feat: HSAP platform v2 — modular navigation, quality review, audit log, world model simulation

Major changes:
- New frontend (platform/web/): Vite + React 18 + TypeScript + Tailwind
- 4-module navigation: 数据送标 / 模型管理 / 车队管理 / 系统管理
- Data catalog with charts (DMS/ADAS/Lane 3-tab view)
- Quality review workflow (标注质检): Good/Fine/Bad scoring with auto-advance
- Audit enhancements: batch operations, rejection categories, Feishu notifications
- Operation audit log (操作日志)
- World model simulation studio (仿真工坊)
- Dataset version management with snapshots and diff
- ADAS 7-class dataset integration (138K images organized + compressed)
- User management with Feishu integration and pagination
- CRUD/search/filter on all pages, card layout redesign
- PIL-optimized image overlay rendering
- Auto-snapshot on build, in_review workflow stage
- Removed embedded algorithm code (now in workspace)

algorithms/dms_yolo/code.embedded.bak/examples/YOLOv8-ONNXRuntime-CPP/inference.h

@@ -0,0 +1,96 @@
+// Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
+
+#pragma once
+
+#define    RET_OK nullptr
+
+#ifdef _WIN32
+#include <Windows.h>
+#include <direct.h>
+#include <io.h>
+#endif
+
+#include <string>
+#include <vector>
+#include <cstdio>
+#include <opencv2/opencv.hpp>
+#include "onnxruntime_cxx_api.h"
+
+#ifdef USE_CUDA
+#include <cuda_fp16.h>
+#endif
+
+
+enum MODEL_TYPE
+{
+    //FLOAT32 MODEL
+    YOLO_DETECT_V8 = 1,
+    YOLO_POSE = 2,
+    YOLO_CLS = 3,
+
+    //FLOAT16 MODEL
+    YOLO_DETECT_V8_HALF = 4,
+    YOLO_POSE_V8_HALF = 5,
+    YOLO_CLS_HALF = 6
+};
+
+
+typedef struct _DL_INIT_PARAM
+{
+    std::string modelPath;
+    MODEL_TYPE modelType = YOLO_DETECT_V8;
+    std::vector<int> imgSize = { 640, 640 };
+    float rectConfidenceThreshold = 0.6;
+    float iouThreshold = 0.5;
+    int	keyPointsNum = 2;//Note:kpt number for pose
+    bool cudaEnable = false;
+    int logSeverityLevel = 3;
+    int intraOpNumThreads = 1;
+} DL_INIT_PARAM;
+
+
+typedef struct _DL_RESULT
+{
+    int classId;
+    float confidence;
+    cv::Rect box;
+    std::vector<cv::Point2f> keyPoints;
+} DL_RESULT;
+
+
+class YOLO_V8
+{
+public:
+    YOLO_V8();
+
+    ~YOLO_V8();
+
+public:
+    char* CreateSession(DL_INIT_PARAM& iParams);
+
+    char* RunSession(cv::Mat& iImg, std::vector<DL_RESULT>& oResult);
+
+    char* WarmUpSession();
+
+    template<typename N>
+    char* TensorProcess(clock_t& starttime_1, cv::Mat& iImg, N& blob, std::vector<int64_t>& inputNodeDims,
+        std::vector<DL_RESULT>& oResult);
+
+    char* PreProcess(cv::Mat& iImg, std::vector<int> iImgSize, cv::Mat& oImg);
+
+    std::vector<std::string> classes{};
+
+private:
+    Ort::Env env;
+    Ort::Session* session;
+    bool cudaEnable;
+    Ort::RunOptions options;
+    std::vector<const char*> inputNodeNames;
+    std::vector<const char*> outputNodeNames;
+
+    MODEL_TYPE modelType;
+    std::vector<int> imgSize;
+    float rectConfidenceThreshold;
+    float iouThreshold;
+    float resizeScales;//letterbox scale
+};