#include "ImageApplyColorRecognition.h"
#include "ImageApplyHeaders.h"

static CImageApplyBWBinaray m_bw;
static CImageApplyAdjustColors m_ac(0, 50, 1.0f);

/// <summary>
/// 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
/// </summary>
/// <param name="image">待测图像</param>
/// <returns>true为彩色，false为非彩色</returns>
bool isColor(const cv::Mat& image)
{
	if (image.channels() != 3) return false;

	cv::Mat pDib_resize;
	cv::resize(image, pDib_resize, cv::Size(image.cols / 9, image.rows / 9), 0, 0, cv::INTER_AREA);

	cv::Mat hsv;
	cv::cvtColor(pDib_resize, hsv, cv::COLOR_BGR2HSV_FULL);
	std::vector<cv::Mat> hsv_channels;
	cv::split(hsv, hsv_channels);

	cv::Mat range_h1, range_h2, range_s, range_v;
	cv::inRange(hsv_channels[0], 0, 85, range_h1);
	cv::inRange(hsv_channels[0], 170, 255, range_h2);
	cv::inRange(hsv_channels[1], 60, 255, range_s);
	cv::inRange(hsv_channels[2], 100, 255, range_v);

	cv::Mat thre = (range_h1 | range_h2) & range_s & range_v;
	return (cv::sum(thre)[0] / 255)> 4;
}

bool isGray(const cv::Mat& image)
{
	if (image.channels() == 3) return true;

	cv::Mat image_clone;
	cv::resize(image, image_clone, cv::Size(), 0.25, 0.25);
	int channels[] = { 0 };
	int histsize[] = { 256 };
	float range[] = { 0, 256 };
	const float* histRanges[] = { range };
	cv::Mat hist;
	cv::calcHist(&image_clone, 1, channels, cv::Mat(), hist, 1, histsize, histRanges, true, false);

	float pixel_count0 = hist.at<float>(0, 0);
	float pixel_count255 = hist.at<float>(255, 0);
	float total = image_clone.total();

	return ((pixel_count0 + pixel_count255) / total) > 0.95;
}

CImageApplyColorRecognition::CImageApplyColorRecognition(ColorRecognitionMode mode)
	: m_mode(mode)
{
}

CImageApplyColorRecognition::~CImageApplyColorRecognition(void)
{
}

void CImageApplyColorRecognition::apply(cv::Mat& pDib, int side)
{
	//先判断是否需要判断是彩色
	if (m_mode == AllColor || m_mode == Color_Gray || m_mode == Color_Mono)
	{
		//如果是彩色，直接退出
		if (isColor(pDib))
		{
			m_result = Color;
			return;
		}
	}

	if (pDib.channels() == 3)
		cv::cvtColor(pDib, pDib, cv::COLOR_BGR2GRAY);

	if (m_mode == Color_Gray)
	{
		m_result = Gray;
		return;
	}

	if (m_mode == Color_Mono)
	{
		m_bw.apply(pDib, side);
		m_result = Mono;
		return;
	}

	if (isGray(pDib))
		m_result = Gray;
	else
	{
		m_bw.apply(pDib, side);
		m_result = Mono;
	}
}

void CImageApplyColorRecognition::apply(std::vector<cv::Mat>& mats, bool isTwoSide)
{
	m_results.clear();
	if (mats.empty()) return;

	if (!mats[0].empty())
		apply(mats[0], 0);

	m_results.push_back(m_result);

	if (isTwoSide && mats.size() > 1)
		if (!mats[1].empty())
			apply(mats[1], 1);

	m_results.push_back(m_result);
}

CImageApplyColorRecognition::ColorType CImageApplyColorRecognition::getResult()
{
	return m_result;
}

std::vector<CImageApplyColorRecognition::ColorType> CImageApplyColorRecognition::getResults()
{
	return m_results;
}