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Fix mixed UTF16 issue (LabVIEW) and fix ANSFR for Intel

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This commit is contained in:
Tuan Nghia Nguyen
2026-04-08 08:47:10 +10:00
parent 866e0282e2
commit a4a8caaa86
10 changed files with 594 additions and 38 deletions
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46
modules/ANSFR/ANSFaceRecognizer.cpp
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@@ -22,12 +22,19 @@ namespace ANSCENTER {
ov::Core core;
std::vector<std::string> available_devices = core.get_available_devices();
ANS_DBG("FaceRecognizer", "OpenVINO available devices: %zu", available_devices.size());
for (const auto& d : available_devices) {
ANS_DBG("FaceRecognizer", " OpenVINO device: %s", d.c_str());
}
std::vector<std::string> priority_devices = { "GPU", "CPU" };
for (const auto& device : priority_devices) {
if (std::find(available_devices.begin(), available_devices.end(), device) != available_devices.end()) {
ANS_DBG("FaceRecognizer", "OpenVINO selected device: %s", device.c_str());
return device;
}
}
ANS_DBG("FaceRecognizer", "OpenVINO fallback to CPU");
return "CPU";
}
@@ -37,12 +44,18 @@ namespace ANSCENTER {
const std::string& modelZipPassword,
std::string& labelMap)
{
ANS_DBG("FaceRecognizer", "Initialize: modelZip=%s", modelZipFilePath.c_str());
bool result = ANSFRBase::Initialize(licenseKey, modelConfig, modelZipFilePath, modelZipPassword, labelMap);
if (!result) return false;
if (!result) {
ANS_DBG("FaceRecognizer", "ANSFRBase::Initialize FAILED");
return false;
}
#ifdef CPU_MODE
engineType = EngineType::CPU;
ANS_DBG("FaceRecognizer", "CPU_MODE forced: engineType=CPU");
#else
engineType = ANSLicenseHelper::CheckHardwareInformation();
ANS_DBG("FaceRecognizer", "HW detection: engineType=%d", static_cast<int>(engineType));
#endif
try {
_modelConfig = modelConfig;
@@ -52,6 +65,12 @@ namespace ANSCENTER {
m_knownPersonThresh = _modelConfig.unknownPersonThreshold;
if (m_knownPersonThresh == 0.0f) m_knownPersonThresh = 0.35f;
ANS_DBG("FaceRecognizer", "engineType=%d (NVIDIA=%d, OPENVINO=%d, AMD=%d, CPU=%d)",
static_cast<int>(engineType),
static_cast<int>(EngineType::NVIDIA_GPU),
static_cast<int>(EngineType::OPENVINO_GPU),
static_cast<int>(EngineType::AMD_GPU),
static_cast<int>(EngineType::CPU));
if (engineType == EngineType::NVIDIA_GPU) {
// 1. Load ONNX model
std::string onnxfile = CreateFilePath(_modelFolder, "ansfacerecognizer.onnx");
@@ -97,6 +116,11 @@ namespace ANSCENTER {
_modelFilePath, __FILE__, __LINE__);
return false;
}
// Create CUDA stream for GPU preprocessing (lazy init)
if (!m_gpuStream) {
m_gpuStream = std::make_unique<cv::cuda::Stream>();
}
}
}
else {
@@ -112,10 +136,13 @@ namespace ANSCENTER {
_modelFilePath, __FILE__, __LINE__);
return false;
}
faceRecognizer = std::make_unique<GlintArcFace>(faceidModel);
ANS_DBG("FaceRecognizer", "Creating GlintArcFace with engineType=%d model=%s",
static_cast<int>(engineType), faceidModel.c_str());
faceRecognizer = std::make_unique<GlintArcFace>(faceidModel, engineType);
if (!faceRecognizer) {
_logger.LogFatal("ANSFaceRecognizer::Initialize",
"Failed to initialize ONNX face recognizer", __FILE__, __LINE__);
ANS_DBG("FaceRecognizer", "FAILED: GlintArcFace returned null");
return false;
}
#else
@@ -151,6 +178,7 @@ namespace ANSCENTER {
return true;
}
catch (const std::exception& e) {
ANS_DBG("FaceRecognizer", "Initialize EXCEPTION: %s", e.what());
_logger.LogFatal("ANSFaceRecognizer::Initialize", e.what(), __FILE__, __LINE__);
return false;
}
@@ -688,8 +716,8 @@ namespace ANSCENTER {
}
cv::Mat cpuRGB;
cv::cvtColor(cpuResized, cpuRGB, cv::COLOR_BGR2RGB);
m_gpuRgb.upload(cpuRGB, m_gpuStream);
m_gpuStream.waitForCompletion();
m_gpuRgb.upload(cpuRGB, *m_gpuStream);
m_gpuStream->waitForCompletion();
// Prepare inference inputs
std::vector<cv::cuda::GpuMat> inputVec;
@@ -703,7 +731,7 @@ namespace ANSCENTER {
bool succ = m_trtEngine->runInference(inputs, featureVectors);
// Synchronize stream
m_gpuStream.waitForCompletion();
m_gpuStream->waitForCompletion();
if (!succ) {
_logger.LogError("ANSFaceRecognizer::RunArcFace",
@@ -783,11 +811,11 @@ namespace ANSCENTER {
cv::cuda::GpuMat d_img = gpuFaceROIs[i]; // already on GPU
if (d_img.cols != GPU_FACE_WIDTH || d_img.rows != GPU_FACE_HEIGHT) {
cv::cuda::GpuMat d_resized;
cv::cuda::resize(d_img, d_resized, targetSize, 0, 0, cv::INTER_LINEAR, m_gpuStream);
cv::cuda::resize(d_img, d_resized, targetSize, 0, 0, cv::INTER_LINEAR, *m_gpuStream);
d_img = d_resized;
}
cv::cuda::GpuMat d_rgb;
cv::cuda::cvtColor(d_img, d_rgb, cv::COLOR_BGR2RGB, 0, m_gpuStream);
cv::cuda::cvtColor(d_img, d_rgb, cv::COLOR_BGR2RGB, 0, *m_gpuStream);
batchGpu.emplace_back(std::move(d_rgb));
} else {
const auto& roi = faceROIs[i];
@@ -807,7 +835,7 @@ namespace ANSCENTER {
cv::Mat cpuRGB;
cv::cvtColor(cpuResized, cpuRGB, cv::COLOR_BGR2RGB);
cv::cuda::GpuMat d_rgb;
d_rgb.upload(cpuRGB, m_gpuStream);
d_rgb.upload(cpuRGB, *m_gpuStream);
batchGpu.emplace_back(std::move(d_rgb));
}
}
@@ -823,7 +851,7 @@ namespace ANSCENTER {
FR_START_TIMER(trt_infer);
std::vector<std::vector<std::vector<float>>> featureVectors;
bool succ = m_trtEngine->runInference(inputs, featureVectors);
m_gpuStream.waitForCompletion();
m_gpuStream->waitForCompletion();
FR_END_TIMER(trt_infer, "RunArcFaceBatch TRT inference (batch=" + std::to_string(actualCount) + ")");
if (!succ) {