Remove locks
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@@ -4,7 +4,6 @@
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#ifdef USEONNXOV
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#endif
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namespace ANSCENTER {
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bool YOLO12OD::OptimizeModel(bool fp16, std::string& optimizedModelFolder) {
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std::lock_guard<std::recursive_mutex> lock(_mutex);
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@@ -28,15 +27,6 @@ namespace ANSCENTER {
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try {
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bool result = ANSODBase::LoadModel(modelZipFilePath, modelZipPassword);
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if (!result) return false;
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// Serialize derived init against concurrent extract re-entries on the
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// same folder. See ModelFolderLockGuard in ANSEngineCommon.h.
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ModelFolderLockGuard _flg(_modelFolder, "YOLO12OD::LoadModel");
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if (!_flg.acquired()) {
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this->_logger.LogError("YOLO12OD::LoadModel",
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"Timed out waiting for model-folder lock: " + _modelFolder,
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__FILE__, __LINE__);
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return false;
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}
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_modelConfig.detectionType = ANSCENTER::DetectionType::DETECTION;
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_modelConfig.inpHeight = 640;
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_modelConfig.inpWidth = 640;
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@@ -96,15 +86,6 @@ namespace ANSCENTER {
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try {
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bool result = ANSODBase::LoadModelFromFolder(licenseKey, modelConfig, modelName, className,modelFolder, labelMap);
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if (!result) return false;
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// Serialize derived init against concurrent extract re-entries on the
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// same folder. See ModelFolderLockGuard in ANSEngineCommon.h.
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ModelFolderLockGuard _flg(_modelFolder, "YOLO12OD::LoadModelFromFolder");
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if (!_flg.acquired()) {
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this->_logger.LogError("YOLO12OD::LoadModelFromFolder",
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"Timed out waiting for model-folder lock: " + _modelFolder,
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__FILE__, __LINE__);
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return false;
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}
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std::string _modelName = modelName;
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if (_modelName.empty()) {
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_modelName = "train_last";
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@@ -178,15 +159,6 @@ namespace ANSCENTER {
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try {
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bool result = ANSODBase::Initialize(licenseKey, modelConfig, modelZipFilePath, modelZipPassword, labelMap);
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if (!result) return false;
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// Serialize derived init against concurrent extract re-entries on the
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// same folder. See ModelFolderLockGuard in ANSEngineCommon.h.
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ModelFolderLockGuard _flg(_modelFolder, "YOLO12OD::Initialize");
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if (!_flg.acquired()) {
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this->_logger.LogError("YOLO12OD::Initialize",
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"Timed out waiting for model-folder lock: " + _modelFolder,
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__FILE__, __LINE__);
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return false;
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}
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// Parsing for YOLO only here
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_modelConfig = modelConfig;
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_modelConfig.detectionType = ANSCENTER::DetectionType::DETECTION;
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@@ -501,7 +473,6 @@ namespace ANSCENTER {
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}
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}
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cv::Mat YOLO12OD::preprocess(const cv::Mat& image, std::vector<float>& blob, std::vector<int64_t>& inputTensorShape) {
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std::lock_guard<std::recursive_mutex> lock(_mutex);
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m_imgWidth = image.cols;
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