基于 SeetaFace6 实现 iOS 端图片人脸识别&比对。
初始化
std::string buddle = [[[NSBundle mainBundle] resourcePath] UTF8String];
seeta::ModelSetting FD_model(buddle + "/assert/model/face_detector.csta");
seeta::ModelSetting FR_model(buddle + "/assert/model/face_recognizer.csta");
seeta::ModelSetting FL_model(buddle + "/assert/model/face_landmarker_pts5.csta");
seeta::FaceDetector FD(FD_model);
seeta::FaceLandmarker FL(FL_model);
seeta::FaceRecognizer FR(FR_model);
封装图片人脸特征值的提取
// 提取图片特征值
std::shared_ptr<float> extract_img(seeta::FaceDetector *fd,
seeta::FaceRecognizer *fr,
seeta::FaceLandmarker *fl,
std::string imgPath) {
seeta::cv::ImageData imgData = cv::imread(imgPath);
auto faces = fd->detect_v2(imgData);
auto points1 = fl->mark(imgData, faces[0].pos);
std::shared_ptr<float> features(new float[fr->GetExtractFeatureSize()],
std::default_delete<float[]>());
fr->Extract(imgData, points1.data(), features.get());
return features;
}
// 提取图片特征值
std::vector<std::shared_ptr<float>> extract_img1(seeta::FaceDetector *fd,
seeta::FaceRecognizer *fr,
seeta::FaceLandmarker *fl,
std::string imgPath) {
std::vector<std::shared_ptr<float>> features;
seeta::cv::ImageData imgData = cv::imread(imgPath);
std::vector<SeetaFaceInfo> faces = fd->detect_v2(imgData);
std::cout << "faces count " << faces.size() << std::endl;
std::vector<SeetaFaceInfo> ::const_iterator cit = faces.begin();
while(cit != faces.end()){
SeetaFaceInfo faceInfo = *cit;
auto points = fl->mark(imgData, faceInfo.pos);
std::shared_ptr<float> feature(new float[fr->GetExtractFeatureSize()],
std::default_delete<float[]>());
fr->Extract(imgData, points.data(), feature.get());
features.push_back(feature);
cit++;
}
return features;
}
特征值比对
/*** 特征值对比 */
float compare(seeta::FaceRecognizer *fr,
const std::shared_ptr<float> &feat1,
const std::shared_ptr<float> &feat2) {
return fr->CalculateSimilarity(feat1.get(), feat2.get());
}
/*** 底层逻辑 */
float compare(const float *lhs, const float *rhs, int size) {
float sum = 0;
for (int i = 0; i < size; ++i) {
sum += *lhs * *rhs;
++lhs;
++rhs;
}
return sum;
}
/*** 简单修改 适配业务需求 */
float compareFixFeature(NSArray<NSString *> *feature, const float *rhs, int size) {
float sum = 0;
for (int i = 0; i < size; ++i) {
CGFloat fl1 = feature[i].floatValue;
sum += fl1 * *rhs;
++rhs;
}
return sum;
}
- (CGFloat)compareFeature1:(NSArray<NSString *> *)feature1 feature2:(NSArray<NSString *> *)feature2 {
CGFloat sum = 0;
for (int i = 0; i < feature1.count; i ++) {
CGFloat fl1 = feature1[i].floatValue;
CGFloat fl2 = feature2[i].floatValue;
sum += fl1 * fl2;
}
return sum;
}
逻辑实现
/*** 提取特征值 */
- (void)getImgFeature {
seeta::FaceDetector FD(FD_model);
seeta::FaceLandmarker FL(FL_model);
seeta::FaceRecognizer FR(FR_model);
std::vector<std::string> imgPathArr;
for (int i = 0; i < 5; i ++) {
std::string path = buddle + "/assert/image/" + std::to_string(i+1) + ".JPG";
imgPathArr.push_back(path);
}
int x = 0;
std::vector<std::string>::iterator imgPath;
for (imgPath = imgPathArr.begin(); imgPath != imgPathArr.end(); imgPath ++) {
std::cout << "img_index *** " << x << std::endl;
std::vector<std::shared_ptr<float>> valueArr = extract_img1(&FD, &FR, &FL, *imgPath);
std::vector<std::shared_ptr<float>>::iterator feature;
for (feature = valueArr.begin(); feature != valueArr.end(); feature ++) {
std::cout << "Feature Adress " << *feature << std::endl;
std::cout << "Feature Value " << **feature << std::endl;
}
x ++;
}
}
/*** 提取特征值 & 输出 Feature float 数组 */
- (void)printImgFeature {
seeta::FaceDetector FD(FD_model);
seeta::FaceLandmarker FL(FL_model);
seeta::FaceRecognizer FR(FR_model);
std::string imgPath = buddle + "/assert/image/11.JPG";
std::shared_ptr<float> feature = extract_img(&FD, &FR, &FL, imgPath);
float *rhs = feature.get();
for (int i = 0; i < 1024; ++i) {
float value = *rhs;
std::cout << i << " * Value * " << value << std::endl;
++rhs;
}
}
/*** 本地图片人脸识别&比对 */
- (void)compare1 {
seeta::FaceDetector FD(FD_model);
seeta::FaceLandmarker FL(FL_model);
seeta::FaceRecognizer FR(FR_model);
std::vector<std::string> imgPathArr;
for (int i = 0; i < 5; i ++) {
std::string path = buddle + "/assert/image/" + std::to_string(i+11) + ".JPG";
imgPathArr.push_back(path);
}
std::vector<std::shared_ptr<float>> valueArr;
std::vector<std::string>::iterator imgPath;
for (imgPath = imgPathArr.begin(); imgPath != imgPathArr.end(); imgPath ++) {
std::shared_ptr<float> value = extract_img(&FD, &FR, &FL, *imgPath);
valueArr.push_back(value);
}
int x = 0;
std::vector<std::shared_ptr<float>>::iterator value_i;
for (value_i = valueArr.begin(); value_i != valueArr.end(); value_i ++) {
std::cout << "img_index *** " << x << std::endl;
std::cout << "Feature Adress " << *value_i << std::endl;
std::cout << "Feature Value " << **value_i << std::endl;
// std::cout << "Feature Value " << *value_i->get() << std::endl;
int y = 0;
std::vector<std::shared_ptr<float>>::iterator value_j;
for (value_j = valueArr.begin(); value_j != valueArr.end(); value_j ++) {
float com = compare(&FR, *value_i, *value_j);
std::cout << "compare: " << x << "_" << y << " * value: " << com << std::endl;
y ++;
}
x ++;
}
}
/*** 后台特征值接收 与 本地图片人脸识别比对 */
- (void)compare2 {
seeta::FaceDetector FD(FD_model);
seeta::FaceLandmarker FL(FL_model);
seeta::FaceRecognizer FR(FR_model);
std::string imgPath = buddle + "/assert/image/11.JPG";
std::string imgPath2 = buddle + "/assert/image/13.JPG";
// 模拟后台数据 - 特征值字符串
NSMutableString *resultStr = [NSMutableString string];
std::shared_ptr<float> feature = extract_img(&FD, &FR, &FL, imgPath);
float *rhs = feature.get();
for (int i = 0; i < 1024; ++i) {
float value = *rhs;
NSString *valueStr = [NSString stringWithFormat:@"%f,", value];
[resultStr appendString:valueStr];
++rhs;
}
// NSLog(@"resultStr: %@", resultStr);
NSArray *featureArr = [resultStr componentsSeparatedByString:@","];
std::shared_ptr<float> feature2 = extract_img(&FD, &FR, &FL, imgPath2);
float com = compareFixFeature(featureArr, feature2.get(), 1024);
std::cout << "compare: " << com << std::endl;
}
