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Update InspireFace to 1.1.2

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This commit is contained in:
JingyuYan
2024-07-02 22:51:19 +08:00
parent a61a1dd466
commit f964f678e6
21 changed files with 327 additions and 83 deletions
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2
cpp-package/inspireface/cpp/inspireface/c_api/inspireface.h
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@@ -171,7 +171,7 @@ HYPER_CAPI_EXPORT extern HResult HFCreateInspireFaceSession(
* @param detectMode Detection mode to be used.
* @param maxDetectFaceNum Maximum number of faces to detect.
* @param detectPixelLevel Modify the input resolution level of the detector, the larger the better,
* the need to input a multiple of 160, such as 160, 320, 640, the default value -1 is 160.
* the need to input a multiple of 160, such as 160, 320, 640, the default value -1 is 320.
* @param trackByDetectModeFPS If you are using the MODE_TRACK_BY_DETECTION tracking mode,
* this value is used to set the fps frame rate of your current incoming video stream, which defaults to -1 at 30fps.
* @param handle Pointer to the context handle that will be returned.

2
cpp-package/inspireface/cpp/inspireface/information.h
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@@ -7,6 +7,6 @@
#define INSPIRE_FACE_VERSION_MAJOR_STR "1"
#define INSPIRE_FACE_VERSION_MINOR_STR "1"
#define INSPIRE_FACE_VERSION_PATCH_STR "1"
#define INSPIRE_FACE_VERSION_PATCH_STR "2"
#endif //HYPERFACEREPO_INFORMATION_H

5
cpp-package/inspireface/cpp/inspireface/middleware/utils.h
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@@ -643,14 +643,13 @@ inline cv::Rect GetNewBox(int src_w, int src_h, cv::Rect bbox, float scale) {
template<typename T>
inline bool isShortestSideGreaterThan(const cv::Rect_<T>& rect, T value) {
inline bool isShortestSideGreaterThan(const cv::Rect_<T>& rect, T value, float scale) {
// Find the shortest edge
T shortestSide = std::min(rect.width, rect.height);
T shortestSide = std::min(rect.width / scale, rect.height / scale);
// Determines whether the shortest edge is greater than the given value
return shortestSide > value;
}
} // namespace inspire
#endif

77
cpp-package/inspireface/cpp/inspireface/track_module/face_track.cpp
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@@ -342,7 +342,7 @@ void FaceTrack::DetectFace(const cv::Mat &input, float scale) {
Object obj;
const auto box = boxes[i];
obj.rect = Rect_<float>(box.x1, box.y1, box.x2 - box.x1, box.y2 - box.y1);
if (!isShortestSideGreaterThan<float>(obj.rect, filter_minimum_face_px_size)) {
if (!isShortestSideGreaterThan<float>(obj.rect, filter_minimum_face_px_size, scale)) {
// Filter too small face detection box
continue;
}
@@ -364,8 +364,8 @@ void FaceTrack::DetectFace(const cv::Mat &input, float scale) {
for (int i = 0; i < boxes.size(); i++) {
bbox[i] = cv::Rect(cv::Point(static_cast<int>(boxes[i].x1), static_cast<int>(boxes[i].y1)),
cv::Point(static_cast<int>(boxes[i].x2), static_cast<int>(boxes[i].y2)));
if (!isShortestSideGreaterThan<float>(bbox[i], filter_minimum_face_px_size)) {
if (!isShortestSideGreaterThan<float>(bbox[i], filter_minimum_face_px_size, scale)) {
// Filter too small face detection box
continue;
}
@@ -378,16 +378,14 @@ void FaceTrack::DetectFace(const cv::Mat &input, float scale) {
FaceObject faceinfo(tracking_idx_, bbox[i], FaceLandmark::NUM_OF_LANDMARK);
faceinfo.detect_bbox_ = bbox[i];
// Control that the number of faces detected does not exceed the maximum limit
if (candidate_faces_.size() < max_detected_faces_) {
candidate_faces_.push_back(faceinfo);
} else {
// If the maximum limit is exceeded, you can choose to discard the currently detected face or choose the face to discard according to the policy
// For example, face confidence can be compared and faces with lower confidence can be discarded
// Take the example of simply discarding the last face
candidate_faces_.pop_back();
if (candidate_faces_.size() >= max_detected_faces_)
{
continue;
}
candidate_faces_.push_back(faceinfo);
}
}
@@ -396,9 +394,10 @@ void FaceTrack::DetectFace(const cv::Mat &input, float scale) {
int FaceTrack::Configuration(inspire::InspireArchive &archive) {
// Initialize the detection model
InspireModel detModel;
auto ret = archive.LoadModel("face_detect", detModel);
auto scheme = ChoiceMultiLevelDetectModel(m_dynamic_detection_input_level_);
auto ret = archive.LoadModel(scheme, detModel);
if (ret != SARC_SUCCESS) {
INSPIRE_LOGE("Load %s error: %d", "face_detect", ret);
INSPIRE_LOGE("Load %s error: %d", "face_detect_320", ret);
return HERR_ARCHIVE_LOAD_MODEL_FAILURE;
}
InitDetectModel(detModel);
@@ -444,21 +443,9 @@ int FaceTrack::InitLandmarkModel(InspireModel &model) {
int FaceTrack::InitDetectModel(InspireModel &model) {
std::vector<int> input_size;
if (m_dynamic_detection_input_level_ != -1) {
if (m_dynamic_detection_input_level_ % 160 != 0 || m_dynamic_detection_input_level_ < 160) {
INSPIRE_LOGE("The input size '%d' for the custom detector is not valid. \
Please use a multiple of 160 (minimum 160) for the input dimensions, such as 320 or 640.", m_dynamic_detection_input_level_);
return HERR_INVALID_DETECTION_INPUT;
}
// Wide-Range mode temporary value
input_size = {m_dynamic_detection_input_level_, m_dynamic_detection_input_level_};
model.Config().set<std::vector<int>>("input_size", input_size);
} else {
input_size = model.Config().get<std::vector<int>>("input_size");
}
bool dym = true;
input_size = model.Config().get<std::vector<int>>("input_size");
m_face_detector_ = std::make_shared<FaceDetect>(input_size[0]);
auto ret = m_face_detector_->loadData(model, model.modelType, dym);
auto ret = m_face_detector_->loadData(model, model.modelType, false);
if (ret != InferenceHelper::kRetOk) {
return HERR_ARCHIVE_LOAD_FAILURE;
}
@@ -499,5 +486,41 @@ void FaceTrack::SetTrackPreviewSize(int preview_size) {
track_preview_size_ = preview_size;
}
std::string FaceTrack::ChoiceMultiLevelDetectModel(const int32_t pixel_size) {
const int32_t supported_sizes[] = {160, 320, 640};
const std::string scheme_names[] = {"face_detect_160", "face_detect_320", "face_detect_640"};
const int32_t num_sizes = sizeof(supported_sizes) / sizeof(supported_sizes[0]);
if (pixel_size == -1)
{
return scheme_names[1];
}
// Check for exact match
for (int i = 0; i < num_sizes; ++i) {
if (pixel_size == supported_sizes[i]) {
return scheme_names[i];
}
}
// Find the closest match
int32_t closest_size = supported_sizes[0];
std::string closest_scheme = scheme_names[0];
int32_t min_diff = std::abs(pixel_size - supported_sizes[0]);
for (int i = 1; i < num_sizes; ++i) {
int32_t diff = std::abs(pixel_size - supported_sizes[i]);
if (diff < min_diff) {
min_diff = diff;
closest_size = supported_sizes[i];
closest_scheme = scheme_names[i];
}
}
INSPIRE_LOGW("Input pixel size %d is not supported. Choosing the closest scheme: %s closest_scheme for size %d.",
pixel_size, closest_scheme.c_str(), closest_size);
return closest_scheme;
}
} // namespace hyper

7
cpp-package/inspireface/cpp/inspireface/track_module/face_track.h
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@@ -138,6 +138,13 @@ private:
*/
int InitFacePoseModel(InspireModel& model);
/**
* @brief Select the detection model scheme to be used according to the input pixel level.
* @param pixel_size Currently, only 160, 320, and 640 pixel sizes are supported.
* @return Return the corresponding scheme name, only ”face_detect_160”, ”face_detect_320”, ”face_detect_640” are supported.
*/
std::string ChoiceMultiLevelDetectModel(const int32_t pixel_size);
public:
/**

2
cpp-package/inspireface/cpp/inspireface/version.txt
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@@ -1 +1 @@
InspireFace Version: 1.1.1
InspireFace Version: 1.1.2

18
cpp-package/inspireface/cpp/sample/CMakeLists.txt
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@@ -6,7 +6,7 @@ option(ISF_BUILD_SAMPLE_CLUTTERED "Whether to compile the cluttered sample progr
include_directories(${SRC_DIR})
if (ISF_ENABLE_RKNN)
set(ISF_RKNN_API_LIB ${ISF_THIRD_PARTY_DIR}/${ISF_RKNPU_MAJOR}/runtime/${ISF_RK_DEVICE_TYPE}/Linux/librknn_api/${CPU_ARCH}/)
set(ISF_RKNN_API_LIB ${ISF_THIRD_PARTY_DIR}/inspireface-precompile/rknn/${ISF_RKNPU_MAJOR}/runtime/${ISF_RK_DEVICE_TYPE}/Linux/librknn_api/${CPU_ARCH}/)
link_directories(${ISF_RKNN_API_LIB})
set(ext rknn_api dl)
endif ()
@@ -38,12 +38,16 @@ set_target_properties(MTFaceTrackSample PROPERTIES
RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/sample/"
)
# Examples of face detection and tracking
add_executable(FaceTrackVideoSample cpp/sample_face_track_video.cpp)
target_link_libraries(FaceTrackVideoSample InspireFace ${ext})
set_target_properties(FaceTrackVideoSample PROPERTIES
RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/sample/"
)
if(NOT DISABLE_GUI)
# Examples of face detection and tracking
add_executable(FaceTrackVideoSample cpp/sample_face_track_video.cpp)
target_link_libraries(FaceTrackVideoSample InspireFace ${ext})
set_target_properties(FaceTrackVideoSample PROPERTIES
RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/sample/"
)
endif()
# Examples of face recognition
add_executable(FaceRecognitionSample cpp/sample_face_recognition.cpp)

6
cpp-package/inspireface/cpp/sample/cpp/face_detect.cpp
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@@ -4,7 +4,9 @@
#include <cstddef>
#include <iostream>
#include <opencv2/core/types.hpp>
#ifndef DISABLE_GUI
#include <opencv2/highgui.hpp>
#endif
#include <opencv2/imgproc.hpp>
#include <vector>
#include "data_type.h"
@@ -38,10 +40,10 @@ int main() {
auto &item = results[i];
cv::rectangle(img, cv::Point2f(item.x1, item.y1), cv::Point2f(item.x2, item.y2), cv::Scalar(0, 0, 255), 4);
}
#ifndef DISABLE_GUI
cv::imshow("w", img);
cv::waitKey(0);
#endif
return 0;
}

6
cpp-package/inspireface/cpp/sample/cpp/sample_face_track.cpp
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@@ -31,9 +31,9 @@ int main(int argc, char* argv[]) {
// Non-video or frame sequence mode uses IMAGE-MODE, which is always face detection without tracking
HFDetectMode detMode = HF_DETECT_MODE_ALWAYS_DETECT;
// Maximum number of faces detected
HInt32 maxDetectNum = 5;
HInt32 maxDetectNum = 20;
// Face detection image input level
HInt32 detectPixelLevel = 640;
HInt32 detectPixelLevel = 160;
// Handle of the current face SDK algorithm context
HFSession session = {0};
ret = HFCreateInspireFaceSessionOptional(option, detMode, maxDetectNum, detectPixelLevel, -1, &session);
@@ -42,7 +42,7 @@ int main(int argc, char* argv[]) {
return ret;
}
HFSessionSetTrackPreviewSize(session, 640);
HFSessionSetTrackPreviewSize(session, detectPixelLevel);
HFSessionSetFilterMinimumFacePixelSize(session, 32);
// Load a image

4
cpp-package/inspireface/cpp/sample/cpp/sample_face_track_cost.cpp
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@@ -29,12 +29,12 @@ int main(int argc, char* argv[]) {
// Enable the functions in the pipeline: mask detection, live detection, and face quality detection
HOption option = HF_ENABLE_QUALITY | HF_ENABLE_MASK_DETECT | HF_ENABLE_LIVENESS;
// Non-video or frame sequence mode uses IMAGE-MODE, which is always face detection without tracking
HFDetectMode detMode = HF_DETECT_MODE_LIGHT_TRACK;
HFDetectMode detMode = HF_DETECT_MODE_ALWAYS_DETECT;
// Maximum number of faces detected
HInt32 maxDetectNum = 50;
// Handle of the current face SDK algorithm context
HFSession session = {0};
ret = HFCreateInspireFaceSessionOptional(option, detMode, maxDetectNum, -1, -1, &session);
ret = HFCreateInspireFaceSessionOptional(option, detMode, maxDetectNum, 160, -1, &session);
if (ret != HSUCCEED) {
std::cout << "Create FaceContext error: " << ret << std::endl;
return ret;

8
cpp-package/inspireface/cpp/sample/cpp/sample_face_track_video.cpp
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@@ -48,9 +48,9 @@ int main(int argc, char* argv[]) {
// Video or frame sequence mode uses VIDEO-MODE, which is face detection with tracking
HFDetectMode detMode = HF_DETECT_MODE_TRACK_BY_DETECTION;
// Maximum number of faces detected
HInt32 maxDetectNum = 5;
HInt32 maxDetectNum = 20;
// Face detection image input level
HInt32 detectPixelLevel = 640;
HInt32 detectPixelLevel = 320;
// fps in tracking-by-detection mode
HInt32 trackByDetectFps = 20;
HFSession session = {0};
@@ -61,8 +61,8 @@ int main(int argc, char* argv[]) {
return ret;
}
HFSessionSetTrackPreviewSize(session, 640);
HFSessionSetFilterMinimumFacePixelSize(session, 32);
HFSessionSetTrackPreviewSize(session, detectPixelLevel);
HFSessionSetFilterMinimumFacePixelSize(session, 0);
// Open the video file
cv::VideoCapture cap(videoPath);

2
cpp-package/inspireface/cpp/test/CMakeLists.txt
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@@ -20,7 +20,7 @@ endif ()
if (ISF_ENABLE_RKNN)
set(DEPEND rknn_api dl)
set(ISF_RKNN_API_LIB ${ISF_THIRD_PARTY_DIR}/${ISF_RKNPU_MAJOR}/runtime/${ISF_RK_DEVICE_TYPE}/Linux/librknn_api/${CPU_ARCH}/)
set(ISF_RKNN_API_LIB ${ISF_THIRD_PARTY_DIR}/inspireface-precompile/rknn/${ISF_RKNPU_MAJOR}/runtime/${ISF_RK_DEVICE_TYPE}/Linux/librknn_api/${CPU_ARCH}/)
message("Enable RKNN Inference")
link_directories(${ISF_RKNN_API_LIB})
set(DEPEND rknn_api dl)

1
cpp-package/inspireface/cpp/test/settings/enviro.h
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@@ -18,6 +18,7 @@ public:
void operator=(Enviro const&) = delete;
std::string getPackName() const { return packName; }
void setPackName(const std::string& name) { packName = name; }
const std::string &getTestResDir() const { return testResDir; }

14
cpp-package/inspireface/cpp/test/test.cpp
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@@ -1,6 +1,7 @@
//
// Created by tunm on 2023/10/11.
//
#include <string>
#define CATCH_CONFIG_RUNNER
#include <iostream>
@@ -54,11 +55,13 @@ int main(int argc, char* argv[]) {
// Pack file name and test directory
std::string pack;
std::string testDir;
std::string packPath;
// Add command line options
auto cli = session.cli()
| Catch::clara::Opt(pack, "value")["--pack"]("Resource pack filename")
| Catch::clara::Opt(testDir, "value")["--test_dir"]("Test dir resource");
| Catch::clara::Opt(testDir, "value")["--test_dir"]("Test dir resource")
| Catch::clara::Opt(packPath, "value")["--pack_path"]("The specified path to the pack file");
// Set combined CLI to the session
session.cli(cli);
@@ -75,15 +78,22 @@ int main(int argc, char* argv[]) {
TEST_PRINT("Using default test dir: {}", getTestDataDir());
}
std::string fullPath;
// Check whether custom parameters are set
if (!pack.empty()) {
SET_PACK_NAME(pack);
fullPath = GET_MODEL_FILE();
TEST_PRINT("Updated global Pack to: {}", TEST_MODEL_FILE);
} else if (!packPath.empty()) {
fullPath = packPath;
TEST_PRINT("Updated global Pack File to: {}", packPath);
} else {
fullPath = GET_MODEL_FILE();
TEST_PRINT("Using default global Pack: {}", TEST_MODEL_FILE);
}
auto ret = HFLaunchInspireFace(GET_MODEL_FILE().c_str());
std::cout << fullPath << std::endl;
auto ret = HFLaunchInspireFace(fullPath.c_str());
if (ret != HSUCCEED) {
spdlog::error("An error occurred while starting InspireFace: {}", ret);
return ret;

199
cpp-package/inspireface/cpp/test/unit/api/test_face_track.cpp
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@@ -21,7 +21,6 @@ TEST_CASE("test_FaceTrack", "[face_track]") {
HFDetectMode detMode = HF_DETECT_MODE_ALWAYS_DETECT;
HFSession session;
ret = HFCreateInspireFaceSession(parameter, detMode, 3, -1, -1, &session);
spdlog::error("error ret :{}", ret);
REQUIRE(ret == HSUCCEED);
// Get a face picture
@@ -49,7 +48,7 @@ TEST_CASE("test_FaceTrack", "[face_track]") {
cv::rectangle(image, cvRect, cv::Scalar(255, 0, 124), 2);
cv::imwrite("ww.jpg", image);
// The iou is allowed to have an error of 10%
CHECK(iou == Approx(1.0f).epsilon(0.1));
CHECK(iou == Approx(1.0f).epsilon(0.3));
ret = HFReleaseImageStream(imgHandle);
REQUIRE(ret == HSUCCEED);
@@ -224,14 +223,15 @@ TEST_CASE("test_FaceTrack", "[face_track]") {
}
SECTION("Face detection benchmark") {
#ifdef ISF_ENABLE_BENCHMARK
SECTION("Face detection benchmark@160") {
int loop = 1000;
HResult ret;
HFSessionCustomParameter parameter = {0};
HFDetectMode detMode = HF_DETECT_MODE_ALWAYS_DETECT;
HFSession session;
ret = HFCreateInspireFaceSession(parameter, detMode, 3, -1, -1, &session);
HInt32 pixLevel = 160;
ret = HFCreateInspireFaceSession(parameter, detMode, 3, pixLevel, -1, &session);
REQUIRE(ret == HSUCCEED);
// Prepare an image
@@ -250,19 +250,95 @@ TEST_CASE("test_FaceTrack", "[face_track]") {
auto cost = ((double) cv::getTickCount() - start) / cv::getTickFrequency() * 1000;
REQUIRE(ret == HSUCCEED);
REQUIRE(multipleFaceData.detectedNum == 1);
TEST_PRINT("<Benchmark> Face Detect -> Loop: {}, Total Time: {:.5f}ms, Average Time: {:.5f}ms", loop, cost, cost / loop);
record.insertBenchmarkData("Face Detect", loop, cost, cost / loop);
TEST_PRINT("<Benchmark> Face Detect@160 -> Loop: {}, Total Time: {:.5f}ms, Average Time: {:.5f}ms", loop, cost, cost / loop);
record.insertBenchmarkData("Face Detect@160", loop, cost, cost / loop);
ret = HFReleaseImageStream(imgHandle);
REQUIRE(ret == HSUCCEED);
ret = HFReleaseInspireFaceSession(session);
REQUIRE(ret == HSUCCEED);
#else
TEST_PRINT("Skip the face detection benchmark test. To run it, you need to turn on the benchmark test.");
#endif
}
SECTION("Face detection benchmark@320") {
int loop = 1000;
HResult ret;
HFSessionCustomParameter parameter = {0};
HFDetectMode detMode = HF_DETECT_MODE_ALWAYS_DETECT;
HFSession session;
HInt32 pixLevel = 320;
ret = HFCreateInspireFaceSession(parameter, detMode, 3, pixLevel, -1, &session);
REQUIRE(ret == HSUCCEED);
// Prepare an image
HFImageStream imgHandle;
auto image = cv::imread(GET_DATA("data/bulk/kun.jpg"));
ret = CVImageToImageStream(image, imgHandle);
REQUIRE(ret == HSUCCEED);
BenchmarkRecord record(getBenchmarkRecordFile());
REQUIRE(ret == HSUCCEED);
HFMultipleFaceData multipleFaceData = {0};
auto start = (double) cv::getTickCount();
for (int i = 0; i < loop; ++i) {
ret = HFExecuteFaceTrack(session, imgHandle, &multipleFaceData);
}
auto cost = ((double) cv::getTickCount() - start) / cv::getTickFrequency() * 1000;
REQUIRE(ret == HSUCCEED);
REQUIRE(multipleFaceData.detectedNum == 1);
TEST_PRINT("<Benchmark> Face Detect@320 -> Loop: {}, Total Time: {:.5f}ms, Average Time: {:.5f}ms", loop, cost, cost / loop);
record.insertBenchmarkData("Face Detect@320", loop, cost, cost / loop);
ret = HFReleaseImageStream(imgHandle);
REQUIRE(ret == HSUCCEED);
ret = HFReleaseInspireFaceSession(session);
REQUIRE(ret == HSUCCEED);
}
SECTION("Face detection benchmark@640") {
int loop = 1000;
HResult ret;
HFSessionCustomParameter parameter = {0};
HFDetectMode detMode = HF_DETECT_MODE_ALWAYS_DETECT;
HFSession session;
HInt32 pixLevel = 640;
ret = HFCreateInspireFaceSession(parameter, detMode, 3, pixLevel, -1, &session);
REQUIRE(ret == HSUCCEED);
// Prepare an image
HFImageStream imgHandle;
auto image = cv::imread(GET_DATA("data/bulk/kun.jpg"));
ret = CVImageToImageStream(image, imgHandle);
REQUIRE(ret == HSUCCEED);
BenchmarkRecord record(getBenchmarkRecordFile());
REQUIRE(ret == HSUCCEED);
HFMultipleFaceData multipleFaceData = {0};
auto start = (double) cv::getTickCount();
for (int i = 0; i < loop; ++i) {
ret = HFExecuteFaceTrack(session, imgHandle, &multipleFaceData);
}
auto cost = ((double) cv::getTickCount() - start) / cv::getTickFrequency() * 1000;
REQUIRE(ret == HSUCCEED);
REQUIRE(multipleFaceData.detectedNum == 1);
TEST_PRINT("<Benchmark> Face Detect@640 -> Loop: {}, Total Time: {:.5f}ms, Average Time: {:.5f}ms", loop, cost, cost / loop);
record.insertBenchmarkData("Face Detect@640", loop, cost, cost / loop);
ret = HFReleaseImageStream(imgHandle);
REQUIRE(ret == HSUCCEED);
ret = HFReleaseInspireFaceSession(session);
REQUIRE(ret == HSUCCEED);
}
#else
TEST_PRINT("Skip the face detection benchmark test. To run it, you need to turn on the benchmark test.");
#endif
SECTION("Face light track benchmark") {
#ifdef ISF_ENABLE_BENCHMARK
int loop = 1000;
@@ -289,7 +365,7 @@ TEST_CASE("test_FaceTrack", "[face_track]") {
}
auto cost = ((double) cv::getTickCount() - start) / cv::getTickFrequency() * 1000;
REQUIRE(ret == HSUCCEED);
REQUIRE(multipleFaceData.detectedNum == 1);
REQUIRE(multipleFaceData.detectedNum > 0);
TEST_PRINT("<Benchmark> Face Track -> Loop: {}, Total Time: {:.5f}ms, Average Time: {:.5f}ms", loop, cost, cost / loop);
record.insertBenchmarkData("Face Track", loop, cost, cost / loop);
@@ -304,4 +380,107 @@ TEST_CASE("test_FaceTrack", "[face_track]") {
}
}
TEST_CASE("test_MultipleLevelFaceDetect", "[face_detect]") {
DRAW_SPLIT_LINE
TEST_PRINT_OUTPUT(true);
SECTION("Detect input 160px") {
HResult ret;
HFSessionCustomParameter parameter = {0};
HFDetectMode detMode = HF_DETECT_MODE_ALWAYS_DETECT;
HFSession session;
HInt32 detectPixelLevel = 160;
ret = HFCreateInspireFaceSession(parameter, detMode, 20, detectPixelLevel, -1, &session);
REQUIRE(ret == HSUCCEED);
HFSessionSetTrackPreviewSize(session, detectPixelLevel);
HFSessionSetFilterMinimumFacePixelSize(session, 0);
// Get a face picture
HFImageStream imgHandle;
auto image = cv::imread(GET_DATA("data/bulk/pedestrian.png"));
ret = CVImageToImageStream(image, imgHandle);
REQUIRE(ret == HSUCCEED);
// Extract basic face information from photos
HFMultipleFaceData multipleFaceData = {0};
ret = HFExecuteFaceTrack(session, imgHandle, &multipleFaceData);
REQUIRE(ret == HSUCCEED);
CHECK(multipleFaceData.detectedNum > 0);
CHECK(multipleFaceData.detectedNum < 7);
ret = HFReleaseImageStream(imgHandle);
REQUIRE(ret == HSUCCEED);
ret = HFReleaseInspireFaceSession(session);
REQUIRE(ret == HSUCCEED);
}
SECTION("Detect input 320px") {
HResult ret;
HFSessionCustomParameter parameter = {0};
HFDetectMode detMode = HF_DETECT_MODE_ALWAYS_DETECT;
HFSession session;
HInt32 detectPixelLevel = 320;
ret = HFCreateInspireFaceSession(parameter, detMode, 20, detectPixelLevel, -1, &session);
REQUIRE(ret == HSUCCEED);
HFSessionSetTrackPreviewSize(session, detectPixelLevel);
HFSessionSetFilterMinimumFacePixelSize(session, 0);
// Get a face picture
HFImageStream imgHandle;
auto image = cv::imread(GET_DATA("data/bulk/pedestrian.png"));
ret = CVImageToImageStream(image, imgHandle);
REQUIRE(ret == HSUCCEED);
// Extract basic face information from photos
HFMultipleFaceData multipleFaceData = {0};
ret = HFExecuteFaceTrack(session, imgHandle, &multipleFaceData);
REQUIRE(ret == HSUCCEED);
CHECK(multipleFaceData.detectedNum > 9);
CHECK(multipleFaceData.detectedNum < 15);
ret = HFReleaseImageStream(imgHandle);
REQUIRE(ret == HSUCCEED);
ret = HFReleaseInspireFaceSession(session);
REQUIRE(ret == HSUCCEED);
}
SECTION("Detect input 640px") {
HResult ret;
HFSessionCustomParameter parameter = {0};
HFDetectMode detMode = HF_DETECT_MODE_ALWAYS_DETECT;
HFSession session;
HInt32 detectPixelLevel = 640;
ret = HFCreateInspireFaceSession(parameter, detMode, 25, detectPixelLevel, -1, &session);
REQUIRE(ret == HSUCCEED);
HFSessionSetTrackPreviewSize(session, detectPixelLevel);
HFSessionSetFilterMinimumFacePixelSize(session, 0);
// Get a face picture
HFImageStream imgHandle;
auto image = cv::imread(GET_DATA("data/bulk/pedestrian.png"));
ret = CVImageToImageStream(image, imgHandle);
REQUIRE(ret == HSUCCEED);
// Extract basic face information from photos
HFMultipleFaceData multipleFaceData = {0};
ret = HFExecuteFaceTrack(session, imgHandle, &multipleFaceData);
REQUIRE(ret == HSUCCEED);
CHECK(multipleFaceData.detectedNum > 15);
CHECK(multipleFaceData.detectedNum < 25);
ret = HFReleaseImageStream(imgHandle);
REQUIRE(ret == HSUCCEED);
ret = HFReleaseInspireFaceSession(session);
REQUIRE(ret == HSUCCEED);
}
}

2
cpp-package/inspireface/cpp/test/unit/api/test_feature_manage.cpp
View File

@@ -335,7 +335,7 @@ TEST_CASE("test_SearchTopK", "[feature_search_top_k]") {
configuration.dbPath = dbPathStr;
configuration.featureBlockNum = 20;
configuration.searchMode = HF_SEARCH_MODE_EXHAUSTIVE;
configuration.searchThreshold = 0.48f;
configuration.searchThreshold = 0.46f;
// Delete the previous data before testing
if (std::remove(configuration.dbPath) != 0) {
spdlog::trace("Error deleting file");