138 lines
3.1 KiB
C++
138 lines
3.1 KiB
C++
#include "ImageApplyColorRecognition.h"
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/// <summary>
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/// 检测图像是否是彩色。当前逻辑仅针对红色像素进行判断，即存在红色像素则为彩色，否则为非彩色
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/// </summary>
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/// <param name="image">待测图像</param>
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/// <returns>true为彩色，false为非彩色</returns>
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bool isColor(const cv::Mat& image, double threshold = 60)
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{
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if (image.channels() != 3) return false;
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cv::Mat pDib_resize;
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cv::resize(image, pDib_resize, cv::Size(200, 200), 0, 0, cv::INTER_AREA);
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cv::Mat hsv;
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cv::cvtColor(pDib_resize, hsv, cv::COLOR_BGR2HSV_FULL);
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std::vector<cv::Mat> hsv_channels;
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cv::split(hsv, hsv_channels);
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double minVal, maxVal;
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cv::minMaxLoc(hsv_channels[1], &minVal, &maxVal);
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return maxVal > threshold;
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}
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bool isGray(const cv::Mat& image)
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{
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//if (image.channels() == 3) return true;
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//cv::Mat image_clone;
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//cv::resize(image, image_clone, cv::Size(), 0.25, 0.25);
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//int channels[] = { 0 };
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//int histsize[] = { 256 };
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//float range[] = { 0, 256 };
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//const float* histRanges[] = { range };
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//cv::Mat hist;
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//cv::calcHist(&image_clone, 1, channels, cv::Mat(), hist, 1, histsize, histRanges, true, false);
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//float pixels[256] = { 0 };
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//for (size_t i = 0; i < 256; i++)
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// pixels[i] = hist.at<float>(i, 0);
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//float sum = 0;
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//for (size_t i = 0; i < 40; i++)
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//{
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//}
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//float pixel_count0 = hist.at<float>(0, 0);
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//float pixel_count255 = hist.at<float>(255, 0);
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//float total = image_clone.total();
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//return ((pixel_count0 + pixel_count255) / total) > 0.95;
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return false;
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}
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CImageApplyColorRecognition::CImageApplyColorRecognition(ColorRecognitionMode mode)
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: m_mode(mode)
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{
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}
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CImageApplyColorRecognition::~CImageApplyColorRecognition(void)
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{
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}
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void CImageApplyColorRecognition::apply(cv::Mat& pDib, int side)
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{
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if (pDib.channels() != 3)
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{
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m_result = Gray;
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return;
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}
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m_result = isColor(pDib) ? Color : Gray;
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if (m_result == Gray && pDib.channels() == 3)
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cv::cvtColor(pDib, pDib, cv::COLOR_BGR2GRAY);
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//先判断是否需要判断是彩色
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//if (m_mode == AllColor || m_mode == Color_Gray || m_mode == Color_Mono)
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//{
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// //如果是彩色，直接退出
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// if (isColor(pDib))
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// {
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// m_result = Color;
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// return;
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// }
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//}
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//if (pDib.channels() == 3)
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// cv::cvtColor(pDib, pDib, cv::COLOR_BGR2GRAY);
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//if (m_mode == Color_Gray)
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//{
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// m_result = Gray;
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// return;
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//}
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//if (m_mode == Color_Mono)
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//{
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// m_bw.apply(pDib, side);
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// m_result = Mono;
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// return;
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//}
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//if (isGray(pDib))
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// m_result = Gray;
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//else
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//{
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// m_bw.apply(pDib, side);
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// m_result = Mono;
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//}
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}
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void CImageApplyColorRecognition::apply(std::vector<cv::Mat>& mats, bool isTwoSide)
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{
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m_results.clear();
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if (mats.empty()) return;
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if (!mats[0].empty())
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apply(mats[0], 0);
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m_results.push_back(m_result);
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if (isTwoSide && mats.size() > 1)
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if (!mats[1].empty())
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apply(mats[1], 1);
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m_results.push_back(m_result);
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}
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CImageApplyColorRecognition::ColorType CImageApplyColorRecognition::getResult()
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{
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return m_result;
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}
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std::vector<CImageApplyColorRecognition::ColorType> CImageApplyColorRecognition::getResults()
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{
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return m_results;
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}
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