) "[]" ["createtime"]=> string(10) "1511396549" ["_id"]=> string(3) "419" } } ["count"]=> int(200) } 222 Learning OpenCV Lecture 2 (Using the Strategy pattern in algorithm design) - 爱码网
ColorDetector.h:
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>

class ColorDetector
{
public:
      // empty constructor
     ColorDetector() : minDist(100) {
            // default parameter initialization here
            target[0] = target[1] = target[2] = 0;
     }

      // Sets the color distance threshold
      // Threshold must be positive
      // othrewise distance threshold is set to 0.
      void setColorDistanceThreshold(int distance) {
            if (distance < 0) {
                 distance = 0;
            }
            minDist = distance;
     }
      // Gets the color distance threshold
      int getColorDistanceThreshold() const {
            return minDist;
     }

      // Sets the color to be detected
      void setTargetColor(unsigned char red,
            unsigned char green,
            unsigned char blue) {
                 // BGR order
                 target[2] = red;
                 target[1] = green;
                 target[0] = blue;
     }
      // Sets the color to be detected
      void setTargetColor(cv::Vec3b color) {
            target = color;
     }
      // Gets the color to be detected
     cv::Vec3b getTargetColor() const {
            return target;
     }

     cv::Mat process(const cv::Mat &image);
      int getDistance(const cv::Vec3b& color) const;

private:
      // minimum acceptable distance
      int minDist;
      // target color
     cv::Vec3b target;
      // image containing resulting binary map
     cv::Mat result;

};

  ColorDetector.cpp:

#include "ColorDetector.h"

cv::Mat ColorDetector::process(const cv::Mat &image) {
     
      // re-allocate binary map if necessary
      // same size as input image, but 1-chaanel
     result.create(image.rows, image.cols, CV_8U);

      // get the iterators
     cv::Mat_<cv::Vec3b>::const_iterator it = image.begin<cv::Vec3b>();
     cv::Mat_<cv::Vec3b>::const_iterator itend = image.end<cv::Vec3b>();
     cv::Mat_<uchar>::iterator itout = result.begin<uchar>();

      // for each pixel
      for ( ; it!= itend; ++it, ++itout) {
            // process each pixel ---------------------
            // compute distance from target color
            if (getDistance(*it) < minDist) {
                 *itout = 255;
            } else {
                 *itout = 0;
            }
            // end of pixel processing ----------------
     }

      return result;
}

int ColorDetector::getDistance(const cv::Vec3b& color) const {
      return abs(color[0] - target[0]) +
              abs(color[1] - target[1]) +
              abs(color[2] - target[2]);

      // Other methods to compute distance
//   return static_cast<int>(
//         cv::norm<int, 3>(cv::Vec3b(color[0] - target[0],
//                                            color[1] - target[1],
//                                            color[2] - target[2])));


}

main.cpp

#include "ColorDetector.h"

int main()
{
      // 1. Create image processor boject
     ColorDetector cdetect;

      // 2. Read input image
     cv::Mat image = cv::imread( "test.jpg");
      if (!image.data) {
            return 0;
     }

      // 3. Set input parameters
     cdetect.setTargetColor(130, 190, 230); // here blue sky

     cv::namedWindow( "result");
     
      // 4. Process the image and display the result
     cv::imshow( "result", cdetect.process(image));

     cv::waitKey();
      return 0;
}

 

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