221 lines
7.7 KiB
C++
221 lines
7.7 KiB
C++
#pragma once
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#include "ANSODEngine.h"
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#include "ANSYOLOOD.h"
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#include "ANSTENSORRTOD.h"
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#include "ANSTENSORRTCL.h"
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#include "ANSOPENVINOCL.h"
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#include "ANSOPENVINOOD.h"
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#include "ANSYOLOV10RTOD.h"
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#include "ANSYOLOV10OVOD.h"
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#include "ANSCUSTOMDetector.h"
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#include "ANSFD.h"
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#include "ANSANOMALIB.h"
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#include "ANSPOSE.h"
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#include "ANSSAM.h"
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#include <pipelines/metadata.h>
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#include <models/input_data.h>
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#include "utils/visualizer.hpp"
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#include <turbojpeg.h>
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#include <vector>
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#include <map>
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#include <string>
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#include "ANSLibsLoader.h"
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namespace ANSCENTER
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{
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//------------------------------------------------------------------------------------------------------------------------//
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// Facial Recognition base class
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void ANSFRBase::CheckLicense() {
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try {
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_licenseValid = ANSCENTER::ANSLicenseHelper::LicenseVerification(_licenseKey, 1004, "ANSFR");//Default productId=1005
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}
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catch (std::exception& e) {
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this->_logger.LogFatal("ANSFRBase::CheckLicense()", e.what(), __FILE__, __LINE__);
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}
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}
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bool ANSFRBase::LoadModel(const std::string& modelZipFilePath, const std::string& modelZipPassword)
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{
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try {
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ANSCENTER::ANSLibsLoader::Initialize();
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_modelFolder = "";
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_modelConfigFile = "";
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_modelFolder.clear();
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_modelConfigFile.clear();
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// 0. Check if the modelZipFilePath exist?
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if (!FileExist(modelZipFilePath)) {
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this->_logger.LogFatal("ANSFRBase::LoadModel", "Model zip file is not exist", __FILE__, __LINE__);
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}
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// 1. Unzip model zip file to a special location with folder name as model file (and version)
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std::string outputFolder;
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std::vector<std::string> passwordArray;
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if (!modelZipPassword.empty()) passwordArray.push_back(modelZipPassword);
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passwordArray.push_back("Sh7O7nUe7vJ/417W0gWX+dSdfcP9hUqtf/fEqJGqxYL3PedvHubJag==");
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passwordArray.push_back("3LHxGrjQ7kKDJBD9MX86H96mtKLJaZcTYXrYRdQgW8BKGt7enZHYMg==");
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passwordArray.push_back("AnsCustomModels20@$");
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passwordArray.push_back("AnsDemoModels20@!");
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std::string modelName = GetFileNameWithoutExtension(modelZipFilePath);
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//this->_logger.LogDebug("ANSFRBase::LoadModel. Model name", modelName, __FILE__, __LINE__);
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size_t vectorSize = passwordArray.size();
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for (size_t i = 0; i < vectorSize; i++) {
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if (ExtractPasswordProtectedZip(modelZipFilePath, passwordArray[i], modelName, _modelFolder, false))
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break; // Break the loop when the condition is met.
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}
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// 2. Check if the outputFolder exist
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if (!std::filesystem::exists(_modelFolder)) {
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this->_logger.LogError("ANSFRBase::LoadModel. Output model folder is not exist", _modelFolder, __FILE__, __LINE__);
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return false; // That means the model file is not exist or the password is not correct
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}
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// 3. Check if the model has the configuration file
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std::string modelConfigName = "model_config.json";
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_modelConfigFile = CreateFilePath(_modelFolder, modelConfigName);
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return true;
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}
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catch (std::exception& e) {
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this->_logger.LogFatal("ANSFRBase::LoadModel", e.what(), __FILE__, __LINE__);
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return false;
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}
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}
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bool ANSFRBase::Initialize(std::string licenseKey, ModelConfig modelConfig, const std::string& modelZipFilePath, const std::string& modelZipPassword, std::string& labelMap) {
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try {
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ANSCENTER::ANSLibsLoader::Initialize();
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_licenseKey = licenseKey;
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_licenseValid = false;
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_modelFolder = "";
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_modelConfigFile = "";
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_modelFolder.clear();
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_modelConfigFile.clear();
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CheckLicense();
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if (!_licenseValid) {
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this->_logger.LogError("ANSFRBase::Initialize", "Invalid License", __FILE__, __LINE__);
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return false;
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}
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// 0. Check if the modelZipFilePath exist?
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if (!FileExist(modelZipFilePath)) {
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this->_logger.LogFatal("ANSFRBase::Initialize", "Model zip file is not exist", __FILE__, __LINE__);
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}
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// 1. Unzip model zip file to a special location with folder name as model file (and version)
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std::string outputFolder;
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std::vector<std::string> passwordArray;
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if (!modelZipPassword.empty()) passwordArray.push_back(modelZipPassword);
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passwordArray.push_back("Sh7O7nUe7vJ/417W0gWX+dSdfcP9hUqtf/fEqJGqxYL3PedvHubJag==");
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passwordArray.push_back("3LHxGrjQ7kKDJBD9MX86H96mtKLJaZcTYXrYRdQgW8BKGt7enZHYMg==");
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passwordArray.push_back("AnsCustomModels20@$");
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passwordArray.push_back("AnsDemoModels20@!");
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std::string modelName = GetFileNameWithoutExtension(modelZipFilePath);
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//this->_logger.LogDebug("ANSFRBase::Initialize. Model name", modelName, __FILE__, __LINE__);
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size_t vectorSize = passwordArray.size();
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for (size_t i = 0; i < vectorSize; i++) {
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if (ExtractPasswordProtectedZip(modelZipFilePath, passwordArray[i], modelName, _modelFolder, false))
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break; // Break the loop when the condition is met.
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}
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// 2. Check if the outputFolder exist
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if (!std::filesystem::exists(_modelFolder)) {
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this->_logger.LogError("ANSFRBase::Initialize. Output model folder is not exist", _modelFolder, __FILE__, __LINE__);
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return false; // That means the model file is not exist or the password is not correct
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}
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// 3. Check if the model has the configuration file
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std::string modelConfigName = "model_config.json";
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_modelConfigFile = CreateFilePath(_modelFolder, modelConfigName);
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return true;
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}
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catch (std::exception& e) {
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this->_logger.LogFatal("ANSFRBase::Initialize", e.what(), __FILE__, __LINE__);
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return false;
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}
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}
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bool ANSFRBase::OptimizeModel(bool fp16, std::string& optimizedModelFolder) {
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try {
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ANSCENTER::ANSLibsLoader::Initialize();
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return true;
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}
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catch (std::exception& e) {
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this->_logger.LogFatal("ANSFRBase::OptimizeModel", e.what(), __FILE__, __LINE__);
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return false;
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}
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}
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ANSFRBase::~ANSFRBase() {
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try {
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}
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catch (std::exception& e) {
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this->_logger.LogFatal("ANSFRBase::~ANSFRBase", e.what(), __FILE__, __LINE__);
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}
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}
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std::vector<float> ANSFRBase::L2Normalize(const std::vector<float>& values) {
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try {
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size_t num_val = values.size();
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if (num_val == 0) {
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return {};
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}
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std::vector<float> norm(num_val);
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float l2_sum_val = 0.f;
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for (const auto& value : values) {
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l2_sum_val += (value * value);
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}
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float l2_sum_sqrt = std::sqrt(l2_sum_val);
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// Check for zero division using machine epsilon
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if (std::abs(l2_sum_sqrt) < std::numeric_limits<float>::epsilon())
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{
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// Return a default value or handle the error as needed
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return std::vector<float>(num_val, 0.0f);
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}
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for (size_t i = 0; i < num_val; ++i) {
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norm[i] = values[i] / l2_sum_sqrt;
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}
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return norm;
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}
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catch (std::exception& e) {
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this->_logger.LogFatal("ANSFRBase::L2Normalize", e.what(), __FILE__, __LINE__);
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return {};
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}
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}
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float ANSFRBase::CosineSimilarity(const std::vector<float>& a, const std::vector<float>& b, bool normalized) {
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try {
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if (a.size() != b.size() || a.empty()) {
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// Return a default value or handle the error as needed
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return 1.0f;
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}
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size_t num_val = a.size();
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float mul_a = 0.f, mul_b = 0.f, mul_ab = 0.f;
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if (normalized) {
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for (size_t i = 0; i < num_val; ++i) {
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mul_a += (a[i] * a[i]);
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mul_b += (b[i] * b[i]);
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mul_ab += (a[i] * b[i]);
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}
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}
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else {
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auto norm_a = L2Normalize(a);
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auto norm_b = L2Normalize(b);
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for (size_t i = 0; i < num_val; ++i) {
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mul_a += (norm_a[i] * norm_a[i]);
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mul_b += (norm_b[i] * norm_b[i]);
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mul_ab += (norm_a[i] * norm_b[i]);
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}
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}
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// Check for zero division using machine epsilon
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float denominator = std::sqrt(mul_a) * std::sqrt(mul_b);
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if (std::abs(denominator) < std::numeric_limits<float>::epsilon()) {
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// Return a default value or handle the error as needed
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return 1.0f;
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}
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return (mul_ab / denominator);
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}
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catch (std::exception& e) {
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this->_logger.LogFatal("ANSFRBase::CosineSimilarity", e.what(), __FILE__, __LINE__);
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return 1.0f;
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}
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}
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}
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