-
Notifications
You must be signed in to change notification settings - Fork 673
/
test_lite_mobilese_focal_face.cpp
155 lines (127 loc) 路 5.53 KB
/
test_lite_mobilese_focal_face.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
//
// Created by DefTruth on 2021/7/24.
//
#include "lite/lite.h"
static void test_default()
{
std::string onnx_path = "../../../examples/hub/onnx/cv/face_recognition.pytorch_Mobilenet_se_focal_121000.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::MobileSEFocalFace *mobilese_focal_face =
new lite::cv::faceid::MobileSEFocalFace(onnx_path);
lite::types::FaceContent face_content0, face_content1;
cv::Mat img_bgr0 = cv::imread(test_img_path0);
cv::Mat img_bgr1 = cv::imread(test_img_path1);
mobilese_focal_face->detect(img_bgr0, face_content0);
mobilese_focal_face->detect(img_bgr1, face_content1);
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 mobilese_focal_face;
}
static void test_onnxruntime()
{
#ifdef ENABLE_ONNXRUNTIME
std::string onnx_path = "../../../examples/hub/onnx/cv/face_recognition.pytorch_Mobilenet_se_focal_121000.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::MobileSEFocalFace *mobilese_focal_face =
new lite::onnxruntime::cv::faceid::MobileSEFocalFace(onnx_path);
lite::types::FaceContent face_content0, face_content1;
cv::Mat img_bgr0 = cv::imread(test_img_path0);
cv::Mat img_bgr1 = cv::imread(test_img_path1);
mobilese_focal_face->detect(img_bgr0, face_content0);
mobilese_focal_face->detect(img_bgr1, face_content1);
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 mobilese_focal_face;
#endif
}
static void test_mnn()
{
#ifdef ENABLE_MNN
std::string mnn_path = "../../../examples/hub/mnn/cv/face_recognition.pytorch_Mobilenet_se_focal_121000.mnn";
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::mnn::cv::faceid::MobileSEFocalFace *mobilese_focal_face =
new lite::mnn::cv::faceid::MobileSEFocalFace(mnn_path);
lite::types::FaceContent face_content0, face_content1;
cv::Mat img_bgr0 = cv::imread(test_img_path0);
cv::Mat img_bgr1 = cv::imread(test_img_path1);
mobilese_focal_face->detect(img_bgr0, face_content0);
mobilese_focal_face->detect(img_bgr1, face_content1);
if (face_content0.flag && face_content1.flag)
{
float sim = lite::utils::math::cosine_similarity<float>(
face_content0.embedding, face_content1.embedding);
std::cout << "MNN Version Detected Sim: " << sim << std::endl;
}
delete mobilese_focal_face;
#endif
}
static void test_ncnn()
{
#ifdef ENABLE_NCNN
std::string param_path = "../../../examples/hub/ncnn/cv/face_recognition.pytorch_Mobilenet_se_focal_121000.opt.param";
std::string bin_path = "../../../examples/hub/ncnn/cv/face_recognition.pytorch_Mobilenet_se_focal_121000.opt.bin";
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::ncnn::cv::faceid::MobileSEFocalFace *mobilese_focal_face =
new lite::ncnn::cv::faceid::MobileSEFocalFace(param_path, bin_path);
lite::types::FaceContent face_content0, face_content1;
cv::Mat img_bgr0 = cv::imread(test_img_path0);
cv::Mat img_bgr1 = cv::imread(test_img_path1);
mobilese_focal_face->detect(img_bgr0, face_content0);
mobilese_focal_face->detect(img_bgr1, face_content1);
if (face_content0.flag && face_content1.flag)
{
float sim = lite::utils::math::cosine_similarity<float>(
face_content0.embedding, face_content1.embedding);
std::cout << "NCNN Version Detected Sim: " << sim << std::endl;
}
delete mobilese_focal_face;
#endif
}
static void test_tnn()
{
#ifdef ENABLE_TNN
std::string proto_path = "../../../examples/hub/tnn/cv/face_recognition.pytorch_Mobilenet_se_focal_121000.opt.tnnproto";
std::string model_path = "../../../examples/hub/tnn/cv/face_recognition.pytorch_Mobilenet_se_focal_121000.opt.tnnmodel";
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::tnn::cv::faceid::MobileSEFocalFace *mobilese_focal_face =
new lite::tnn::cv::faceid::MobileSEFocalFace(proto_path, model_path);
lite::types::FaceContent face_content0, face_content1;
cv::Mat img_bgr0 = cv::imread(test_img_path0);
cv::Mat img_bgr1 = cv::imread(test_img_path1);
mobilese_focal_face->detect(img_bgr0, face_content0);
mobilese_focal_face->detect(img_bgr1, face_content1);
if (face_content0.flag && face_content1.flag)
{
float sim = lite::utils::math::cosine_similarity<float>(
face_content0.embedding, face_content1.embedding);
std::cout << "TNN Version Detected Sim: " << sim << std::endl;
}
delete mobilese_focal_face;
#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;
}