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Fix AMD and OpenVINO

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This commit is contained in:
Tuan Nghia Nguyen
2026-04-08 13:45:52 +10:00
parent a4a8caaa86
commit 69787b0ff0
15 changed files with 1209 additions and 132 deletions
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696
tests/ANSLPR-UnitTest/ANSLPR-UnitTest.cpp
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@@ -29,6 +29,7 @@
#include <set>
#include <map>
#include <cuda_runtime.h>
#include "EPLoader.h"
template<typename T>
T GetOptionalValue(const boost::property_tree::ptree& pt, std::string attribute, T defaultValue) {
@@ -664,9 +665,21 @@ struct GpuSnapshot {
size_t usedMiB = 0;
};
// Safe check: is CUDA runtime available? (prevents crash on CPU-only PCs)
static bool IsCudaAvailable() {
static int cached = -1;
if (cached < 0) {
HMODULE h = LoadLibraryA("nvcuda.dll");
cached = (h != nullptr) ? 1 : 0;
if (h) FreeLibrary(h);
}
return cached == 1;
}
// Query current GPU VRAM usage for all devices
static std::vector<GpuSnapshot> QueryGpuVram() {
std::vector<GpuSnapshot> snapshots;
if (!IsCudaAvailable()) return snapshots;
int deviceCount = 0;
if (cudaGetDeviceCount(&deviceCount) != cudaSuccess) return snapshots;
for (int i = 0; i < deviceCount; i++) {
@@ -693,6 +706,7 @@ static std::vector<GpuSnapshot> QueryGpuVram() {
// Measure per-GPU free VRAM (returns array indexed by device)
static std::vector<size_t> GetPerGpuFreeMiB() {
std::vector<size_t> result;
if (!IsCudaAvailable()) return result;
int deviceCount = 0;
if (cudaGetDeviceCount(&deviceCount) != cudaSuccess) return result;
int prevDevice;
@@ -712,6 +726,11 @@ static ThreadSafeLog g_log;
// Log GPU info using CUDA runtime
static void LogGpuInfo() {
if (!IsCudaAvailable()) {
g_log.add("No NVIDIA GPU detected — running in CPU mode");
printf("[GPU] No NVIDIA GPU detected — running in CPU mode\n");
return;
}
int deviceCount = 0;
cudaError_t err = cudaGetDeviceCount(&deviceCount);
if (err != cudaSuccess) {
@@ -749,6 +768,12 @@ static void LogGpuInfo() {
printf("============================================================\n");
}
// Global inference mutex: serializes inference on non-NVIDIA GPUs (DirectML/OpenVINO).
// DirectML is not thread-safe when multiple ORT sessions run concurrently on the
// same integrated GPU — causes access violations on 4K frames.
// On NVIDIA, each task has its own CUDA context so no serialization needed.
static std::mutex g_inferenceMutex;
// Worker thread: reads RTSP frames and runs ALPR inference
// RTSP client and ALPR engine are pre-created on the main thread to avoid
// race conditions in CreateANSRTSPHandle / CreateANSALPRHandle.
@@ -845,12 +870,18 @@ static void ALPRWorkerThread(int taskId,
if (grabMs > maxGrabMs) maxGrabMs = grabMs;
// Run ALPR inference
bool isNvidia = (ANSCENTER::EPLoader::Current().type == ANSCENTER::EngineType::NVIDIA_GPU);
fprintf(stderr, "[Worker T%d] frame %d: calling inference %dx%d...\n",
taskId, state.frameCount + 1, framePtr->cols, framePtr->rows);
auto infStart = std::chrono::steady_clock::now();
std::string lpnResult, jpegImage;
// Pass framePtr directly — NOT a copy. ANSGpuFrameRegistry::lookup()
// matches by cv::Mat* pointer, so `new cv::Mat(*framePtr)` would create
// a different pointer the registry doesn't know, breaking NV12 zero-copy.
ANSALPR_RunInferenceComplete_CPP(&alprHandle, &framePtr, cameraId.c_str(), 0, 0, lpnResult, jpegImage);
{
std::unique_lock<std::mutex> infLock(g_inferenceMutex, std::defer_lock);
if (!isNvidia) infLock.lock();
ANSALPR_RunInferenceComplete_CPP(&alprHandle, &framePtr, cameraId.c_str(), 0, 0, lpnResult, jpegImage);
}
fprintf(stderr, "[Worker T%d] frame %d: inference done, result len=%zu\n",
taskId, state.frameCount + 1, lpnResult.size());
// Release stream lock — inference is done, CHAOS can now safely destroy.
streamLock.unlock();
@@ -950,25 +981,454 @@ static void ALPRWorkerThread(int taskId,
g_log.add(prefix + " Worker loop exited");
}
// =============================================================================
// ANSLPR_SingleTask_Test — 1 stream, 1 AI task. For isolating DirectML/ORT
// issues on non-NVIDIA GPUs. If this works but 2-task crashes, it's concurrency.
// =============================================================================
int ANSLPR_SingleTask_Test() {
ANSCENTER::ANSOPENCV::InitCameraNetwork();
g_log.init();
printf("\n");
printf("============================================================\n");
printf(" ANSLPR Single-Task Test — 1 Stream, 1 AI Task\n");
printf(" Press ESC to stop\n");
printf(" Log file: %s\n", LOG_FILE_PATH);
printf("============================================================\n\n");
g_log.add("============================================================");
g_log.add(" ANSLPR Single-Task Test — 1 Stream, 1 AI Task");
g_log.add("============================================================");
const std::string streamUrl = "rtsp://admin:admin123@103.156.0.133:8010/cam/realmonitor?channel=1&subtype=0";
g_log.add("Stream: " + streamUrl);
// --- Create RTSP client ---
ANSCENTER::ANSRTSPClient* rtspClient = nullptr;
printf("[Stream0] Creating RTSP handle...\n");
int rtspResult = CreateANSRTSPHandle(&rtspClient, "", "", "", streamUrl.c_str());
if (rtspResult != 1 || rtspClient == nullptr) {
printf("[Stream0] FAILED to create RTSP handle\n");
ANSCENTER::ANSOPENCV::DeinitCameraNetwork();
return -1;
}
SetRTSPImageQuality(&rtspClient, 0);
SetRTSPHWDecoding(&rtspClient, -1); // Force software decoding
StartRTSP(&rtspClient);
g_log.add("[Stream0] RTSP started (software decode)");
// --- Create single ALPR engine ---
ANSCENTER::ANSALPR* alprHandle = nullptr;
std::string modelZipFile = "C:\\ProgramData\\ANSCENTER\\ANSVIS Server\\ANSALPR\\ANS_ALPR_v1.2.zip";
printf("[Task0] Creating ALPR handle...\n");
auto engineStart = std::chrono::steady_clock::now();
int createResult = CreateANSALPRHandle(&alprHandle, "", modelZipFile.c_str(), "",
1, 0.5, 0.5, 0.5);
if (createResult != 1 || alprHandle == nullptr) {
printf("[Task0] FAILED to create ALPR handle (result=%d)\n", createResult);
StopRTSP(&rtspClient); ReleaseANSRTSPHandle(&rtspClient);
ANSCENTER::ANSOPENCV::DeinitCameraNetwork();
return -1;
}
printf("[Task0] Loading ALPR engine...\n");
int loadResult = LoadANSALPREngineHandle(&alprHandle);
auto engineEnd = std::chrono::steady_clock::now();
double loadMs = std::chrono::duration<double, std::milli>(engineEnd - engineStart).count();
if (loadResult != 1) {
printf("[Task0] FAILED to load ALPR engine (result=%d)\n", loadResult);
ReleaseANSALPRHandle(&alprHandle);
StopRTSP(&rtspClient); ReleaseANSRTSPHandle(&rtspClient);
ANSCENTER::ANSOPENCV::DeinitCameraNetwork();
return -1;
}
printf("[Task0] Engine loaded in %.0f ms\n", loadMs);
g_log.add("[Task0] Engine loaded in " + std::to_string((int)loadMs) + " ms");
// --- Single-task worker + display ---
TaskState state;
state.engineLoaded = true;
state.streamOk = true;
state.statusMsg = "Running";
std::mutex streamGuard;
std::thread worker(ALPRWorkerThread, 0, &rtspClient, &streamGuard, alprHandle, std::ref(state));
const int cellW = 800, cellH = 600;
const int logPanelH = 80;
std::string windowTitle = "ANSLPR Single-Task Test";
cv::namedWindow(windowTitle, cv::WINDOW_NORMAL);
cv::resizeWindow(windowTitle, cellW, cellH + logPanelH);
auto testStart = std::chrono::steady_clock::now();
while (g_running.load()) {
cv::Mat canvas(cellH + logPanelH, cellW, CV_8UC3, cv::Scalar(30, 30, 30));
cv::Mat cell;
double fps = 0, infMs = 0;
int fCount = 0, dCount = 0;
std::string lastPlate;
{
std::lock_guard<std::mutex> lk(state.mtx);
if (!state.displayFrame.empty())
cv::resize(state.displayFrame, cell, cv::Size(cellW, cellH));
fps = state.fps;
infMs = state.inferenceMs;
fCount = state.frameCount;
dCount = state.detectionCount;
lastPlate = state.lastPlate;
}
if (cell.empty())
cell = cv::Mat(cellH, cellW, CV_8UC3, cv::Scalar(40, 40, 40));
cv::rectangle(cell, cv::Rect(0, cellH - 40, cellW, 40), cv::Scalar(0, 0, 0), cv::FILLED);
char bar[256];
snprintf(bar, sizeof(bar), "T0 | %.1f FPS | %.0fms | F:%d | D:%d | %s",
fps, infMs, fCount, dCount, lastPlate.empty() ? "-" : lastPlate.c_str());
cv::putText(cell, bar, cv::Point(5, cellH - 12),
cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 255, 0), 1);
cell.copyTo(canvas(cv::Rect(0, 0, cellW, cellH)));
cv::Mat logPanel = canvas(cv::Rect(0, cellH, cellW, logPanelH));
logPanel.setTo(cv::Scalar(20, 20, 20));
auto elapsed = std::chrono::duration<double>(std::chrono::steady_clock::now() - testStart).count();
char header[256];
snprintf(header, sizeof(header), "Elapsed: %.0fs | 1 camera, 1 AI task | %.1f FPS | Press ESC to stop",
elapsed, fps);
cv::putText(logPanel, header, cv::Point(10, 20),
cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(200, 200, 0), 1);
cv::imshow(windowTitle, canvas);
if (cv::waitKey(30) == 27) {
g_log.add("ESC pressed — stopping...");
printf("\nESC pressed — stopping...\n");
g_running.store(false);
}
}
if (worker.joinable()) worker.join();
printf("\n============================================================\n");
printf(" FINAL SUMMARY\n");
printf(" Frames: %d | Detections: %d | FPS: %.1f | InfMs: %.0f\n",
state.frameCount, state.detectionCount, state.fps, state.inferenceMs);
printf("============================================================\n");
ReleaseANSALPRHandle(&alprHandle);
StopRTSP(&rtspClient);
ReleaseANSRTSPHandle(&rtspClient);
g_log.close();
cv::destroyAllWindows();
ANSCENTER::ANSOPENCV::DeinitCameraNetwork();
return 0;
}
// =============================================================================
// ANSLPR_CPU_StressTest — Lightweight 2-task stress test for CPU-only PCs
// Uses ANSALPR_OD (engineType=1) which auto-falls-back to ONNX Runtime on CPU.
// No VRAM tracking, no NVDEC alignment, no chaos thread.
// =============================================================================
int ANSLPR_CPU_StressTest() {
ANSCENTER::ANSOPENCV::InitCameraNetwork();
g_log.init();
const int NUM_STREAMS = 2;
const int NUM_TASKS = 2;
printf("\n");
printf("============================================================\n");
printf(" ANSLPR CPU Stress Test — %d Parallel ALPR Tasks\n", NUM_TASKS);
printf(" Press ESC to stop\n");
printf(" Log file: %s\n", LOG_FILE_PATH);
printf("============================================================\n\n");
g_log.add("============================================================");
g_log.add(" ANSLPR CPU Stress Test — " + std::to_string(NUM_TASKS) + " Tasks");
g_log.add("============================================================");
// --- RTSP URLs (2 camera streams) ---
const std::string streamUrls[NUM_STREAMS] = {
"rtsp://admin:admin123@103.156.0.133:8010/cam/realmonitor?channel=1&subtype=0",
"rtsp://nhathuocngoclinh.zapto.org:600/rtsp/streaming?channel=01&subtype=0"
};
const int taskStreamMap[NUM_TASKS] = { 0, 1 };
for (int i = 0; i < NUM_STREAMS; i++)
g_log.add("Stream " + std::to_string(i) + ": " + streamUrls[i]);
// --- Task states ---
TaskState taskStates[NUM_TASKS];
// --- Create RTSP clients (software decoding) ---
ANSCENTER::ANSRTSPClient* rtspClients[NUM_STREAMS] = {};
for (int s = 0; s < NUM_STREAMS; s++) {
printf("[Stream%d] Creating RTSP handle...\n", s);
int result = CreateANSRTSPHandle(&rtspClients[s], "", "", "", streamUrls[s].c_str());
if (result != 1 || rtspClients[s] == nullptr) {
printf("[Stream%d] FAILED to create RTSP handle\n", s);
g_log.add("[Stream" + std::to_string(s) + "] RTSP create FAILED");
rtspClients[s] = nullptr;
continue;
}
SetRTSPImageQuality(&rtspClients[s], 0);
SetRTSPHWDecoding(&rtspClients[s], -1); // HW_DECODING_DISABLE: force software decoding
StartRTSP(&rtspClients[s]);
g_log.add("[Stream" + std::to_string(s) + "] RTSP started (software decode)");
}
// --- Create ALPR engines (engineType=1 → ANSALPR_OD, auto CPU/GPU) ---
ANSCENTER::ANSALPR* alprHandles[NUM_TASKS] = {};
std::string modelZipFile = "C:\\ProgramData\\ANSCENTER\\ANSVIS Server\\ANSALPR\\ANS_ALPR_v1.2.zip";
int engineType = 1; // ANSALPR_OD: auto CPU/GPU
double detThresh = 0.5, ocrThresh = 0.5, colThresh = 0.5;
for (int i = 0; i < NUM_TASKS; i++) {
char tag[32];
snprintf(tag, sizeof(tag), "[Task%d]", i);
int streamIdx = taskStreamMap[i];
if (rtspClients[streamIdx] == nullptr) {
printf("%s Skipped — Stream%d not available\n", tag, streamIdx);
continue;
}
{
std::lock_guard<std::mutex> lk(taskStates[i].mtx);
taskStates[i].streamOk = true;
taskStates[i].statusMsg = "Loading ALPR engine...";
}
printf("%s Creating ALPR handle...\n", tag);
auto engineStart = std::chrono::steady_clock::now();
int createResult = CreateANSALPRHandle(&alprHandles[i], "", modelZipFile.c_str(), "",
engineType, detThresh, ocrThresh, colThresh);
if (createResult != 1 || alprHandles[i] == nullptr) {
printf("%s FAILED to create ALPR handle (result=%d)\n", tag, createResult);
g_log.add(std::string(tag) + " ALPR create FAILED");
continue;
}
printf("%s Loading ALPR engine...\n", tag);
int loadResult = LoadANSALPREngineHandle(&alprHandles[i]);
auto engineEnd = std::chrono::steady_clock::now();
double loadMs = std::chrono::duration<double, std::milli>(engineEnd - engineStart).count();
if (loadResult != 1) {
printf("%s FAILED to load ALPR engine (result=%d)\n", tag, loadResult);
g_log.add(std::string(tag) + " Engine load FAILED");
ReleaseANSALPRHandle(&alprHandles[i]);
alprHandles[i] = nullptr;
continue;
}
char buf[256];
snprintf(buf, sizeof(buf), "%s Engine loaded in %.0f ms (Stream%d)", tag, loadMs, streamIdx);
printf("%s\n", buf);
g_log.add(buf);
{
std::lock_guard<std::mutex> lk(taskStates[i].mtx);
taskStates[i].engineLoaded = true;
taskStates[i].statusMsg = "Running";
}
}
// --- Launch worker threads ---
std::mutex streamGuards[NUM_STREAMS];
std::thread workers[NUM_TASKS];
for (int i = 0; i < NUM_TASKS; i++) {
int streamIdx = taskStreamMap[i];
if (rtspClients[streamIdx] && alprHandles[i]) {
workers[i] = std::thread(ALPRWorkerThread, i,
&rtspClients[streamIdx],
&streamGuards[streamIdx],
alprHandles[i],
std::ref(taskStates[i]));
}
}
// --- Display loop ---
const int cellW = 640, cellH = 480;
const int logPanelH = 120;
const int gridCols = 2, gridRows = 1;
std::string windowTitle = "ANSLPR CPU Stress Test";
cv::namedWindow(windowTitle, cv::WINDOW_NORMAL);
cv::resizeWindow(windowTitle, cellW * gridCols, cellH * gridRows + logPanelH);
auto testStart = std::chrono::steady_clock::now();
while (g_running.load()) {
cv::Mat canvas(cellH * gridRows + logPanelH, cellW * gridCols, CV_8UC3, cv::Scalar(30, 30, 30));
for (int i = 0; i < NUM_TASKS; i++) {
int col = i % gridCols, row = i / gridCols;
cv::Rect roi(col * cellW, row * cellH, cellW, cellH);
cv::Mat cell;
double fps = 0, infMs = 0;
int fCount = 0, dCount = 0;
std::string statusMsg, lastPlate;
bool engineLoaded = false;
{
std::lock_guard<std::mutex> lk(taskStates[i].mtx);
if (!taskStates[i].displayFrame.empty())
cv::resize(taskStates[i].displayFrame, cell, cv::Size(cellW, cellH));
fps = taskStates[i].fps;
infMs = taskStates[i].inferenceMs;
fCount = taskStates[i].frameCount;
dCount = taskStates[i].detectionCount;
statusMsg = taskStates[i].statusMsg;
lastPlate = taskStates[i].lastPlate;
engineLoaded = taskStates[i].engineLoaded;
}
if (cell.empty()) {
cell = cv::Mat(cellH, cellW, CV_8UC3, cv::Scalar(40, 40, 40));
cv::putText(cell, "Task " + std::to_string(i) + ": " + statusMsg,
cv::Point(20, cellH / 2),
cv::FONT_HERSHEY_SIMPLEX, 0.8, cv::Scalar(100, 100, 255), 2);
}
// Status bar
cv::rectangle(cell, cv::Rect(0, cellH - 40, cellW, 40), cv::Scalar(0, 0, 0), cv::FILLED);
char bar[256];
snprintf(bar, sizeof(bar), "T%d(S%d) | %.1f FPS | %.0fms | F:%d | D:%d | %s",
i, taskStreamMap[i], fps, infMs, fCount, dCount,
lastPlate.empty() ? "-" : lastPlate.c_str());
cv::Scalar barColor = engineLoaded ? cv::Scalar(0, 255, 0) : cv::Scalar(0, 100, 255);
cv::putText(cell, bar, cv::Point(5, cellH - 12),
cv::FONT_HERSHEY_SIMPLEX, 0.45, barColor, 1);
cell.copyTo(canvas(roi));
}
// Grid line
if (gridCols > 1)
cv::line(canvas, cv::Point(cellW, 0), cv::Point(cellW, cellH * gridRows),
cv::Scalar(100, 100, 100), 1);
// Log panel
cv::Rect logRoi(0, cellH * gridRows, cellW * gridCols, logPanelH);
cv::Mat logPanel = canvas(logRoi);
logPanel.setTo(cv::Scalar(20, 20, 20));
auto elapsed = std::chrono::duration<double>(std::chrono::steady_clock::now() - testStart).count();
double totalFps = 0;
for (int i = 0; i < NUM_TASKS; i++) {
std::lock_guard<std::mutex> lk(taskStates[i].mtx);
totalFps += taskStates[i].fps;
}
char header[256];
snprintf(header, sizeof(header),
"Elapsed: %.0fs | %d cameras, %d AI tasks | Total: %.1f FPS | Press ESC to stop",
elapsed, NUM_STREAMS, NUM_TASKS, totalFps);
cv::putText(logPanel, header, cv::Point(10, 20),
cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(200, 200, 0), 1);
// Per-task summary
for (int i = 0; i < NUM_TASKS; i++) {
std::lock_guard<std::mutex> lk(taskStates[i].mtx);
char tLine[256];
snprintf(tLine, sizeof(tLine),
"T%d(S%d): FPS=%.1f Inf=%.0fms Frames=%d Det=%d",
i, taskStreamMap[i], taskStates[i].fps, taskStates[i].inferenceMs,
taskStates[i].frameCount, taskStates[i].detectionCount);
cv::putText(logPanel, tLine, cv::Point(10, 42 + i * 18),
cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(200, 200, 200), 1);
}
// Recent log
auto recentLogs = g_log.getRecent(3);
int logY = 42 + NUM_TASKS * 18 + 5;
for (const auto& line : recentLogs) {
if (logY > logPanelH - 5) break;
std::string display = (line.size() > 120) ? line.substr(0, 117) + "..." : line;
cv::putText(logPanel, display, cv::Point(10, logY),
cv::FONT_HERSHEY_PLAIN, 1.0, cv::Scalar(140, 140, 140), 1);
logY += 15;
}
cv::imshow(windowTitle, canvas);
int key = cv::waitKey(30);
if (key == 27) {
g_log.add("ESC pressed — stopping...");
printf("\nESC pressed — stopping...\n");
g_running.store(false);
}
}
// --- Wait for workers ---
for (int i = 0; i < NUM_TASKS; i++) {
if (workers[i].joinable()) workers[i].join();
}
// --- Final summary ---
double totalElapsed = std::chrono::duration<double>(
std::chrono::steady_clock::now() - testStart).count();
printf("\n============================================================\n");
printf(" FINAL SUMMARY (runtime: %.0fs)\n", totalElapsed);
printf("============================================================\n");
double totalFpsFinal = 0;
for (int i = 0; i < NUM_TASKS; i++) {
char buf[256];
snprintf(buf, sizeof(buf), " Task %d (Stream %d): %d frames, %d detections, FPS=%.1f, InfMs=%.0f",
i, taskStreamMap[i], taskStates[i].frameCount, taskStates[i].detectionCount,
taskStates[i].fps, taskStates[i].inferenceMs);
printf("%s\n", buf);
g_log.add(buf);
totalFpsFinal += taskStates[i].fps;
}
printf(" Total throughput: %.1f FPS\n", totalFpsFinal);
printf("============================================================\n");
// --- Cleanup ---
for (int i = 0; i < NUM_TASKS; i++) {
if (alprHandles[i]) ReleaseANSALPRHandle(&alprHandles[i]);
}
for (int s = 0; s < NUM_STREAMS; s++) {
if (rtspClients[s]) {
StopRTSP(&rtspClients[s]);
ReleaseANSRTSPHandle(&rtspClients[s]);
}
}
g_log.close();
cv::destroyAllWindows();
ANSCENTER::ANSOPENCV::DeinitCameraNetwork();
return 0;
}
int ANSLPR_MultiGPU_StressTest() {
ANSCENTER::ANSOPENCV::InitCameraNetwork();
// --- Initialize log file ---
g_log.init();
printf("\n");
// --- Auto-detect GPU availability (safe on CPU-only PCs without CUDA runtime) ---
int gpuCount = 0;
bool hasGpu = false;
if (IsCudaAvailable()) {
cudaGetDeviceCount(&gpuCount);
hasGpu = (gpuCount > 0);
}
const char* modeStr = hasGpu ? "GPU (NVIDIA CUDA)" : "CPU (Software Decoding)";
printf("\n");
printf("============================================================\n");
printf(" ANSLPR Multi-GPU Stress Test — 5 Parallel ALPR Tasks\n");
printf(" ANSLPR Multi-Engine Stress Test — 5 Parallel ALPR Tasks\n");
printf(" Mode: %s\n", modeStr);
printf(" (4 cameras, 5 AI tasks — Task 4 shares Stream 2)\n");
printf(" Press ESC to stop\n");
printf(" Log file: %s\n", LOG_FILE_PATH);
printf("============================================================\n\n");
g_log.add("============================================================");
g_log.add(" ANSLPR Multi-GPU Stress Test — 5 Parallel ALPR Tasks");
g_log.add(" ANSLPR Multi-Engine Stress Test — 5 Parallel ALPR Tasks");
g_log.add(" Mode: " + std::string(modeStr));
g_log.add("============================================================");
// --- Log GPU info for diagnostics ---
// --- Log GPU info for diagnostics (safe on CPU — prints "no GPU found") ---
LogGpuInfo();
// --- RTSP URLs (4 independent camera streams) ---
@@ -1027,7 +1487,7 @@ int ANSLPR_MultiGPU_StressTest() {
continue;
}
SetRTSPImageQuality(&rtspClients[s], 0);
SetRTSPHWDecoding(&rtspClients[s], 7); // HW_DECODING_CUDA: force CUDA/NVDEC zero-copy path
if (hasGpu) SetRTSPHWDecoding(&rtspClients[s], 7); // CUDA HW decode only with GPU
StartRTSP(&rtspClients[s]);
g_log.add("[Stream" + std::to_string(s) + "] RTSP started");
}
@@ -1040,7 +1500,7 @@ int ANSLPR_MultiGPU_StressTest() {
// =========================================================================
ANSCENTER::ANSALPR* alprHandles[NUM_TASKS] = {};
std::string modelZipFile = "C:\\ProgramData\\ANSCENTER\\ANSVIS Server\\ANSALPR\\ANS_ALPR_v1.2.zip";
int engineType = 1; // NVIDIA_GPU
int engineType = 1; // ANSALPR_OD: auto-detects GPU/CPU, uses ONNX Runtime on CPU
double detThresh = 0.5, ocrThresh = 0.5, colThresh = 0.5;
for (int i = 0; i < NUM_TASKS; i++) {
@@ -1074,11 +1534,12 @@ int ANSLPR_MultiGPU_StressTest() {
continue;
}
printf("%s Loading ALPR engine (TensorRT)...\n", tag);
printf("%s Loading ALPR engine (%s)...\n", tag, hasGpu ? "TensorRT" : "CPU");
g_log.add(std::string(tag) + " Loading ALPR engine...");
// Snapshot VRAM before engine load to measure consumption
auto vramBefore = GetPerGpuFreeMiB();
// Snapshot VRAM before engine load to measure consumption (GPU only)
std::vector<size_t> vramBefore;
if (hasGpu) vramBefore = GetPerGpuFreeMiB();
int loadResult = LoadANSALPREngineHandle(&alprHandles[i]);
auto engineEnd = std::chrono::steady_clock::now();
@@ -1094,40 +1555,47 @@ int ANSLPR_MultiGPU_StressTest() {
continue;
}
// Snapshot VRAM after engine load — find which GPU lost the most VRAM
auto vramAfter = GetPerGpuFreeMiB();
int bestGpu = 0;
int bestGpu = -1;
size_t maxDelta = 0;
size_t gpuCount = vramBefore.size() < vramAfter.size() ? vramBefore.size() : vramAfter.size();
for (size_t g = 0; g < gpuCount; g++) {
size_t delta = (vramBefore[g] > vramAfter[g]) ? (vramBefore[g] - vramAfter[g]) : 0;
if (delta > maxDelta) {
maxDelta = delta;
bestGpu = (int)g;
if (hasGpu) {
// Snapshot VRAM after engine load — find which GPU lost the most VRAM
auto vramAfter = GetPerGpuFreeMiB();
size_t gpuCnt = vramBefore.size() < vramAfter.size() ? vramBefore.size() : vramAfter.size();
bestGpu = 0;
for (size_t g = 0; g < gpuCnt; g++) {
size_t delta = (vramBefore[g] > vramAfter[g]) ? (vramBefore[g] - vramAfter[g]) : 0;
if (delta > maxDelta) {
maxDelta = delta;
bestGpu = (int)g;
}
}
}
char buf[512];
snprintf(buf, sizeof(buf),
"%s Engine loaded in %.0f ms | GPU[%d] | VRAM used: %zu MiB (Stream%d)",
tag, loadMs, bestGpu, maxDelta, streamIdx);
printf("%s\n", buf);
g_log.add(buf);
char buf[512];
snprintf(buf, sizeof(buf),
"%s Engine loaded in %.0f ms | GPU[%d] | VRAM used: %zu MiB (Stream%d)",
tag, loadMs, bestGpu, maxDelta, streamIdx);
printf("%s\n", buf);
g_log.add(buf);
// Log per-GPU VRAM state after this engine load
for (size_t g = 0; g < vramAfter.size(); g++) {
size_t total = 0;
if (g < vramBefore.size()) {
// Compute total from free + used
// Log per-GPU VRAM state after this engine load
for (size_t g = 0; g < vramAfter.size(); g++) {
size_t total = 0;
auto gpus = QueryGpuVram();
if (g < gpus.size()) total = gpus[g].totalMiB;
char vbuf[256];
snprintf(vbuf, sizeof(vbuf),
" GPU[%zu] VRAM: %zu MiB free (of %zu MiB)",
g, vramAfter[g], total);
printf("%s\n", vbuf);
g_log.add(vbuf);
}
char vbuf[256];
snprintf(vbuf, sizeof(vbuf),
" GPU[%zu] VRAM: %zu MiB free (of %zu MiB)",
g, vramAfter[g], total);
printf("%s\n", vbuf);
g_log.add(vbuf);
} else {
char buf[256];
snprintf(buf, sizeof(buf), "%s Engine loaded in %.0f ms (CPU mode, Stream%d)",
tag, loadMs, streamIdx);
printf("%s\n", buf);
g_log.add(buf);
}
{
@@ -1140,6 +1608,8 @@ int ANSLPR_MultiGPU_StressTest() {
}
// --- Align NVDEC decode GPU with inference GPU for NV12 zero-copy ---
// (GPU only — software decoding on CPU doesn't use NVDEC)
if (hasGpu)
// Each stream should decode on the same GPU as its inference engine to enable
// direct NVDEC→TensorRT zero-copy (0.5ms vs 17ms preprocess per frame).
//
@@ -1343,7 +1813,7 @@ int ANSLPR_MultiGPU_StressTest() {
streamUrls[streamIdx].c_str());
if (result == 1 && rtspClients[streamIdx]) {
SetRTSPImageQuality(&rtspClients[streamIdx], 0);
SetRTSPHWDecoding(&rtspClients[streamIdx], 7);
if (hasGpu) SetRTSPHWDecoding(&rtspClients[streamIdx], 7);
StartRTSP(&rtspClients[streamIdx]);
auto chaosEnd = std::chrono::steady_clock::now();
@@ -1368,8 +1838,9 @@ int ANSLPR_MultiGPU_StressTest() {
const int cellW = 480, cellH = 360; // Smaller cells for 3-column layout
const int logPanelH = 220;
const int gridCols = 3, gridRows = 2;
cv::namedWindow("ANSLPR Multi-GPU Stress Test", cv::WINDOW_NORMAL);
cv::resizeWindow("ANSLPR Multi-GPU Stress Test", cellW * gridCols, cellH * gridRows + logPanelH);
std::string windowTitle = hasGpu ? "ANSLPR Multi-GPU Stress Test" : "ANSLPR CPU Stress Test";
cv::namedWindow(windowTitle, cv::WINDOW_NORMAL);
cv::resizeWindow(windowTitle, cellW * gridCols, cellH * gridRows + logPanelH);
auto testStart = std::chrono::steady_clock::now();
auto lastGpuSnapshot = std::chrono::steady_clock::now();
@@ -1468,7 +1939,9 @@ int ANSLPR_MultiGPU_StressTest() {
snprintf(bar1, sizeof(bar1), "T%d(S%d) | %.1f FPS | %.0fms | F:%d | D:%d | %s",
i, taskStreamMap[i], fps, infMs, fCount, dCount,
lastPlate.empty() ? "-" : lastPlate.c_str());
if (gpuId >= 0) {
if (!hasGpu) {
snprintf(bar2, sizeof(bar2), "CPU mode (software decoding)");
} else if (gpuId >= 0) {
snprintf(bar2, sizeof(bar2), "GPU[%d] | VRAM: %zu MiB", gpuId, vramMiB);
} else {
snprintf(bar2, sizeof(bar2), "GPU: N/A");
@@ -1572,7 +2045,7 @@ int ANSLPR_MultiGPU_StressTest() {
gpuLineY += 15;
}
cv::imshow("ANSLPR Multi-GPU Stress Test", canvas);
cv::imshow(windowTitle, canvas);
int key = cv::waitKey(30);
if (key == 27) { // ESC
g_log.add("ESC pressed — stopping all tasks...");
@@ -2930,6 +3403,136 @@ int ANSLPR_MultiGPU_StressTest_FilePlayer() {
return 0;
}
// ANSLPR_OD_CPU_VideoTest — Uses ANSALPR_OD (engineType=1) on Intel CPU/iGPU.
// ANSALPR_OD auto-detects hardware (OpenVINO on Intel, DirectML on AMD, etc.)
// No CUDA calls — safe on non-NVIDIA systems.
int ANSLPR_OD_CPU_VideoTest() {
std::cout << "\n============================================================" << std::endl;
std::cout << " ANSLPR CPU/iGPU Test (ANSALPR_OD with auto-detect)" << std::endl;
std::cout << "============================================================\n" << std::endl;
std::string modelZipFile = "C:\\ProgramData\\ANSCENTER\\ANSVIS Server\\ANSALPR\\ANS_ALPR_v1.2.zip";
std::string videoFilePath = "C:\\ProgramData\\ANSCENTER\\Shared\\classroom.mp4";
std::cout << "Model: " << modelZipFile << std::endl;
std::cout << "Video: " << videoFilePath << std::endl;
ANSCENTER::ANSALPR* infHandle = nullptr;
int engineType = 1; // ANSALPR_OD (auto-detects HW internally)
double detThresh = 0.5, ocrThresh = 0.5, colThresh = 0.5;
// Step 1: Create handle
std::cout << "[LPR-CPU] Step 1: Creating handle..." << std::endl;
int createResult = CreateANSALPRHandle(&infHandle, "", modelZipFile.c_str(), "",
engineType, detThresh, ocrThresh, colThresh);
std::cout << "[LPR-CPU] CreateANSALPRHandle result: " << createResult << std::endl;
if (createResult != 1 || infHandle == nullptr) {
std::cerr << "[LPR-CPU] FAILED: CreateANSALPRHandle returned " << createResult << std::endl;
return -1;
}
// Step 2: Load engine
std::cout << "[LPR-CPU] Step 2: Loading engine..." << std::endl;
int loadResult = LoadANSALPREngineHandle(&infHandle);
std::cout << "[LPR-CPU] LoadANSALPREngineHandle result: " << loadResult << std::endl;
if (loadResult != 1) {
std::cerr << "[LPR-CPU] FAILED: LoadANSALPREngineHandle returned " << loadResult << std::endl;
ReleaseANSALPRHandle(&infHandle);
return -2;
}
// Step 3: Open video
std::cout << "[LPR-CPU] Step 3: Opening video..." << std::endl;
cv::VideoCapture capture(videoFilePath);
if (!capture.isOpened()) {
std::cerr << "[LPR-CPU] FAILED: Could not open video: " << videoFilePath << std::endl;
ReleaseANSALPRHandle(&infHandle);
return -3;
}
int totalFrames = static_cast<int>(capture.get(cv::CAP_PROP_FRAME_COUNT));
std::cout << "[LPR-CPU] Video opened: " << totalFrames << " frames" << std::endl;
// Step 4: Run inference
std::cout << "[LPR-CPU] Step 4: Running inference..." << std::endl;
boost::property_tree::ptree pt;
int frameIndex = 0;
int totalDetections = 0;
double totalInferenceMs = 0.0;
int maxFrames = 200;
while (frameIndex < maxFrames) {
cv::Mat frame;
if (!capture.read(frame)) {
std::cout << "[LPR-CPU] End of video at frame " << frameIndex << std::endl;
break;
}
frameIndex++;
unsigned int bufferLength = 0;
unsigned char* jpeg_bytes = CVMatToBytes(frame, bufferLength);
int height = frame.rows;
int width = frame.cols;
auto start = std::chrono::system_clock::now();
std::string detectionResult = ANSALPR_RunInferenceBinary(&infHandle, jpeg_bytes, width, height);
auto end = std::chrono::system_clock::now();
auto elapsed = std::chrono::duration_cast<std::chrono::milliseconds>(end - start);
totalInferenceMs += static_cast<double>(elapsed.count());
delete[] jpeg_bytes;
if (!detectionResult.empty()) {
try {
pt.clear();
std::stringstream ss;
ss << detectionResult;
boost::property_tree::read_json(ss, pt);
int detCount = 0;
BOOST_FOREACH(const boost::property_tree::ptree::value_type& child, pt.get_child("results")) {
const boost::property_tree::ptree& r = child.second;
const auto class_name = GetData<std::string>(r, "class_name");
const auto x = GetData<float>(r, "x");
const auto y = GetData<float>(r, "y");
const auto w = GetData<float>(r, "width");
const auto h = GetData<float>(r, "height");
detCount++;
cv::rectangle(frame, cv::Rect(x, y, w, h), cv::Scalar(0, 255, 0), 2);
cv::putText(frame, class_name, cv::Point(x, y - 5),
0, 0.6, cv::Scalar(0, 0, 255), 1, cv::LINE_AA);
}
totalDetections += detCount;
}
catch (...) {}
}
if (frameIndex % 10 == 0) {
double avgSoFar = totalInferenceMs / frameIndex;
std::cout << "[LPR-CPU] Frame " << frameIndex << "/" << maxFrames
<< " | Time: " << elapsed.count() << "ms"
<< " | Avg: " << static_cast<int>(avgSoFar) << "ms"
<< " | Detections: " << totalDetections << std::endl;
}
cv::imshow("ANSLPR CPU Test", frame);
if (cv::waitKey(1) == 27) break;
}
// Summary
double avgMs = (frameIndex > 0) ? (totalInferenceMs / frameIndex) : 0.0;
std::cout << "\n=== LPR CPU Test Summary ===" << std::endl;
std::cout << "Frames processed: " << frameIndex << std::endl;
std::cout << "Total detections: " << totalDetections << std::endl;
std::cout << "Avg inference: " << avgMs << " ms/frame" << std::endl;
std::cout << "Total time: " << totalInferenceMs << " ms" << std::endl;
std::cout << (frameIndex > 0 ? "[LPR-CPU] PASSED" : "[LPR-CPU] FAILED") << std::endl;
capture.release();
cv::destroyAllWindows();
ReleaseANSALPRHandle(&infHandle);
return (frameIndex > 0) ? 0 : -4;
}
int main()
{
// ANSLPR_OD_INDOInferences_FileTest();
@@ -2940,9 +3543,12 @@ int main()
//for (int i = 0; i < 100; i++) {
// ANSLPR_CPU_Inferences_FileTest();
//}
ANSLPR_MultiGPU_StressTest();
//ANSLPR_SingleTask_Test();
ANSLPR_CPU_StressTest();
//ANSLPR_MultiGPU_StressTest();
//ANSLPR_MultiGPU_StressTest_SimulatedCam();
// ANSLPR_MultiGPU_StressTest_FilePlayer();
//ANSLPR_OD_CPU_VideoTest();
return 0;
}

2
tests/ANSLPR-UnitTest/CMakeLists.txt
View File

@@ -7,6 +7,7 @@ target_include_directories(ANSLPR-UnitTest PRIVATE
${CMAKE_SOURCE_DIR}/modules/ANSLPR
${CMAKE_SOURCE_DIR}/modules/ANSLPR/include
${CMAKE_SOURCE_DIR}/modules/ANSODEngine
${CMAKE_SOURCE_DIR}/core/ANSLibsLoader/include
${CMAKE_SOURCE_DIR}/modules/ANSCV
${CMAKE_SOURCE_DIR}/MediaClient
${CMAKE_SOURCE_DIR}/MediaClient/media
@@ -36,6 +37,7 @@ target_link_libraries(ANSLPR-UnitTest
PRIVATE ANSODEngine
PRIVATE ANSCV
PRIVATE ANSLicensingSystem
PRIVATE ANSLibsLoader
PRIVATE anslicensing
PRIVATE ANSMOT
PRIVATE opencv

8
tests/ANSODEngine-UnitTest/ANSODEngine-UnitTest.cpp
View File

@@ -1449,8 +1449,8 @@ int YOLO26ODYolo12Test() {
}
int YOLO26ODYolo11Test() {
std::string modelFilePath = "C:\\Projects\\ANSVIS\\Models\\ANS_VehicleDetection_v2.0.zip";
std::string videoFile = "E:\\Programs\\DemoAssets\\Videos\\road.mp4";
int modelType = 31; // ONNX YOLO (30) RT YOLO (31)
std::string videoFile = "C:\\ProgramData\\ANSCENTER\\Shared\\road.mp4";
int modelType = 3; // ONNX YOLO (30) RT YOLO (31)
VideoDetectorEngine(modelFilePath, videoFile, modelType);
return 0;
}
@@ -1861,12 +1861,12 @@ int main()
//YOLO26POSEYolo11Test();
//YOLO26CLYolo11Test();
//YOLO26ODYolo12Test();
//YOLO26ODYolo11Test();
YOLO26ODYolo11Test();
//YOLO26ODYolo10Test();
//YOLO26OBBYolo11Test();
//SAM3ONNX_ImageTest(); // ORT reference — runs first, prints decoder input stats
//SAM3TRT_ImageTest(); // TRT under test — compare decoder input stats with above
CustomModel_StressTest_FilePlayer(); // Multi-task stress test (LabVIEW flow)
//CustomModel_StressTest_FilePlayer(); // Multi-task stress test (LabVIEW flow)
//SAM3TRT_UnitTest(); // TensorRT SAM3 test (in ANSSAM3-UnitTest.cpp)
//TensorRT10Test();
//FireNSmokeCustomDetection();