#include "stdafx.h"
#include 
#include "opencv2/core/core.hpp" 
#include 
#include 
using namespace std;
using namespace cv;

void RGBtoHSV(float b,float g,float r,float &h,float &s,float &v)//將RGB值轉化為HSV值
{
	float max = (((r > b) ? r : b) > g) ? ((r > b) ? r : b) : g ;
	float min = (((r > b) ? b : r) > g) ? g : ((r > b) ? b : r);

	if (max == min)
	{
		h = 0; s = 0; v = max / 255;
	}
	else if (g >= b)
	{
		h = (max - r + g - min + b - min) / (max - min) * 60;
		s = 1 - min / max;
		v = max / 255;
	}
	else if (g < b)
	{
		h = 360 - (max - r + g - min + b - min) / (max - min) * 60;
		s = 1 - min / max;
		v = max / 255;
	}
}

//以HSV總量作為特徵量提取關鍵幀
int HSV(Mat img)
{
	
//	IplImage * ipl_img = NULL;
//	* ipl_img =img;//將Mat型別轉化為IplImage
	float B, G, R, H=0, S=0, V=0;
	int nr = img.rows; // number of rows  
	int nc = img.cols; // number of cols
	float sumH = 0, sumS = 0, sumV = 0;
	CvScalar cs;

	//將Mat型別轉化為IplImage
	IplImage *ipl_img = cvCreateImage(cvSize(nr, nc), 8, 3);
	ipl_img->imageData = (char *)img.data;

	for (int j = 0; j<nr; j++) {
		for (int i = 0; i<nc; i++) {
			cs =cvGet2D(ipl_img, i, j);
			B = cs.val[0];
			G = cs.val[1];
			R = cs.val[2];
			RGBtoHSV(B, G, R, H, S, V);
			sumH = sumH + H;
			sumS = sumS + S;
			sumV = sumV + V;
		}
	}
	float aveH = sumH / (nc*nr);
	float aveS = sumS / (nc*nr);
	float aveV = sumV / (nc*nr);
	float totalHSV = 9 * aveH + 3 * aveS + aveV;//totalHSV為特徵量
	return totalHSV;
}


int main()
{
	VideoCapture cap;
	cap.open("E:\\1.avi");
	Mat frame[5000];
	Mat keyframe[5000];
	int keycount=0;
	int frmNum = 0;
	float curhsv, lathsv;//當前幀的hsv值與後一幀的hsv值

	if (!cap.isOpened())
	{
		cout << "無法開啟視訊！" << endl;
		return -1;
	}

	int th=2;//提取關鍵幀的閾值
//	cout << "輸入閾值提取關鍵幀(大於1)：";
//	cin >> th;
	for (;;)
	{
		frmNum++;
		cap >> frame[frmNum];
		if (frame[frmNum].empty())
		{
			cout << "讀取視訊完畢 !" << endl;
			break;
		}
		keyframe[0] = frame[1];
		if (frmNum > 1)
		{
			curhsv = HSV(frame[frmNum - 1]);
			lathsv = HSV(frame[frmNum]);
			if (abs(curhsv - lathsv) > 2)//設定閾值th提取關鍵幀
			{
				keycount++;
				keyframe[keycount] = frame[frmNum];
			}
		}
	}

	cout << "該視訊總共有" << frmNum << "幀" << endl;
	cout << "在閾值為"<<th<<"時提取了" << keycount+1 << " 個關鍵幀!" << endl;
	for (int i = 0; i < keycount + 1; i++)
	{
		imshow("關鍵幀", keyframe[i]);//展示所有提取的關鍵幀
		waitKey(1);
	}
	return 0;
}