在一些特殊情况下，经常需要依据图像中的人脸，对图片进行倾斜矫正。
例如拍照角度幅度过大之类的情况，而进行人工矫正确实很叫人头大。
那是不是可以有一种算法，可以根据人脸的信息对图片进行角度的修复呢？
答案肯定是确认的。
再次例如，想要通过人脸的特征对人物的表情和情绪进行精准判断，
那么这个时候如果能确保人脸没有发现严重倾斜，无疑对准确率判断有一定的帮助。
那么假如一张图片只有一个人脸，其实很好判断，通过眼睛的位置的坐标，根据两眼的直线角度，
就可以计算出修正的角度。
然后旋转图片到对应角度即可。
但是如果，一张图片存在多张人脸的时候该怎么办？
有两种方法：
1.找到最大的那个人脸，以它为基准
2.找到频次最高的人脸角度，以频次为基准
当然在大多数情况，方法1是比较合理的。
这两个种情况就留给各位看官去实现了。
本人仅仅考虑一张人脸的情况，演示如何实现该功能。
倾斜角度计算的代码如下:
float diffEyeX = right_eye_x - left_eye_x;
float diffEyeY = right_eye_y - left_eye_y; float fAngle;
float M_PI = 3.1415926535897932384626433832795f;
if (fabs(diffEyeX) < 0.0000001f)
fAngle = .f;
else
fAngle = atanf(diffEyeY / diffEyeX) * 180.0f / M_PI;
如果看不明白，需要好好补一下高中数学基础。
为了节约时间，直接复用《自动红眼移除算法 附c++完整代码》的代码。
增加函数如下:
void RotateBilinear(unsigned char *sourceData, int width, int height, int Channels, int RowBytes,
unsigned char *destinationData, int newWidth, int newHeight, float angle, bool keepSize = true,
int fillColorR = , int fillColorG = , int fillColorB = ) {
if (sourceData == NULL || destinationData == NULL) return; float oldXradius = (float) (width - ) / ;
float oldYradius = (float) (height - ) / ; float newXradius = (float) (newWidth - ) / ;
float newYradius = (float) (newHeight - ) / ; double MPI = 3.14159265358979323846;
double angleRad = -angle * MPI / 180.0;
float angleCos = (float) cos(angleRad);
float angleSin = (float) sin(angleRad); int srcStride = RowBytes;
int dstOffset = newWidth * Channels - ((Channels == ) ? newWidth : newWidth * Channels); unsigned char fillR = fillColorR;
unsigned char fillG = fillColorG;
unsigned char fillB = fillColorB; unsigned char *src = (unsigned char *) sourceData;
unsigned char *dst = (unsigned char *) destinationData; int ymax = height - ;
int xmax = width - ;
if (Channels == ) {
float cy = -newYradius;
for (int y = ; y < newHeight; y++) {
float tx = angleSin * cy + oldXradius;
float ty = angleCos * cy + oldYradius; float cx = -newXradius;
for (int x = ; x < newWidth; x++, dst++) {
float ox = tx + angleCos * cx;
float oy = ty - angleSin * cx; int ox1 = (int) ox;
int oy1 = (int) oy; if ((ox1 < ) || (oy1 < ) || (ox1 >= width) || (oy1 >= height)) {
*dst = fillG;
} else {
int ox2 = (ox1 == xmax) ? ox1 : ox1 + ;
int oy2 = (oy1 == ymax) ? oy1 : oy1 + ;
float dx1 = ;
if ((dx1 = ox - (float) ox1) < )
dx1 = ;
float dx2 = 1.0f - dx1;
float dy1 = ;
if ((dy1 = oy - (float) oy1) < )
dy1 = ;
float dy2 = 1.0f - dy1; unsigned char *p1 = src + oy1 * srcStride;
unsigned char *p2 = src + oy2 * srcStride; *dst = (unsigned char) (dy2 * (dx2 * p1[ox1] + dx1 * p1[ox2]) +
dy1 * (dx2 * p2[ox1] + dx1 * p2[ox2]));
}
cx++;
}
cy++;
dst += dstOffset;
}
} else if (Channels == ) {
float cy = -newYradius;
for (int y = ; y < newHeight; y++) {
float tx = angleSin * cy + oldXradius;
float ty = angleCos * cy + oldYradius; float cx = -newXradius;
for (int x = ; x < newWidth; x++, dst += Channels) {
float ox = tx + angleCos * cx;
float oy = ty - angleSin * cx; int ox1 = (int) ox;
int oy1 = (int) oy; if ((ox1 < ) || (oy1 < ) || (ox1 >= width) || (oy1 >= height)) {
dst[] = fillR;
dst[] = fillG;
dst[] = fillB;
} else {
int ox2 = (ox1 == xmax) ? ox1 : ox1 + ;
int oy2 = (oy1 == ymax) ? oy1 : oy1 + ; float dx1 = ;
if ((dx1 = ox - (float) ox1) < )
dx1 = ;
float dx2 = 1.0f - dx1;
float dy1 = ;
if ((dy1 = oy - (float) oy1) < )
dy1 = ;
float dy2 = 1.0f - dy1; unsigned char *p1 = src + oy1 * srcStride;
unsigned char *p2 = p1;
p1 += ox1 * Channels;
p2 += ox2 * Channels; unsigned char *p3 = src + oy2 * srcStride;
unsigned char *p4 = p3;
p3 += ox1 * Channels;
p4 += ox2 * Channels; dst[] = (unsigned char) (
dy2 * (dx2 * p1[] + dx1 * p2[]) +
dy1 * (dx2 * p3[] + dx1 * p4[])); dst[] = (unsigned char) (
dy2 * (dx2 * p1[] + dx1 * p2[]) +
dy1 * (dx2 * p3[] + dx1 * p4[])); dst[] = (unsigned char) (
dy2 * (dx2 * p1[] + dx1 * p2[]) +
dy1 * (dx2 * p3[] + dx1 * p4[]));
}
cx++;
}
cy++;
dst += dstOffset;
}
} else if (Channels == ) {
float cy = -newYradius;
for (int y = ; y < newHeight; y++) {
float tx = angleSin * cy + oldXradius;
float ty = angleCos * cy + oldYradius; float cx = -newXradius;
for (int x = ; x < newWidth; x++, dst += Channels) {
float ox = tx + angleCos * cx;
float oy = ty - angleSin * cx; int ox1 = (int) ox;
int oy1 = (int) oy; if ((ox1 < ) || (oy1 < ) || (ox1 >= width) || (oy1 >= height)) {
dst[] = fillR;
dst[] = fillG;
dst[] = fillB;
dst[] = ;
} else {
int ox2 = (ox1 == xmax) ? ox1 : ox1 + ;
int oy2 = (oy1 == ymax) ? oy1 : oy1 + ; float dx1 = ;
if ((dx1 = ox - (float) ox1) < )
dx1 = ;
float dx2 = 1.0f - dx1;
float dy1 = ;
if ((dy1 = oy - (float) oy1) < )
dy1 = ;
float dy2 = 1.0f - dy1; unsigned char *p1 = src + oy1 * srcStride;
unsigned char *p2 = p1;
p1 += ox1 * Channels;
p2 += ox2 * Channels; unsigned char *p3 = src + oy2 * srcStride;
unsigned char *p4 = p3;
p3 += ox1 * Channels;
p4 += ox2 * Channels; dst[] = (unsigned char) (
dy2 * (dx2 * p1[] + dx1 * p2[]) +
dy1 * (dx2 * p3[] + dx1 * p4[])); dst[] = (unsigned char) (
dy2 * (dx2 * p1[] + dx1 * p2[]) +
dy1 * (dx2 * p3[] + dx1 * p4[])); dst[] = (unsigned char) (
dy2 * (dx2 * p1[] + dx1 * p2[]) +
dy1 * (dx2 * p3[] + dx1 * p4[]));
dst[] = ;
}
cx++;
}
cy++;
dst += dstOffset;
}
}
} void facialPoseCorrection(unsigned char *inputImage, int Width, int Height, int Channels, int left_eye_x, int left_eye_y,
int right_eye_x, int right_eye_y) {
float diffEyeX = right_eye_x - left_eye_x;
float diffEyeY = right_eye_y - left_eye_y; float fAngle;
float M_PI = 3.1415926535897932384626433832795f;
if (fabs(diffEyeX) < 0.0000001f)
fAngle = .f;
else
fAngle = atanf(diffEyeY / diffEyeX) * 180.0f / M_PI;
size_t numberOfPixels = Width * Height * Channels * sizeof(unsigned char);
unsigned char *outputImage = (unsigned char *) malloc(numberOfPixels);
if (outputImage != nullptr) {
RotateBilinear(inputImage, Width, Height, Channels, Width * Channels, outputImage, Width, Height, fAngle);
memcpy(inputImage, outputImage, numberOfPixels);
free(outputImage);
}
}
上效果图片。
原图：
红眼修复+倾斜矫正:
项目地址:
https://github.com/cpuimage/MTCNN
命令行参数:
mtcnn 模型文件路径 图片路径
例如: mtcnn ../models ../sample.jpg
用cmake即可进行编译示例代码，详情见CMakeLists.txt。
若有其他相关问题或者需求也可以邮件联系俺探讨。
邮箱地址是:
gaozhihan@vip.qq.com