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test_lite_pose_robust_face.cpp
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test_lite_pose_robust_face.cpp
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//
// Created by DefTruth on 2021/7/18.
//
#include "lite/lite.h"
static void test_default()
{
std::string onnx_path = "../../../examples/hub/onnx/cv/dream_ijba_res18_end2end.onnx";
std::string pose_onnx_path = "../../../examples/hub/onnx/cv/fsanet-var.onnx";
std::string test_img_path0 = "../../../examples/lite/resources/test_lite_faceid_0.png";
std::string test_img_path1 = "../../../examples/lite/resources/test_lite_faceid_1.png";
lite::cv::faceid::PoseRobustFace *pose_robust_face = new lite::cv::faceid::PoseRobustFace(onnx_path);
lite::cv::face::pose::FSANet *fsanet = new lite::cv::face::pose::FSANet(pose_onnx_path);
lite::types::FaceContent face_content0, face_content1;
lite::types::EulerAngles euler_angles0, euler_angles1;
cv::Mat img_bgr0 = cv::imread(test_img_path0);
cv::Mat img_bgr1 = cv::imread(test_img_path1);
fsanet->detect(img_bgr0, euler_angles0); // head pose estimation first
fsanet->detect(img_bgr1, euler_angles1);
if (euler_angles0.flag && euler_angles1.flag)
{
// need a yaw value of input image, but can not get good performance
// in my test. so, I set it 0 in order to get default and robust performance
// pose_robust_face->detect(img_bgr0, face_content0, euler_angles0.yaw);
// pose_robust_face->detect(img_bgr1, face_content1, euler_angles1.yaw);
pose_robust_face->detect(img_bgr0, face_content0, 0.f);
pose_robust_face->detect(img_bgr1, face_content1, 0.f);
} else
{
pose_robust_face->detect(img_bgr0, face_content0, 0.f);
pose_robust_face->detect(img_bgr1, face_content1, 0.f);
}
std::cout << "face0.yaw: " << euler_angles0.yaw << " "
<< "face1.yaw: " << euler_angles1.yaw << std::endl;
if (face_content0.flag && face_content1.flag)
{
float sim = lite::utils::math::cosine_similarity<float>(
face_content0.embedding, face_content1.embedding);
std::cout << "Default Version Detected Sim: " << sim << std::endl;
}
delete pose_robust_face;
delete fsanet;
}
static void test_onnxruntime()
{
#ifdef ENABLE_ONNXRUNTIME
std::string onnx_path = "../../../examples/hub/onnx/cv/dream_ijba_res18_end2end.onnx";
std::string pose_onnx_path = "../../../examples/hub/onnx/cv/fsanet-var.onnx";
std::string test_img_path0 = "../../../examples/lite/resources/test_lite_faceid_0.png";
std::string test_img_path1 = "../../../examples/lite/resources/test_lite_faceid_2.png";
lite::onnxruntime::cv::faceid::PoseRobustFace *pose_robust_face =
new lite::onnxruntime::cv::faceid::PoseRobustFace(onnx_path);
lite::onnxruntime::cv::face::pose::FSANet *fsanet =
new lite::onnxruntime::cv::face::pose::FSANet(pose_onnx_path);
lite::types::FaceContent face_content0, face_content1;
lite::types::EulerAngles euler_angles0, euler_angles1;
cv::Mat img_bgr0 = cv::imread(test_img_path0);
cv::Mat img_bgr1 = cv::imread(test_img_path1);
fsanet->detect(img_bgr0, euler_angles0); // head pose estimation first
fsanet->detect(img_bgr1, euler_angles1);
if (euler_angles0.flag && euler_angles1.flag)
{
// pose_robust_face->detect(img_bgr0, face_content0, euler_angles0.yaw);
// pose_robust_face->detect(img_bgr1, face_content1, euler_angles1.yaw);
pose_robust_face->detect(img_bgr0, face_content0, 0.f);
pose_robust_face->detect(img_bgr1, face_content1, 0.f);
} else
{
pose_robust_face->detect(img_bgr0, face_content0, 0.f);
pose_robust_face->detect(img_bgr1, face_content1, 0.f);
}
std::cout << "face0.yaw: " << euler_angles0.yaw << " "
<< "face1.yaw: " << euler_angles1.yaw << std::endl;
if (face_content0.flag && face_content1.flag)
{
float sim = lite::utils::math::cosine_similarity<float>(
face_content0.embedding, face_content1.embedding);
std::cout << "ONNXRuntime Version Detected Sim: " << sim << std::endl;
}
delete pose_robust_face;
delete fsanet;
#endif
}
static void test_mnn()
{
#ifdef ENABLE_MNN
#endif
}
static void test_ncnn()
{
#ifdef ENABLE_NCNN
#endif
}
static void test_tnn()
{
#ifdef ENABLE_TNN
#endif
}
static void test_lite()
{
test_default();
test_onnxruntime();
test_mnn();
test_ncnn();
test_tnn();
}
int main(__unused int argc, __unused char *argv[])
{
test_lite();
return 0;
}