mirror of
https://github.com/deepinsight/insightface.git
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Add the inspireface project to cpp-package.
This commit is contained in:
JingyuYan
517
cpp-package/inspireface/cpp/test/unit/api/test_feature_hub.cpp
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517
cpp-package/inspireface/cpp/test/unit/api/test_feature_hub.cpp
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@@ -0,0 +1,517 @@
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//
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// Created by tunm on 2024/4/13.
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//
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#include <iostream>
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#include "settings/test_settings.h"
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#include "inspireface/c_api/inspireface.h"
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#include "unit/test_helper/test_help.h"
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#include <thread>
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TEST_CASE("test_FeatureHubBase", "[FeatureHub][BasicFunction]") {
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DRAW_SPLIT_LINE
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TEST_PRINT_OUTPUT(true);
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SECTION("FeatureHub basic function") {
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HResult ret;
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HFFeatureHubConfiguration configuration = {0};
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auto dbPath = GET_SAVE_DATA(".test");
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HString dbPathStr = new char[dbPath.size() + 1];
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std::strcpy(dbPathStr, dbPath.c_str());
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configuration.enablePersistence = 1;
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configuration.dbPath = dbPathStr;
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configuration.featureBlockNum = 20;
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configuration.searchMode = HF_SEARCH_MODE_EXHAUSTIVE;
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configuration.searchThreshold = 0.48f;
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// Delete the previous data before testing
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if (std::remove(configuration.dbPath) != 0) {
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spdlog::trace("Error deleting file");
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}
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ret = HFFeatureHubDataEnable(configuration);
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REQUIRE(ret == HSUCCEED);
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ret = HFFeatureHubDataDisable();
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REQUIRE(ret == HSUCCEED);
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delete []dbPathStr;
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}
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SECTION("FeatureHub search top-k") {
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HResult ret;
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HFFeatureHubConfiguration configuration = {0};
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auto dbPath = GET_SAVE_DATA(".test");
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HString dbPathStr = new char[dbPath.size() + 1];
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std::strcpy(dbPathStr, dbPath.c_str());
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configuration.enablePersistence = 1;
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configuration.dbPath = dbPathStr;
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configuration.featureBlockNum = 20;
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configuration.searchMode = HF_SEARCH_MODE_EXHAUSTIVE;
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configuration.searchThreshold = 0.48f;
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// Delete the previous data before testing
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if (std::remove(configuration.dbPath) != 0) {
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spdlog::trace("Error deleting file");
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}
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ret = HFFeatureHubDataEnable(configuration);
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REQUIRE(ret == HSUCCEED);
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std::vector<std::vector<HFloat>> baseFeatures;
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size_t genSizeOfBase = 2000;
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HInt32 featureLength;
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HFGetFeatureLength(&featureLength);
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REQUIRE(featureLength > 0);
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for (int i = 0; i < genSizeOfBase; ++i) {
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auto feat = GenerateRandomFeature(featureLength);
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baseFeatures.push_back(feat);
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auto name = std::to_string(i);
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// Establish a security buffer
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std::vector<char> nameBuffer(name.begin(), name.end());
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nameBuffer.push_back('\0');
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// Construct face feature
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HFFaceFeature feature = {0};
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feature.size = feat.size();
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feature.data = feat.data();
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HFFaceFeatureIdentity identity = {0};
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identity.feature = &feature;
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identity.customId = i;
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identity.tag = nameBuffer.data();
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ret = HFFeatureHubInsertFeature(identity);
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REQUIRE(ret == HSUCCEED);
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}
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HInt32 totalFace;
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ret = HFFeatureHubGetFaceCount(&totalFace);
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REQUIRE(ret == HSUCCEED);
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REQUIRE(totalFace == genSizeOfBase);
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// 2000 data was imported
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HInt32 targetId = 523;
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auto targetFeature = baseFeatures[targetId];
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std::vector<std::vector<HFloat>> similarVectors;
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std::vector<HInt32> coverIds = {2, 300, 524, 789, 1024, 1995};
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for (int i = 0; i < coverIds.size(); ++i) {
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auto feat = SimulateSimilarVector(targetFeature);
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// Construct face feature
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HFFaceFeature feature = {0};
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feature.size = feat.size();
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feature.data = feat.data();
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HFFaceFeatureIdentity identity = {0};
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identity.feature = &feature;
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identity.customId = coverIds[i];
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identity.tag = "HOLD";
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ret = HFFeatureHubFaceUpdate(identity);
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REQUIRE(ret == HSUCCEED);
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}
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// Generate a new similar feature for search
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auto topK = 10;
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auto searchFeat = SimulateSimilarVector(targetFeature);
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HFFaceFeature searchFeature = {0};
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searchFeature.size = searchFeat.size();
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searchFeature.data = searchFeat.data();
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HFSearchTopKResults results = {0};
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ret = HFFeatureHubFaceSearchTopK(searchFeature, topK, &results);
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REQUIRE(ret == HSUCCEED);
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coverIds.push_back(targetId);
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REQUIRE(coverIds.size() == results.size);
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for (int i = 0; i < results.size; ++i) {
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REQUIRE(std::find(coverIds.begin(), coverIds.end(), results.customIds[i]) != coverIds.end());
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}
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ret = HFFeatureHubDataDisable();
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REQUIRE(ret == HSUCCEED);
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delete []dbPathStr;
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}
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SECTION("Repeat the enable and disable tests") {
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HResult ret;
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auto dbPath = GET_SAVE_DATA(".test");
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HString dbPathStr = new char[dbPath.size() + 1];
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HFFeatureHubConfiguration configuration = {0};
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configuration.enablePersistence = 0;
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configuration.dbPath = dbPathStr;
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configuration.featureBlockNum = 20;
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configuration.searchMode = HF_SEARCH_MODE_EXHAUSTIVE;
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configuration.searchThreshold = 0.48f;
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ret = HFFeatureHubDataEnable(configuration);
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REQUIRE(ret == HSUCCEED);
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ret = HFFeatureHubDataEnable(configuration);
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REQUIRE(ret == HERR_FT_HUB_ENABLE_REPETITION);
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ret = HFFeatureHubDataDisable();
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REQUIRE(ret == HSUCCEED);
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ret = HFFeatureHubDataDisable();
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REQUIRE(ret == HERR_FT_HUB_DISABLE_REPETITION);
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delete []dbPathStr;
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}
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SECTION("Only memory storage is used") {
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HResult ret;
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HFFeatureHubConfiguration configuration = {0};
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configuration.enablePersistence = 0;
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ret = HFFeatureHubDataEnable(configuration);
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REQUIRE(ret == HSUCCEED);
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// TODO
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ret = HFFeatureHubDataDisable();
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REQUIRE(ret == HSUCCEED);
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}
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}
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TEST_CASE("test_ConcurrencyInsertion", "[FeatureHub][Concurrency]") {
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DRAW_SPLIT_LINE
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TEST_PRINT_OUTPUT(true);
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HResult ret;
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HFFeatureHubConfiguration configuration = {0};
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auto dbPath = GET_SAVE_DATA(".test");
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HString dbPathStr = new char[dbPath.size() + 1];
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std::strcpy(dbPathStr, dbPath.c_str());
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configuration.enablePersistence = 1;
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configuration.dbPath = dbPathStr;
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configuration.featureBlockNum = 20;
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configuration.searchMode = HF_SEARCH_MODE_EXHAUSTIVE;
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configuration.searchThreshold = 0.48f;
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// Delete the previous data before testing
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if (std::remove(configuration.dbPath) != 0) {
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spdlog::trace("Error deleting file");
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}
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ret = HFFeatureHubDataEnable(configuration);
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REQUIRE(ret == HSUCCEED);
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HInt32 baseNum;
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ret = HFFeatureHubGetFaceCount(&baseNum);
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REQUIRE(ret == HSUCCEED);
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HInt32 featureLength;
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HFGetFeatureLength(&featureLength);
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const int numThreads = 4;
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const int insertsPerThread = 50;
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std::vector<std::thread> threads;
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auto beginGenId = 2000;
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for (int i = 0; i < numThreads; ++i) {
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threads.emplace_back([=]() { // 使用值捕获以避免捕获引用后变量改变
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for (int j = 0; j < insertsPerThread; ++j) {
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auto feat = GenerateRandomFeature(featureLength);
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auto name = std::to_string(beginGenId + j + i * insertsPerThread);
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std::vector<char> nameBuffer(name.begin(), name.end());
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nameBuffer.push_back('\0');
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HFFaceFeature feature = {0};
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feature.size = feat.size();
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feature.data = feat.data();
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HFFaceFeatureIdentity featureIdentity = {0};
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featureIdentity.feature = &feature;
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featureIdentity.customId = beginGenId + j + i * insertsPerThread; // 确保 customId 唯一
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featureIdentity.tag = nameBuffer.data();
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auto ret = HFFeatureHubInsertFeature(featureIdentity);
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REQUIRE(ret == HSUCCEED);
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}
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});
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}
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for (auto &th : threads) {
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th.join();
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}
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HInt32 count;
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ret = HFFeatureHubGetFaceCount(&count);
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REQUIRE(ret == HSUCCEED);
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REQUIRE(count == baseNum + numThreads * insertsPerThread); // Ensure that the previous base data is added to the newly inserted data
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ret = HFFeatureHubDataDisable();
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REQUIRE(ret == HSUCCEED);
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delete []dbPathStr;
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}
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TEST_CASE("test_ConcurrencyRemove", "[FeatureHub][Concurrency]") {
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DRAW_SPLIT_LINE
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TEST_PRINT_OUTPUT(true);
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HResult ret;
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HFFeatureHubConfiguration configuration = {0};
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auto dbPath = GET_SAVE_DATA(".test");
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HString dbPathStr = new char[dbPath.size() + 1];
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std::strcpy(dbPathStr, dbPath.c_str());
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configuration.enablePersistence = 1;
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configuration.dbPath = dbPathStr;
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configuration.featureBlockNum = 20;
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configuration.searchMode = HF_SEARCH_MODE_EXHAUSTIVE;
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configuration.searchThreshold = 0.48f;
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// Delete the previous data before testing
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if (std::remove(configuration.dbPath) != 0) {
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spdlog::trace("Error deleting file");
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}
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ret = HFFeatureHubDataEnable(configuration);
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REQUIRE(ret == HSUCCEED);
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std::vector<std::vector<HFloat>> baseFeatures;
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size_t genSizeOfBase = 1000;
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HInt32 featureLength;
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HFGetFeatureLength(&featureLength);
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REQUIRE(featureLength > 0);
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for (int i = 0; i < genSizeOfBase; ++i) {
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auto feat = GenerateRandomFeature(featureLength);
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baseFeatures.push_back(feat);
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auto name = std::to_string(i);
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// Establish a security buffer
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std::vector<char> nameBuffer(name.begin(), name.end());
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nameBuffer.push_back('\0');
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// Construct face feature
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HFFaceFeature feature = {0};
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feature.size = feat.size();
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feature.data = feat.data();
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HFFaceFeatureIdentity identity = {0};
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identity.feature = &feature;
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identity.customId = i;
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identity.tag = nameBuffer.data();
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ret = HFFeatureHubInsertFeature(identity);
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REQUIRE(ret == HSUCCEED);
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}
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HInt32 totalFace;
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ret = HFFeatureHubGetFaceCount(&totalFace);
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REQUIRE(ret == HSUCCEED);
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REQUIRE(totalFace == genSizeOfBase);
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const int numThreads = 4;
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const int removePerThread = genSizeOfBase / 5;
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std::vector<std::thread> threads;
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for (int t = 0; t < numThreads; ++t) {
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threads.emplace_back([&, t]() {
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for (int j = 0; j < removePerThread; ++j) {
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int idToRemove = t * removePerThread + j;
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auto ret = HFFeatureHubFaceRemove(idToRemove);
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REQUIRE(ret == HSUCCEED);
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}
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});
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}
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// Wait for all threads to complete
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for (auto &th : threads) {
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th.join();
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}
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HInt32 remainingCount;
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ret = HFFeatureHubGetFaceCount(&remainingCount);
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REQUIRE(ret == HSUCCEED);
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REQUIRE(remainingCount == genSizeOfBase - numThreads * removePerThread);
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TEST_PRINT("Remaining Count: {}", remainingCount);
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ret = HFFeatureHubDataDisable();
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REQUIRE(ret == HSUCCEED);
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delete []dbPathStr;
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}
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TEST_CASE("test_ConcurrencySearch", "[FeatureHub][Concurrency]") {
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DRAW_SPLIT_LINE
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TEST_PRINT_OUTPUT(true);
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HResult ret;
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HFFeatureHubConfiguration configuration = {0};
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auto dbPath = GET_SAVE_DATA(".test");
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HString dbPathStr = new char[dbPath.size() + 1];
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std::strcpy(dbPathStr, dbPath.c_str());
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configuration.enablePersistence = 1;
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configuration.dbPath = dbPathStr;
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configuration.featureBlockNum = 20;
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configuration.searchMode = HF_SEARCH_MODE_EXHAUSTIVE;
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configuration.searchThreshold = 0.48f;
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// Delete the previous data before testing
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if (std::remove(configuration.dbPath) != 0) {
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spdlog::trace("Error deleting file");
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}
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ret = HFFeatureHubDataEnable(configuration);
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REQUIRE(ret == HSUCCEED);
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std::vector<std::vector<HFloat>> baseFeatures;
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size_t genSizeOfBase = 1000;
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HInt32 featureLength;
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HFGetFeatureLength(&featureLength);
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REQUIRE(featureLength > 0);
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for (int i = 0; i < genSizeOfBase; ++i) {
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auto feat = GenerateRandomFeature(featureLength);
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baseFeatures.push_back(feat);
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auto name = std::to_string(i);
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// Establish a security buffer
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std::vector<char> nameBuffer(name.begin(), name.end());
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nameBuffer.push_back('\0');
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// Construct face feature
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HFFaceFeature feature = {0};
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feature.size = feat.size();
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feature.data = feat.data();
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HFFaceFeatureIdentity identity = {0};
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identity.feature = &feature;
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identity.customId = i;
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identity.tag = nameBuffer.data();
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ret = HFFeatureHubInsertFeature(identity);
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REQUIRE(ret == HSUCCEED);
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}
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HInt32 totalFace;
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ret = HFFeatureHubGetFaceCount(&totalFace);
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REQUIRE(ret == HSUCCEED);
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REQUIRE(totalFace == genSizeOfBase);
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auto preDataSample = 200;
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// Generate some feature vectors that are similar to those of the existing database
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auto numberOfSimilar = preDataSample;
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auto targetIds = GenerateRandomNumbers(numberOfSimilar, 0, genSizeOfBase - 1);
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std::vector<std::vector<HFloat>> similarFeatures;
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for (int i = 0; i < numberOfSimilar; ++i) {
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auto index = targetIds[i];
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HFFaceFeatureIdentity identity = {0};
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ret = HFFeatureHubGetFaceIdentity(index, &identity);
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REQUIRE(ret == HSUCCEED);
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std::vector<HFloat> feature(identity.feature->data, identity.feature->data + identity.feature->size);
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auto simFeat = SimulateSimilarVector(feature);
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HFFaceFeature simFeature = {0};
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simFeature.data = simFeat.data();
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simFeature.size = simFeat.size();
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HFFaceFeature target = {0};
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target.data = identity.feature->data;
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target.size = identity.feature->size;
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HFloat cosine;
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ret = HFFaceComparison(target, simFeature, &cosine);
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REQUIRE(ret == HSUCCEED);
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REQUIRE(cosine > 0.80f);
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similarFeatures.push_back(feature);
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||||
|
||||
}
|
||||
REQUIRE(similarFeatures.size() == numberOfSimilar);
|
||||
|
||||
auto numberOfNotSimilar = preDataSample;
|
||||
std::vector<std::vector<HFloat>> notSimilarFeatures;
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// Generate some feature vectors that are not similar to the existing database
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for (int i = 0; i < numberOfNotSimilar; ++i) {
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||||
auto feat = GenerateRandomFeature(featureLength);
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||||
HFFaceFeature feature = {0};
|
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feature.size = feat.size();
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||||
feature.data = feat.data();
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HFFaceFeatureIdentity mostSim = {0};
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HFloat cosine;
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HFFeatureHubFaceSearch(feature, &cosine, &mostSim);
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REQUIRE(cosine < 0.3f);
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notSimilarFeatures.push_back(feat);
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}
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REQUIRE(notSimilarFeatures.size() == numberOfNotSimilar);
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||||
// Multithreaded search simulation
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const int numThreads = 5;
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std::vector<std::thread> threads;
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||||
std::mutex mutex;
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||||
|
||||
// Start threads for concurrent searching
|
||||
for (int t = 0; t < numThreads; ++t) {
|
||||
threads.emplace_back([&]() {
|
||||
std::random_device rd;
|
||||
std::mt19937 gen(rd());
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||||
std::uniform_int_distribution<> dis(0, preDataSample - 1);
|
||||
for (int j = 0; j < 50; ++j) { // Each thread performs 50 similar searches
|
||||
int idx = dis(gen);
|
||||
auto targetId = targetIds[idx];
|
||||
HFFaceFeature feature = {0};
|
||||
feature.data = similarFeatures[idx].data();
|
||||
feature.size = similarFeatures[idx].size();
|
||||
HFloat score;
|
||||
HFFaceFeatureIdentity identity = {0};
|
||||
HFFeatureHubFaceSearch(feature, &score, &identity);
|
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CHECK(identity.customId == targetId);
|
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}
|
||||
for (int j = 0; j < 50; ++j) {
|
||||
int idx = dis(gen);
|
||||
HFFaceFeature feature = {0};
|
||||
feature.data = notSimilarFeatures[idx].data();
|
||||
feature.size = notSimilarFeatures[idx].size();
|
||||
HFloat score;
|
||||
HFFaceFeatureIdentity identity = {0};
|
||||
HFFeatureHubFaceSearch(feature, &score, &identity);
|
||||
CHECK(identity.customId == -1);
|
||||
}
|
||||
});
|
||||
}
|
||||
for (auto &thread : threads) {
|
||||
thread.join();
|
||||
}
|
||||
|
||||
ret = HFFeatureHubDataDisable();
|
||||
REQUIRE(ret == HSUCCEED);
|
||||
|
||||
|
||||
delete []dbPathStr;
|
||||
}
|
||||
|
||||
|
||||
TEST_CASE("test_FeatureCache", "[FeatureHub][Concurrency]") {
|
||||
DRAW_SPLIT_LINE
|
||||
TEST_PRINT_OUTPUT(true);
|
||||
|
||||
HResult ret;
|
||||
HFFeatureHubConfiguration configuration = {0};
|
||||
auto dbPath = GET_SAVE_DATA(".test");
|
||||
HString dbPathStr = new char[dbPath.size() + 1];
|
||||
std::strcpy(dbPathStr, dbPath.c_str());
|
||||
configuration.enablePersistence = 1;
|
||||
configuration.dbPath = dbPathStr;
|
||||
configuration.featureBlockNum = 20;
|
||||
configuration.searchMode = HF_SEARCH_MODE_EXHAUSTIVE;
|
||||
configuration.searchThreshold = 0.48f;
|
||||
// Delete the previous data before testing
|
||||
if (std::remove(configuration.dbPath) != 0) {
|
||||
spdlog::trace("Error deleting file");
|
||||
}
|
||||
ret = HFFeatureHubDataEnable(configuration);
|
||||
REQUIRE(ret == HSUCCEED);
|
||||
|
||||
auto randomVec = GenerateRandomFeature(512);
|
||||
HFFaceFeature feature = {0};
|
||||
feature.data = randomVec.data();
|
||||
feature.size = randomVec.size();
|
||||
HFFaceFeatureIdentity identity = {0};
|
||||
identity.feature = &feature;
|
||||
identity.tag = "FK";
|
||||
identity.customId = 12;
|
||||
|
||||
ret = HFFeatureHubInsertFeature(identity);
|
||||
REQUIRE(ret == HSUCCEED);
|
||||
|
||||
auto simVec = SimulateSimilarVector(randomVec);
|
||||
HFFaceFeature simFeature = {0};
|
||||
simFeature.data = simVec.data();
|
||||
simFeature.size = simVec.size();
|
||||
|
||||
|
||||
for (int i = 0; i < 10; ++i) {
|
||||
HFFaceFeatureIdentity capture = {0};
|
||||
ret = HFFeatureHubGetFaceIdentity(12, &capture);
|
||||
REQUIRE(ret == HSUCCEED);
|
||||
|
||||
HFFaceFeature target = {0};
|
||||
target.data = capture.feature->data;
|
||||
target.size = capture.feature->size;
|
||||
|
||||
HFloat cosine;
|
||||
ret = HFFaceComparison(target, simFeature, &cosine);
|
||||
REQUIRE(cosine > 0.8f);
|
||||
REQUIRE(ret == HSUCCEED);
|
||||
|
||||
}
|
||||
|
||||
ret = HFFeatureHubDataDisable();
|
||||
REQUIRE(ret == HSUCCEED);
|
||||
|
||||
delete []dbPathStr;
|
||||
|
||||
}
|
||||
Reference in New Issue
Block a user