【OpenCV】人脸旋转角度计算

// SeetaFacesTest.cpp : 定义控制台应用程序的入口点。
//

#include "stdafx.h"

#include <iostream>
#include <cstdint>
#include <fstream>
#include <string>
#include <cmath>

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>  // Gaussian Blur

#include "face_detection.h"
#include "face_alignment.h"

using namespace cv;
using namespace std;

int main()
{
// Initialize face detection model
seeta::FaceDetection detector("seeta_fd_frontal_v1.0.bin");
detector.SetMinFaceSize(80);
detector.SetScoreThresh(2.f);
detector.SetImagePyramidScaleFactor(0.8f);
detector.SetWindowStep(4, 4);

// Initialize face alignment model
seeta::FaceAlignment point_detector("seeta_fa_v1.1.bin");

//load image
const char* picturename = "10.jpg";

cv::Mat img_grayscale = cv::imread(picturename, 0);
cv::Mat img_color = cv::imread(picturename, 1);
if (img_grayscale.empty())
{
return 0;
}

seeta::ImageData img_data;
img_data.data = img_grayscale.data;
img_data.width = img_grayscale.cols;
img_data.height = img_grayscale.rows;
img_data.num_channels = 1;

// Detect faces
std::vector<seeta::FaceInfo> faces = detector.Detect(img_data);
int32_t face_num = static_cast<int32_t>(faces.size());

if (face_num == 0)
{
return 0;
}

// Detect 5 facial landmarks
seeta::FacialLandmark points[5];
point_detector.PointDetectLandmarks(img_data, faces[0], points);

Rect face_rect;
face_rect.x = faces[0].bbox.x;
face_rect.y = faces[0].bbox.y;
face_rect.width = faces[0].bbox.width;
face_rect.height = faces[0].bbox.height;

cv::Mat img_rect(img_grayscale, face_rect);  //截取脸部
cv::namedWindow("img_grayscale", CV_WINDOW_NORMAL);
cv::imshow("img_grayscale", img_rect);

//-------计算角度--------
int x1 = points[0].x;
int y1 = points[0].y;
int x2 = points[1].x;
int y2 = points[1].y;
cout << "0: " << x1 << ", " << y1 << endl;
cout << "1: " << x2 << ", " << y2 << endl;
double dX = (double)(x2 - x1);
double dY = (double)(y2 - y1);
float nAngle = (float)(atan(dY / dX)*180/3.1415926);
cout << "nAngle:" << nAngle << endl;

RotatedRect rrect(cvPoint(points[2].x, points[2].y), Size(face_rect.width, face_rect.height), nAngle);
Point2f vertices[4];
rrect.points(vertices);
for (int i = 0; i < 4; i++){
line(img_color, vertices[i], vertices[(i + 1) % 4], Scalar(0, 255, 150));
}

// Visualize the results
cv::rectangle(img_color, face_rect, Scalar(150, 255, 0), 5, 8, 0);
for (int i = 0; i < 5; i++)
{
cout << i << ": " << points[i].x << ", " << points[i].y << endl;
cv::circle(img_color, cvPoint(points[i].x, points[i].y), 10, CV_RGB(0, 255, 0), CV_FILLED);
}
cv::namedWindow("result", CV_WINDOW_NORMAL);
cv::resizeWindow("result", 484, 644);
cv::imshow("result", img_color);
cv::waitKey(0);
cv::imwrite("result.jpg", img_color);

return 0;
}

// SeetaFacesTest.cpp : 定义控制台应用程序的入口点。
//

#include "stdafx.h"

#include <iostream>
#include <cstdint>
#include <fstream>
#include <string>
#include <cmath>

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>  // Gaussian Blur

#include "face_detection.h"
#include "face_alignment.h"

using namespace cv;
using namespace std;

//逆时针旋转图像degree角度（原尺寸）
void rotateImage(const cv::Mat src, const cv::Mat& img_rotate, double degree)
{
//旋转中心为图像中心
Point2f center;
center.x = float(src.cols / 2.0 + 0.5);
center.y = float(src.rows / 2.0 + 0.5);
int length = 0;
length = sqrt(src.cols*src.cols + src.rows*src.rows);
//计算二维旋转的仿射变换矩阵
Mat M = getRotationMatrix2D(center, degree, 1);
warpAffine(src, img_rotate, M, Size(length, length));//仿射变换
}

int main()
{
// Initialize face detection model
seeta::FaceDetection detector("seeta_fd_frontal_v1.0.bin");
detector.SetMinFaceSize(80);
detector.SetScoreThresh(2.f);
detector.SetImagePyramidScaleFactor(0.8f);
detector.SetWindowStep(4, 4);

// Initialize face alignment model
seeta::FaceAlignment point_detector("seeta_fa_v1.1.bin");

//load image
const char* picturename = "10.jpg";

cv::Mat img_grayscale = cv::imread(picturename, 0);
cv::Mat img_color = cv::imread(picturename, 1);
if (img_grayscale.empty())
{
return 0;
}

seeta::ImageData img_data;
img_data.data = img_grayscale.data;
img_data.width = img_grayscale.cols;
img_data.height = img_grayscale.rows;
img_data.num_channels = 1;

// Detect faces
std::vector<seeta::FaceInfo> faces = detector.Detect(img_data);
int32_t face_num = static_cast<int32_t>(faces.size());

if (face_num == 0)
{
return 0;
}

// Detect 5 facial landmarks
seeta::FacialLandmark points[5];
point_detector.PointDetectLandmarks(img_data, faces[0], points);

//Rect face_rect;
//face_rect.x = faces[0].bbox.x;
//face_rect.y = faces[0].bbox.y;
//face_rect.width = faces[0].bbox.width;
//face_rect.height = faces[0].bbox.height;

//---------------------
Rect face_rect;
int tempx0 = points[0].x < points[3].x ? points[0].x : points[3].x;
int tempx1 = points[1].x > points[4].x ? points[1].x : points[4].x;
int nfaceW = (int)((tempx1 - tempx0)*2.2);
int tempy0 = points[0].y > points[1].y ? points[0].y : points[1].y;
int tempy1 = points[3].y > points[4].y ? points[3].y : points[4].y;
int nfaceH = (int)((tempy1 - tempy0)*2.2);
//int FaceWidth = (nfaceW > nfaceH ? nfaceW : nfaceH) * 1.3;
int x0 = points[2].x - nfaceW / 2;
int y0 = points[2].y - nfaceW / 2;
int w0 = nfaceW;
int h0 = nfaceW;
face_rect.x = x0;
face_rect.y = y0;
face_rect.width = w0;
face_rect.height = h0;

cv::Mat img_rect(img_color, face_rect);  //截取脸部
cv::circle(img_rect, cvPoint(img_rect.cols / 2, img_rect.rows / 2), 10, CV_RGB(0, 255, 0), CV_FILLED);

cv::namedWindow("img_rect", CV_WINDOW_NORMAL);
cv::imshow("img_rect", img_rect);
cout << "img_rect : " << img_rect.cols << ", " << img_rect.rows << endl;

//-------计算角度--------
int x1 = points[0].x;
int y1 = points[0].y;
int x2 = points[1].x;
int y2 = points[1].y;
cout << "0: " << x1 << ", " << y1 << endl;
cout << "1: " << x2 << ", " << y2 << endl;
double dX = (double)(x2 - x1);
double dY = (double)(y2 - y1);
float Angle = (float)(atan(dY / dX)*180/3.1415926);
cout << "nAngle:" << Angle << endl;

//--------------------------------
int length = 0;
length = sqrt(img_rect.cols*img_rect.cols + img_rect.rows*img_rect.rows);
cv::Mat tempImg(length, length, img_rect.type());//临时图像，大小和输出图像一样大
int ROI_x = length / 2 - img_rect.cols / 2;//ROI矩形左上角的x坐标
int ROI_y = length / 2 - img_rect.rows / 2;//ROI矩形左上角的y坐标
Rect ROIRect(ROI_x, ROI_y, img_rect.cols, img_rect.rows);//ROI矩形
Mat tempImgROI2(tempImg, ROIRect);//tempImg的中间部分
img_rect.copyTo(tempImgROI2);//将原图复制到tempImg的中心
cv::namedWindow("tempImg", CV_WINDOW_NORMAL);
cv::imshow("tempImg", tempImg);

cv::Mat dst_image;
Point2f center(float(length / 2.0), float(length / 2.0));//旋转中心
Mat M = getRotationMatrix2D(center, (double)Angle, 1);//计算旋转的仿射变换矩阵
warpAffine(tempImg, dst_image, M, Size(length, length));//仿射变换
cout << "dst_image : " << dst_image.cols << ", " << dst_image.rows << endl;
cv::circle(dst_image, cvPoint(dst_image.cols / 2, dst_image.rows / 2), 10, CV_RGB(150, 255, 0), CV_FILLED);

cv::namedWindow("dst_image", CV_WINDOW_NORMAL);
cv::imshow("dst_image", dst_image);

//-----------------------
int ndstfaceW = (int)((float)nfaceW/2.2*1.5);
Rect dst_rect;
dst_rect.x = dst_image.cols / 2 - ndstfaceW / 2;
dst_rect.y = dst_image.rows / 2 - ndstfaceW / 2;
dst_rect.width = ndstfaceW;
dst_rect.height = ndstfaceW;

cv::Mat img_dst_face(dst_image, dst_rect);  //截取脸部
cv::namedWindow("img_dst_face", CV_WINDOW_NORMAL);
cv::imshow("img_dst_face", img_dst_face);

//-------------------
RotatedRect rrect(cvPoint(points[2].x, points[2].y), Size(face_rect.width, face_rect.height), Angle);
Point2f vertices[4];
rrect.points(vertices);
for (int i = 0; i < 4; i++){
line(img_color, vertices[i], vertices[(i + 1) % 4], Scalar(0, 255, 150));
}

// Visualize the results
cv::rectangle(img_color, face_rect, Scalar(150, 255, 0), 5, 8, 0);
for (int i = 0; i < 5; i++)
{
cout << i << ": " << points[i].x << ", " << points[i].y << endl;
cv::circle(img_color, cvPoint(points[i].x, points[i].y), 10, CV_RGB(0, 255, 0), CV_FILLED);
}
cv::namedWindow("result", CV_WINDOW_NORMAL);
cv::resizeWindow("result", 484, 644);
cv::imshow("result", img_color);
cv::waitKey(0);
cv::imwrite("result.jpg", img_color);

return 0;
}