Fix issue that generate two or more objects with the same LP numbers/user name in the same image frame
This commit is contained in:
@@ -8,7 +8,8 @@
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"Bash(grep -n \"g_processExiting\" /c/Projects/CLionProjects/ANSCORE/engines/TensorRTAPI/include/engine/*.h /c/Projects/CLionProjects/ANSCORE/modules/ANSODEngine/engine.h)",
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"Bash(ssh -T git@anscenter.ddns.net -p 2222)",
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"Bash(ssh-add -l)",
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"Bash(dotnet build:*)"
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"Bash(dotnet build:*)",
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"Bash(grep -n \"struct Object\\\\|class Object\" /c/Projects/CLionProjects/ANSCORE/modules/ANSLPR/*.h /c/Projects/CLionProjects/ANSCORE/modules/ANSLPR/include/*.h)"
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]
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}
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}
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@@ -2163,7 +2163,9 @@ namespace ANSCENTER {
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END_TIMER(postprocess, "Update Face Attributes Time");
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// Deduplicate: if two faces matched the same userId, keep only the highest confidence
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ensureUniqueUserIdWithHighestConfidence(resultObjects);
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// Pass camera data for trackId-based identity persistence to prevent flickering
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CameraData* camDataPtr = (!camera_id.empty()) ? &GetCameraData(camera_id) : nullptr;
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ensureUniqueUserIdWithHighestConfidence(resultObjects, camDataPtr);
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}
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}
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catch (const std::exception& e) {
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@@ -2500,49 +2502,132 @@ namespace ANSCENTER {
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cv::cvtColor(input, frame, cv::COLOR_GRAY2BGR);
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return frame;
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}
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void ANSFacialRecognition::ensureUniqueUserIdWithHighestConfidence(std::vector<FaceResultObject>& resultObjects)
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void ANSFacialRecognition::ensureUniqueUserIdWithHighestConfidence(std::vector<FaceResultObject>& resultObjects, CameraData* camData)
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{
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// NO LOCK NEEDED - Operating on thread-local resultObjects
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// Each camera has its own vector, no shared state
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if (resultObjects.empty()) {
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return;
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}
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// Map userId to index of face with highest confidence
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auto isUnknownId = [](const std::string& id) {
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return id == "0000" || id == "0" || id.empty();
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};
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if (camData) {
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auto& identities = camData->trackIdentities;
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// Step 1: Build map of userId → candidate face indices (before modifying anything)
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std::unordered_map<std::string, std::vector<size_t>> userIdCandidates;
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for (size_t i = 0; i < resultObjects.size(); ++i) {
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if (isUnknownId(resultObjects[i].userId)) continue;
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userIdCandidates[resultObjects[i].userId].push_back(i);
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}
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// Step 2: Resolve duplicate userIds using accumulated scores
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for (auto& [uid, indices] : userIdCandidates) {
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if (indices.size() <= 1) continue;
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// Find the candidate with the highest accumulated score for this userId
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size_t winner = indices[0];
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float bestScore = 0.0f;
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for (size_t idx : indices) {
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int tid = resultObjects[idx].trackId;
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float score = resultObjects[idx].confidence; // fallback for new trackIds
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auto it = identities.find(tid);
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if (it != identities.end() && it->second.userId == uid) {
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// Use accumulated score + this frame's confidence
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score = it->second.accumulatedScore + resultObjects[idx].confidence;
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}
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if (score > bestScore) {
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bestScore = score;
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winner = idx;
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}
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}
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// Mark all non-winners as unknown
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for (size_t idx : indices) {
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if (idx != winner) {
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MarkAsUnknown(resultObjects[idx]);
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}
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}
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}
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// Step 3: Update accumulated scores after dedup.
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// - Winners: add this frame's confidence to their score
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// - Losers (marked Unknown by dedup): decay their score (×0.8)
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// so they gradually lose claim but don't reset instantly
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// (avoids the alternating-win problem where neither can accumulate)
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// - Losers that decay below a threshold are erased entirely
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constexpr float DECAY_FACTOR = 0.8f;
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constexpr float MIN_SCORE = 0.1f;
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for (auto& r : resultObjects) {
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int tid = r.trackId;
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if (isUnknownId(r.userId)) {
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// Lost dedup or genuinely unknown — decay existing score
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auto it = identities.find(tid);
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if (it != identities.end()) {
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it->second.accumulatedScore *= DECAY_FACTOR;
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if (it->second.accumulatedScore < MIN_SCORE) {
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identities.erase(it);
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}
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}
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continue;
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}
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auto it = identities.find(tid);
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if (it != identities.end()) {
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if (it->second.userId == r.userId) {
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// Same identity as before and won dedup — accumulate
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it->second.accumulatedScore += r.confidence;
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} else {
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// Different identity — start fresh
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it->second.userId = r.userId;
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it->second.accumulatedScore = r.confidence;
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}
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} else {
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// New trackId — initialize
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identities[tid] = { r.userId, r.confidence };
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}
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}
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// Step 3: Clean up trackIds no longer in the scene
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std::unordered_set<int> activeTrackIds;
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for (const auto& r : resultObjects) {
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activeTrackIds.insert(r.trackId);
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}
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for (auto it = identities.begin(); it != identities.end(); ) {
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if (activeTrackIds.find(it->first) == activeTrackIds.end()) {
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it = identities.erase(it);
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} else {
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++it;
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}
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}
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} else {
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// No camera data: fall back to simple confidence-based dedup
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std::unordered_map<std::string, size_t> highestConfidenceIndices;
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highestConfidenceIndices.reserve(resultObjects.size());
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for (size_t i = 0; i < resultObjects.size(); ++i) {
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const std::string& userId = resultObjects[i].userId;
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// Skip unknown faces
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if (userId == "0000") {
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continue;
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}
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if (isUnknownId(userId)) continue;
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auto it = highestConfidenceIndices.find(userId);
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if (it == highestConfidenceIndices.end()) {
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// First occurrence of this userId
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highestConfidenceIndices[userId] = i;
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}
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else {
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// Duplicate userId found - keep only highest confidence
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} else {
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size_t existingIndex = it->second;
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if (resultObjects[i].confidence > resultObjects[existingIndex].confidence) {
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// Current face has higher confidence - mark previous as unknown
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MarkAsUnknown(resultObjects[existingIndex]);
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highestConfidenceIndices[userId] = i;
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}
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else {
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// Existing face has higher confidence - mark current as unknown
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} else {
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MarkAsUnknown(resultObjects[i]);
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}
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}
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}
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}
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}
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std::vector<Object> ANSFacialRecognition::CheckFaces(const std::vector<Object>& faceObjects,bool checkFaceSize)
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{
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@@ -123,6 +123,7 @@ namespace ANSCENTER
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void Destroy();
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void SetMaxSlotsPerGpu(int n) { m_maxSlotsPerGpu = n; }
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private:
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struct CameraData; // Forward declaration for ensureUniqueUserIdWithHighestConfidence
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int m_maxSlotsPerGpu{ 1 }; // set by dllmain based on GPU topology
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int GetUser(int userId, UserRecord& userRecord);
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int GetUser(int userId, const std::string& userCode,const std::string& userName, UserRecord& userRecord);
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@@ -140,7 +141,7 @@ namespace ANSCENTER
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bool InitializeAgeGenderModel(const std::string& deviceName);
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bool InitializeEmotionModel(const std::string& deviceName);
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bool InitializeHeadPoseModel(const std::string& deviceName);
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void ensureUniqueUserIdWithHighestConfidence(std::vector<FaceResultObject>& resultObjects);
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void ensureUniqueUserIdWithHighestConfidence(std::vector<FaceResultObject>& resultObjects, CameraData* camData = nullptr);
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Object GetLargestObject(const std::vector<Object>& objects);
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bool AreFacesSimilar(const FaceResultObject& face1, const FaceResultObject& face2);
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size_t GenerateFaceHash(const FaceResultObject& face, const std::vector<FaceResultObject>& detectedObjects);
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@@ -232,6 +233,16 @@ namespace ANSCENTER
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int attributeFrameCounter = 0; // counts frames for attribute skip logic
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std::unordered_map<int, CachedFaceAttributes> cachedAttributes; // trackId → cached attrs
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// Identity persistence: accumulated confidence per (trackId, userId) pair.
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// Each frame adds the recognition confidence to the running total.
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// When two trackIds claim the same userId, the one with the higher
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// accumulated score wins — preventing single-frame flickering.
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struct TrackIdentity {
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std::string userId;
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float accumulatedScore = 0.0f;
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};
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std::unordered_map<int, TrackIdentity> trackIdentities; // trackId → accumulated identity
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// Adaptive interval state
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int currentAttributeInterval = 5; // current adaptive interval
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int stableFrameCount = 0; // frames with no new/lost trackIds
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@@ -246,6 +257,7 @@ namespace ANSCENTER
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_detectionQueue.clear();
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attributeFrameCounter = 0;
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cachedAttributes.clear();
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trackIdentities.clear();
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currentAttributeInterval = 5;
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stableFrameCount = 0;
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previousTrackIdCount = 0;
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@@ -990,6 +990,10 @@ namespace ANSCENTER {
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cv::waitKey(1);
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#endif
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// Deduplicate: if two trackIds claim the same plate text, keep the one
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// with the higher accumulated score to prevent plate flickering
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ensureUniquePlateText(output, cameraId);
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return output;
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}
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@@ -2313,6 +2317,10 @@ namespace ANSCENTER {
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output.push_back(std::move(lprObject));
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}
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// Deduplicate: if two trackIds claim the same plate text, keep the one
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// with the higher accumulated score to prevent plate flickering
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ensureUniquePlateText(output, cameraId);
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return output;
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}
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catch (const cv::Exception& e) {
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@@ -2701,4 +2709,102 @@ namespace ANSCENTER {
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return AnalyseLicensePlateText(ocrText);
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}
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}
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void ANSALPR_OD::ensureUniquePlateText(std::vector<Object>& results, const std::string& cameraId)
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{
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if (results.empty()) return;
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auto isEmptyPlate = [](const std::string& plate) {
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return plate.empty();
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};
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auto& identities = _plateIdentities[cameraId];
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// Step 1: Build map of plateText → candidate indices
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std::unordered_map<std::string, std::vector<size_t>> plateCandidates;
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for (size_t i = 0; i < results.size(); ++i) {
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if (isEmptyPlate(results[i].className)) continue;
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plateCandidates[results[i].className].push_back(i);
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}
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// Step 2: Resolve duplicates using accumulated scores
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for (auto& [plateText, indices] : plateCandidates) {
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if (indices.size() <= 1) continue;
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// Find the candidate with the highest accumulated score
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size_t winner = indices[0];
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float bestScore = 0.0f;
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for (size_t idx : indices) {
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int tid = results[idx].trackId;
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float score = results[idx].confidence; // fallback for new trackIds
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auto it = identities.find(tid);
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if (it != identities.end() && it->second.plateText == plateText) {
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score = it->second.accumulatedScore + results[idx].confidence;
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}
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if (score > bestScore) {
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bestScore = score;
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winner = idx;
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}
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}
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// Clear plate text from non-winners
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for (size_t idx : indices) {
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if (idx != winner) {
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results[idx].className.clear();
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}
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}
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}
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// Step 3: Update accumulated scores — winners accumulate, losers decay
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constexpr float DECAY_FACTOR = 0.8f;
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constexpr float MIN_SCORE = 0.1f;
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for (auto& r : results) {
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int tid = r.trackId;
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if (isEmptyPlate(r.className)) {
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// Lost dedup or empty — decay
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auto it = identities.find(tid);
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if (it != identities.end()) {
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it->second.accumulatedScore *= DECAY_FACTOR;
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if (it->second.accumulatedScore < MIN_SCORE) {
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identities.erase(it);
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}
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}
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continue;
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}
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auto it = identities.find(tid);
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if (it != identities.end()) {
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if (it->second.plateText == r.className) {
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it->second.accumulatedScore += r.confidence;
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} else {
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it->second.plateText = r.className;
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it->second.accumulatedScore = r.confidence;
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}
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} else {
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identities[tid] = { r.className, r.confidence };
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}
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}
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// Step 4: Clean up trackIds no longer in the scene
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std::unordered_set<int> activeTrackIds;
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for (const auto& r : results) {
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activeTrackIds.insert(r.trackId);
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}
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for (auto it = identities.begin(); it != identities.end(); ) {
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if (activeTrackIds.find(it->first) == activeTrackIds.end()) {
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it = identities.erase(it);
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} else {
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++it;
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}
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}
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// Step 5: Remove entries with cleared plate text from results
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results.erase(
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std::remove_if(results.begin(), results.end(),
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[](const Object& o) { return o.className.empty(); }),
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results.end());
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}
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};
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@@ -7,6 +7,7 @@
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#include <map>
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#include <string>
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#include <unordered_map>
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#include <unordered_set>
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#include <utility>
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#include <vector>
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@@ -134,6 +135,16 @@ namespace ANSCENTER
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"59S2", "94D1", "59H1", "29B1", "59L1", "50X1", "72L1",
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"43B1", "68L1", "70G1", "36M1", "81N1", "90K1", "17B1", "64E1", "99D1", "60B2", "74L1", "60C1", "68M1", "63B7", "34B1", "69M1", "24B1", "15M1", "83Y1", "48C1", "95H1", "79X1", "17B6", "36E1", "38K1", "25N1", "25U1", "61B1", "36C1", "36B3", "38F1", "99G1", "69N1", "97D1", "92T1", "92B1", "88B1", "97G1", "14U1", "63A1", "26N1", "19D1", "93C1", "73B1", "84B1", "81K1", "18L1", "64D1", "35M1", "61N1", "83P1", "15S1", "82B1", "92U1", "43D1", "22L1", "63B5", "64G1", "27N1", "14X1", "62C1", "81D1", "38G1", "19F1", "34K1", "49P1", "89H1", "14T1", "19M1", "78D1", "76A1", "66K1", "66C1", "71C1", "37K1", "19G1", "15F1", "85C1", "49B1", "21B1", "89F1", "23M1", "66L1", "90B5", "93M1", "14P1", "77N1", "36B8", "86B1", "12U1", "63B3", "21L1", "36G5", "65G1", "82E1", "61H1", "65H1", "84A1", "23F1", "95C1", "99K1", "49G1", "92D1", "36K3", "92N1", "82X1", "83M1", "11N1", "14K1", "19H1", "93H1", "60A1", "79A1", "20D1", "90D1", "81C1", "66P1", "36K1", "92V1", "18B1", "37P1", "22Y1", "23H1", "26D1", "66G1", "78F1", "49C1", "26H1", "38P1", "47T1", "74H1", "63P1", "47D1", "15D1", "23D1", "68E1", "20B1", "49F1", "43K1", "65K1", "27Z1", "92S1", "79H1", "21E1", "35Y1", "14S1", "75E1", "24Y1", "12T1", "27P1", "77B1", "88H1", "60B3", "23P1", "61F1", "99H1", "23K1", "59A3", "26C1", "81B1", "74E1", "66B1", "22S1", "92P1", "93B1", "69B1", "81P1", "12H1", "62K1", "35A1", "77C1", "27V1", "68N1", "12D1", "64K1", "41A1", "12Z1", "76C1", "38B1", "78G1", "74K1", "69H1", "94A1", "61K1", "86B7", "82G1", "14N1", "82M1", "76E1", "18E1", "61C1", "15N1", "90A1", "77F1", "34D1", "47B1", "62S1", "43E1", "81M1", "92X1", "75B1", "34F1", "70H1", "62B1", "26B1", "60B4", "61A1", "12B1", "90T1", "92E1", "34C1", "47G1", "97B1", "25S1", "70E1", "93Y1", "47S1", "37F1", "28N1", "11K1", "38E1", "78M1", "74C1", "12S1", "75S1", "37A1", "28D1", "65L1", "22B1", "99B1", "74G1", "79K1", "76K1", "76H1", "23B1", "15R1", "36B1", "74D1", "62L1", "37E1", "78E1", "89K1", "26M1", "25F1", "48H1", "79D1", "43H1", "76F1", "36L1", "43L1", "21K1", "88L1", "27S1", "92K1", "77D1", "19N1", "66H1", "36H5", "62N1", "18G1", "75D1", "37L1", "68K1", "28C1", "26E1", "35N1", "85H1", "62D1", "27U1", "19E1", "99E1", "14Y1", "49L1", "66M1", "73F1", "70K1", "36F5", "97H1", "93E1", "68P1", "43F1", "48G1", "75K1", "62U1", "86B9", "65F1", "27L1", "70L1", "63B8", "78L1", "11Z1", "68C1", "18D1", "15L1", "99C1", "49E1", "84E1", "69E1", "38A1", "48D1", "68S1", "81E1", "84K1", "63B6", "24T1", "95A1", "86B4", "34M1", "84L1", "24V1", "14M1", "36H1", "15B1", "69F1", "47E1", "38H1", "88D1", "28E1", "60C2", "63B9", "75Y1", "21D1", "35H1", "68F1", "86B5", "15H1", "36B5", "83X1", "17B7", "12V1", "86B8", "95E1", "63B2", "74F1", "86C1", "48K1", "89M1", "85D1", "71C4", "34E1", "97C1", "88E1", "81F1", "60B5", "84M1", "92H1", "28L1", "34H1", "38X1", "82L1", "61E1", "82F1", "62P1", "93F1", "65B1", "93L1", "95B1", "15P1", "77G1", "28M1", "35B1", "68G1", "36C2", "68D1", "69K1", "14L1", "36M3", "24X1", "24Z1", "86A1", "88C1", "15E1", "77E1", "83E1", "47L1", "25T1", "89C1", "71C3", "49D1", "36L6", "48F1", "36B6", "34P1", "84D1", "15C1", "38M1", "85F1", "77K1", "86B3", "74B1", "78H1", "89G1", "64A2", "15K1", "85B1", "49K1", "21H1", "73C1", "47U1", "65E1", "18C1", "69D1", "63B1", "95G1", "19L1", "20G1", "76D1", "29A1", "68T1", "75L1", "12L1", "89L1", "37C1", "27B1", "19C1", "11H1", "81X1", "70B1", "11V1", "43G1", "22A1", "83C1", "75C1", "79C1", "22F1", "92F1", "81G1", "81T1", "28H1", "66N1", "71B1", "18H1", "76P1", "26F1", "81U1", "34N1", "64F1", "76N1", "24S1", "26P1", "63B4", "35T1", "36N1", "47F1", "81L1", "61G1", "77M1", "34G1", "26G1", "97F1", "62H1", "28F1", "62T1", "93G1", "73D1", "65A1", "47P1", "74P1", "82N1", "20E1", "36D1", "60B1", "49M1", "37H1", "37M1", "38D1", "84F1", "88F1", "36B2", "65C1", "92M1", "86B6", "75H1", "38L1", "20C1", "97E1", "85E1", "38N1", "26K1", "89B1", "99F1", "28B1", "34L1", "86B2", "66F1", "77L1", "27Y1", "68H1", "37D1", "92L1", "82K1", "99A1", "69L1", "76M1", "90B4", "48B1", "95D1", "20H1", "64H1", "79Z1", "92G1", "23G1", "21G1", "37G1", "35K1", "81H1", "83Z1", "76T1", "36F1", "36B4", "14B9", "47K1", "20K1", "62M1", "84H1", "62F1", "74A1", "18A1", "73H1", "37N1", "79N1", "61D1", "11P1", "15G1", "47N1", "19K1", "71C2", "81S1", "11M1", "60B7", "60B8", "62G1", "71A1", "24P1", "69A1", "38C1", "49N1", "21C1", "84G1", "37B1", "72A1", "88K1", "88G1", "83V1", "78C1", "73K1", "78K1", "73E189D1", "67A1", "27X1", "62A1", "18K1", "70F1", "36K5", "19B1", "49H1", "66S1", "12P1" };
|
||||
ALPRChecker alprChecker;
|
||||
|
||||
// Plate identity persistence: accumulated confidence per (trackId, plateText) pair.
|
||||
// Prevents the same plate string from flickering between different vehicles.
|
||||
struct PlateTrackIdentity {
|
||||
std::string plateText;
|
||||
float accumulatedScore = 0.0f;
|
||||
};
|
||||
// cameraId → { trackId → PlateTrackIdentity }
|
||||
std::unordered_map<std::string, std::unordered_map<int, PlateTrackIdentity>> _plateIdentities;
|
||||
void ensureUniquePlateText(std::vector<Object>& results, const std::string& cameraId);
|
||||
std::vector<std::string> ValidVNCarList = { "94H", "49F", "93A", "20F", "81H", "95R", "38R", "29F", "81F", "28G", "19A", "85B", "2", "43H", "51L", "28C", "21A", "51D", "50F", "24H", "93R", "92H", "71G", "75H", "86G", "30L", "79A", "82B", "79H", "78C", "61E", "70A", "90C", "72G", "34B", "17E", "18E", "78A", "37F", "51E", "71A", "28F", "47E", "83D", "81B", "84C", "71H", "76G", "92E", "36A", "69R", "30M", "27R", "71D", "19B", "34E", "38K", "88G", "68G", "30E", "68E", "25F", "74D", "98K", "89H", "36R", "84D", "61F", "49G", "25H", "17F", "14R", "36H", "47G", "90A", "68A", "83C", "26B", "15B", "61C", "15K", "47H", "78E", "75D", "15C", "63E", "34C", "36F", "38G", "15E", "93F", "22G", "60B", "94D", "62R", "24D", "11R", "12A", "76A", "94C", "97R", "24E", "26A", "15F", "72A", "49H", "62D", "98C", "71B", "61A", "12C", "27A", "78R", "51M", "69E", "76D", "78F", "49R", "81A", "64F", "29D", "18A", "19F", "21E", "92A", "65G", "86E", "62G", "61K", "47A", "23R", "14F", "95D", "36B", "74R", "11H", "24C", "11G", "66D", "63A", "43R", "70F", "86B", "61G", "47M", "67C", "37D", "43G", "14H", "90F", "51G", "86A", "11E", "29K", "85C", "83F", "24B", "98R", "19E", "61B", "90D", "82G", "14K", "74G", "72D", "85A", "19C", "37G", "98E", "74F", "28H", "90E", "89D", "35R", "97H", "83H", "95A", "20C", "65E", "15R", "73C", "37A", "38E", "77G", "94B", "17A", "75R", "98F", "65R", "76R", "20B", "24G", "25B", "73G", "62F", "29G", "77C", "22H", "14D", "23F", "93C", "19R", "15D", "47R", "79D", "60G", "77A", "82C", "63G", "21H", "81E", "25D", "12D", "37R", "36K", "84F", "98G", "28B", "51N", "18F", "50R", "74C", "35C", "30G", "64A", "95F", "18C", "99G", "99B", "37C", "76H", "60K", "67R", "75A", "83R", "28E", "65F", "17D", "92G", "23C", "60R", "90R", "38A", "43D", "50H", "43C", "77H", "47B", "89F", "82F", "65H", "89E", "62C", "24R", "26G", "84E", "17C", "65B", "34A", "12B", "64R", "29H", "71C", "88D", "79F", "76C", "98A", "69H", "22B", "29A", "72R", "67H", "48C", "22D", "60C", "35H", "38H", "63P", "70D", "49D", "18H", "89A", "72E", "92D", "26H", "73R", "85G", "20E", "98H", "69C", "18B", "73B", "22E", "34G", "30K", "20D", "50A", "34D", "15H", "34H", "71E", "62E", "64C", "51R", "82D", "99E", "70R", "18D", "92F", "94R", "24A", "85H", "11C", "73E", "95E", "86C", "94F", "86R", "37K", "23B", "20H", "73D", "95H", "35A", "89B", "82H", "67F", "70H", "97F", "29E", "97A", "51K", "68D", "37B", "82E", "18R", "86H", "35B", "43E", "35F", "95B", "70E", "21D", "27F", "36E", "63D", "68C", "50E", "36G", "75F", "21G", "29B", "93B", "22A", "18G", "43F", "93G", "62A", "83B", "28D", "75C", "22C", "21R", "25E", "23G", "97C", "75E", "79E", "19H", "47K", "65C", "35E", "20R", "68B", "89R", "67A", "75G", "81R", "78B", "77D", "78G", "20K", "36D", "66C", "38F", "27G", "19D", "67B", "84G", "22F", "61D", "20G", "48A", "76F", "48H", "92B", "85R", "26C", "65A", "70B", "38D", "14C", "66A", "73A", "49C", "74E", "68R", "66B", "74A", "49E", "17B", "69D", "51C", "85F", "21F", "99C", "17G", "72H", "94E", "51F", "92R", "60H", "21B", "93D", "19G", "86F", "51A", "66R", "72B", "26D", "64E", "93H", "12H", "97E", "60E", "82A", "60A", "83E", "27D", "64B", "11B", "11D", "76B", "95G", "14A", "61R", "21C", "30F", "23H", "89C", "97G", "62B", "63R", "88B", "98B", "90B", "67G", "69F", "73H", "20A", "72C", "65D", "68H", "51H", "79G", "70C", "90G", "66G", "83A", "77F", "63B", "64G", "25A", "88E", "68F", "99D", "26E", "94A", "48F", "34R", "61H", "90H", "74B", "14G", "12F", "15A", "27E", "69A", "35D", "12E", "85E", "25C", "29M", "89G", "17R", "78D", "84R", "95C", "15G", "28R", "99A", "69G", "48D", "97D", "27C", "78H", "14E", "79R", "73F", "88A", "48E", "48B", "64H", "99R", "14B", "77R", "75B", "88F", "84B", "11A", "67E", "12R", "50M", "11F", "79C", "49A", "43A", "88R", "77E", "48G", "51B", "81D", "74H", "93E", "37H", "88C", "71F", "94G", "38C", "29C", "43B", "30H", "81G", "28A", "26R", "66H", "66E", "17H", "79B", "49B", "63C", "98D", "81C", "69B", "63H", "85D", "26F", "22R", "83G", "37E", "12G", "77B", "35G", "62H", "60D", "60F", "99H", "70G", "76E", "84A", "72F", "25R", "27B", "30A", "47F", "34F", "97B", "23E", "36C", "66F", "48R", "92C", "71R", "23A", "50G", "47C", "82R", "63F", "84H", "38B", "47D", "67D", "25G", "86D", "88H", "64D", "24F", "23D", "99F" };
|
||||
[[nodiscard]] std::string AnalyseLicensePlateText(const std::string& ocrText);
|
||||
[[nodiscard]] char convertDigitToLetter(char c);
|
||||
|
||||
@@ -730,8 +730,8 @@ int ANSVISTest() {
|
||||
|
||||
//std::string videoFilePath = "E:\\Programs\\DemoAssets\\Videos\\ANSVIS_Issues\\face.mp4";
|
||||
//std::string videoFilePath = "E:\\Programs\\DemoAssets\\Videos\\TestFR\\Face31.mp4";
|
||||
//std::string videoFilePath = "E:\\Programs\\DemoAssets\\Videos\\classroom.mp4";
|
||||
std::string videoFilePath = "E:\\Programs\\DemoAssets\\Videos\\TestFR\\school1.mp4";// "C:\\ProgramData\\ANSCENTER\\Shared\\classroom.mp4";
|
||||
std::string videoFilePath = "E:\\Programs\\DemoAssets\\Videos\\classroom.mp4";
|
||||
//std::string videoFilePath = "E:\\Programs\\DemoAssets\\Videos\\TestFR\\school1.mp4";// "C:\\ProgramData\\ANSCENTER\\Shared\\classroom.mp4";
|
||||
|
||||
const char* configFilePath = "";
|
||||
ANSCENTER::ANSFacialRecognition* infHandle;
|
||||
|
||||
@@ -2770,9 +2770,9 @@ int main()
|
||||
//for (int i = 0; i < 100; i++) {
|
||||
// ANSLPR_CPU_Inferences_FileTest();
|
||||
//}
|
||||
ANSLPR_MultiGPU_StressTest();
|
||||
//ANSLPR_MultiGPU_StressTest();
|
||||
//ANSLPR_MultiGPU_StressTest_SimulatedCam();
|
||||
//ANSLPR_MultiGPU_StressTest_FilePlayer();
|
||||
ANSLPR_MultiGPU_StressTest_FilePlayer();
|
||||
return 0;
|
||||
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user