修正parse_road无返回值导致崩溃的问题；

返回值中sy_point更换为cv::Point；优化model_path

修正parse_road无返回值导致崩溃的问题；
返回值中sy_point更换为cv::Point；优化model_path
Hu Chunming
1 parent 8d319775
Showing 21 changed files with 114 additions and 1027 deletions
jni/VehicleNativeInterface.cpp
src/PicAnalysis.cpp
src/ai_engine_module/HumanAnalysis.cpp
src/ai_engine_module/HumanAnalysis.h
src/ai_engine_module/HumanCarAnalysis.cpp
src/ai_engine_module/HumanCarAnalysis.h
src/ai_engine_module/MotorPhoneAnalysis.cpp
src/ai_engine_module/MotorPhoneAnalysis.h
src/ai_engine_module/MotorRainshedAnalysis.cpp
src/ai_engine_module/MotorRainshedAnalysis.h
src/ai_engine_module/RoadSegAnalysis.cpp
src/ai_engine_module/RoadSegAnalysis.h
src/ai_engine_module/VehicleAnalysis.cpp
src/ai_engine_module/VehicleAnalysis.h
src/ai_engine_module/VehicleHeadTail.cpp
src/ai_engine_module/VehicleHeadTail.h
src/ai_engine_module/VidClothes.cpp
src/ai_engine_module/VidClothes.h
src/ai_engine_module/va_test.cpp0
src/demo/main.cpp
@@ -126,28 +126,22 @@ JNIEXPORT jint JNICALL Java_com_objecteye_nativeinterface_vehicle_VehicleNativeI
     //�㷨���ò���
     jclass cls_vehcileAnalysisParam = env->GetObjectClass(vehicleAnalysisParam);
-    jfieldID fid_dbpath = env->GetFieldID(cls_vehcileAnalysisParam, "dbPath", "Ljava/lang/String;");
-	jfieldID fid_modelspath = env->GetFieldID(cls_vehcileAnalysisParam, "modelsPath", "Ljava/lang/String;");
+    jfieldID fid_sdk_path = env->GetFieldID(cls_vehcileAnalysisParam, "sdk_path", "Ljava/lang/String;");
     jfieldID fid_gpuid = env->GetFieldID(cls_vehcileAnalysisParam, "gpuId", "I");
-    jstring str_dbpath = (jstring)env->GetObjectField(vehicleAnalysisParam, fid_dbpath);
-    const char *dbpath = env->GetStringUTFChars(str_dbpath, JNI_FALSE);
-	jstring str_modlespath = (jstring)env->GetObjectField(vehicleAnalysisParam, fid_modelspath);
-	const char *models_path = env->GetStringUTFChars(str_modlespath, JNI_FALSE);
+    jstring str_sdk_path = (jstring)env->GetObjectField(vehicleAnalysisParam, fid_sdk_path);
+    const char *sdk_path = env->GetStringUTFChars(str_sdk_path, JNI_FALSE);
     jint gpuid = env->GetIntField(vehicleAnalysisParam, fid_gpuid);
     void *vaHandle = NULL;
     VillageParam param;
     param.dev_id = gpuid;
-    param.db_path = dbpath;
-    param.model_path = models_path;
+    param.sdk_path = sdk_path;
     int ret = village_pic_init(&vaHandle, param);
- 	if (ret != SUCCESS)
-	{
+ 	if (ret != SUCCESS) {
 		printf("jni info:va_init failed.");
 		return ret;
 	}
-
     if (ret == SUCCESS)
     {
@@ -166,8 +160,7 @@ JNIEXPORT jint JNICALL Java_com_objecteye_nativeinterface_vehicle_VehicleNativeI
         temp[0] = (jlong)vaHandle;
         env->SetLongArrayRegion(handle, 0, 1, temp);
     }
-    env->ReleaseStringUTFChars(str_dbpath, dbpath);
-	env->ReleaseStringUTFChars(str_modlespath, models_path);
+    env->ReleaseStringUTFChars(str_sdk_path, sdk_path);
     return ret;
 }
@@ -564,7 +557,7 @@ JNIEXPORT jint JNICALL Java_com_objecteye_nativeinterface_vehicle_VehicleNativeI
                 for (int k = 0; k < line_info.vec_pt.size(); k++)
                 {
                     auto pt = line_info.vec_pt[k];
-                    jobject line_info_point = env->NewObject(cls_SyPoint, mid_SyPoint, pt.x_, pt.y_);
+                    jobject line_info_point = env->NewObject(cls_SyPoint, mid_SyPoint, pt.x, pt.y);
                     env->SetObjectArrayElement(ptArray, k, line_info_point);
                 }
@@ -584,7 +577,7 @@ JNIEXPORT jint JNICALL Java_com_objecteye_nativeinterface_vehicle_VehicleNativeI
                 for (int k = 0; k < road_info.vec_pt.size(); k++)
                 {
                     auto pt = road_info.vec_pt[k];
-                    jobject road_info_point = env->NewObject(cls_SyPoint, mid_SyPoint, pt.x_, pt.y_);
+                    jobject road_info_point = env->NewObject(cls_SyPoint, mid_SyPoint, pt.x, pt.y);
                     env->SetObjectArrayElement(ptArray, k, road_info_point);
                 }
@@ -19,7 +19,7 @@ int PicAnalysis::init(VillageParam param) {
     int ret = SY_FAILED;
-    ret = m_vehicle_analysis.init(dev_id, 16);
+    ret = m_vehicle_analysis.init(dev_id, param.sdk_path, 16);
     if(0 != ret){
         return -1;
     }
@@ -27,37 +27,38 @@ int PicAnalysis::init(VillageParam param) {
     // head_tail_param ht_param;
     // ht_param.devId = dev_id;
     // ht_param.max_batch = 16;
+    // ht_param.sdk_path = param.sdk_path;
     // ret = m_head_tail_algorithm.init(ht_param);
     // if(0 != ret){
     //     return -1;
     // }
-    ret = m_clothes_algorithm.init(dev_id);
+    ret = m_clothes_algorithm.init(dev_id, param.sdk_path);
     if(0 != ret){
         return -1;
     }
-    ret = m_human_algorithm.init(dev_id);
+    ret = m_human_algorithm.init(dev_id, param.sdk_path);
     if(0 != ret){
         return -1;
     }
-    ret = m_human_car_algorithm.init(dev_id);
+    ret = m_human_car_algorithm.init(dev_id, param.sdk_path);
     if(0 != ret){
         return -1;
     }
-    ret = m_motor_rainshed_algorithm.init(dev_id);
+    ret = m_motor_rainshed_algorithm.init(dev_id, param.sdk_path);
     if(0 != ret){
         return -1;
     }
-    ret = m_motor_phone_algorithm.init(dev_id);
+    ret = m_motor_phone_algorithm.init(dev_id, param.sdk_path);
     if(0 != ret){
         return -1;
     }
-    ret = m_road_seg_algorithm.init(dev_id);
+    ret = m_road_seg_algorithm.init(dev_id, param.sdk_path);
     if(0 != ret){
         return -1;
     }
@@ -356,9 +357,9 @@ vector&lt;AnalysisResult&gt; PicAnalysis::analysis_img(vector&lt;sy_img&gt; vec_img){
             }
             //压黄实线
-            result_info.cross_line = m_road_seg_algorithm.check_cross_line(road_info.vec_line, vehicle_rect);
+            result_info.cross_line = m_road_seg_algorithm.check_cross_line(road_info.vec_line, vehicle_rect, src.width, src.height);
             // 压导流线
-            result_info.cross_diversion_line = m_road_seg_algorithm.check_cross_region(road_info.vec_road, vehicle_rect, 3);    //3是导流线区域
+            result_info.cross_diversion_line = m_road_seg_algorithm.check_cross_region(road_info.vec_road, vehicle_rect, src.width, src.height, 3);    //3是导流线区域
         }
     }
@@ -11,12 +11,14 @@ HumanAnalysis::~HumanAnalysis()
     release();
 }
-int HumanAnalysis::init(int devId){
+int HumanAnalysis::init(int devId, std::string sdk_root){
     ACL_CALL(aclrtCreateContext(&ctx, devId), SY_SUCCESS, SY_FAILED);
     ACL_CALL(aclrtSetCurrentContext(ctx), SY_SUCCESS, SY_FAILED);
+    std::string model_path = sdk_root + "/models/hp/hp220908_310p.om";
+
     hp_param param;
-    param.modelNames = "./models/hp/hp220908_310p.om";
+    param.modelNames = (char*)model_path.data();
     param.devId = devId;
     cout << "hp_init start " << endl;
@@ -14,7 +14,7 @@ public:
     HumanAnalysis(/* args */);
     ~HumanAnalysis();
-    int init(int devId);
+    int init(int devId, std::string sdk_root);
     vector<BodyColorInfo> detect(vector<sy_img> vec_img);
@@ -13,12 +13,14 @@ HumanCarAnalysis::~HumanCarAnalysis()
     release();
 }
-int HumanCarAnalysis::init(int devId){
+int HumanCarAnalysis::init(int devId, std::string sdk_root){
     ACL_CALL(aclrtCreateContext(&ctx, devId), SY_SUCCESS, SY_FAILED);
     ACL_CALL(aclrtSetCurrentContext(ctx), SY_SUCCESS, SY_FAILED);
+    std::string model_path = sdk_root + "/models/hcp/hcp211008_310p.om";
+
     hcp_param param;
-    param.modelNames = "./models/hcp/hcp211008_310p.om";
+    param.modelNames = (char*)model_path.data();
     param.devId = devId;
     cout << "hcp_init start " << endl;
@@ -41,7 +41,7 @@ public:
     HumanCarAnalysis(/* args */);
     ~HumanCarAnalysis();
-    int init(int devId);
+    int init(int devId, std::string sdk_root);
     std::vector<HumanCarResult> detect(vector<sy_img> vec_img);
@@ -10,11 +10,13 @@ MotorPhoneAnalysis::~MotorPhoneAnalysis()
     release();
 }
-int MotorPhoneAnalysis::init(int devId){
+int MotorPhoneAnalysis::init(int devId, std::string sdk_root){
     ACL_CALL(aclrtCreateContext(&ctx, devId), SY_SUCCESS, SY_FAILED);
+    std::string model_path = sdk_root + "/models/motor_phone/motor_phone1127_310p.om";
+
     motor_phone_param param;
-    param.modelNames = "./models/motor_phone/motor_phone1127_310p.om"; 
+    param.modelNames = (char*)model_path.data();
     param.thresld = 0.25;
     param.devId = devId;
@@ -11,7 +11,7 @@ public:
     MotorPhoneAnalysis(/* args */);
     ~MotorPhoneAnalysis();
-    int init(int devId);
+    int init(int devId, std::string sdk_root);
     vector<MotorPhoneResult> detect(vector<sy_img> vec_img);
@@ -10,11 +10,13 @@ MotorRainshedAnalysis::~MotorRainshedAnalysis()
     release();
 }
-int MotorRainshedAnalysis::init(int devId){
+int MotorRainshedAnalysis::init(int devId, std::string sdk_root){
     ACL_CALL(aclrtCreateContext(&ctx, devId), SY_SUCCESS, SY_FAILED);
+    std::string model_path = sdk_root + "/models/rainshed/motor_rainshed_231123_310p.om";
+
     mrc_param param;
-    param.modelNames = "./models/rainshed/motor_rainshed_231123_310p.om";
+    param.modelNames = (char*)model_path.data();
     param.thresld = 0.0;
     param.devId = devId;
@@ -11,7 +11,7 @@ public:
     MotorRainshedAnalysis(/* args */);
     ~MotorRainshedAnalysis();
-    int init(int devId);
+    int init(int devId, std::string sdk_root);
     vector<MotorRainshedResult> detect(vector<sy_img> vec_img);
@@ -12,11 +12,13 @@ RoadSegAnalysis::~RoadSegAnalysis()
     release();
 }
-int RoadSegAnalysis::init(int devId){
+int RoadSegAnalysis::init(int devId, std::string sdk_root){
     ACL_CALL(aclrtCreateContext(&ctx, devId), SY_SUCCESS, SY_FAILED);
+    std::string model_path = sdk_root + "/models/road_seg/tzroad_seg240108_310p.om";
+
     rs_param param;
-    param.modelNames = "./models/road_seg/tzroad_seg240108_310p.om";
+    param.modelNames = (char*)model_path.data();
     param.thresld = 0.25;
     param.devId = devId;
@@ -93,33 +95,20 @@ RoadInfo RoadSegAnalysis::parse_road(rs_result one_result, sy_img src)
     cv::Mat seg_output = seg_post_process(large_resolution, one_result.seg_array, combined, poly_masks, region_classes, lanes, cats, x_sort); //m_masks:mask前的结果  poly_masks后的结果               
     for (int i = 0; i < lanes.size(); ++i) {
-        std::vector<cv::Point> points = lanes[i];
         LineInfo info;
-        for (size_t j = 0; j < points.size(); j++)
-        {
-            sy_point pt;
-            pt.x_ = points[j].x;
-            pt.y_ = points[j].y;
-
-            info.vec_pt.push_back(pt);
-        }
+        info.vec_pt = lanes[i];
         info.line_type = cats[i];
         one_road.vec_line.push_back(info);
     } 
     for (int i = 0; i < poly_masks.size(); ++i) {
-        std::vector<cv::Point> points = poly_masks[i];
         SegInfo seg_info;
-        for (int j = 0; j < points.size(); ++j) {
-            sy_point pt;
-            pt.x_ = points[j].x;
-            pt.y_ = points[j].y;
-
-            seg_info.vec_pt.push_back(pt);
-        }
+        seg_info.vec_pt = poly_masks[i];
         seg_info.seg_type = region_classes[i];
         one_road.vec_road.push_back(seg_info);
     }
+
+    return one_road;
 }
 std::vector<SegInfo> RoadSegAnalysis::parse_direct(rs_result one_result, sy_img src) {
@@ -133,21 +122,26 @@ std::vector&lt;SegInfo&gt; RoadSegAnalysis::parse_direct(rs_result one_result, sy_img 
     cv::Mat seg_output = seg_post_process(large_resolution, one_result.direct_seg, combined, poly_masks, region_classes, lanes, cats, x_sort); //m_masks:mask前的结果  poly_masks后的结果               
+
+    cv::Mat image(cv::Size(640, 360), CV_8UC3, cv::Scalar(0, 0, 0));
+
     std::vector<SegInfo> vec_road;
     for (int i = 0; i < poly_masks.size(); ++i) {
-        std::vector<cv::Point> points = poly_masks[i];
         SegInfo seg_info;
-        for (int j = 0; j < points.size(); ++j) {
-            sy_point pt;
-            pt.x_ = points[j].x;
-            pt.y_ = points[j].y;
-
-            seg_info.vec_pt.push_back(pt);
-        }
         seg_info.seg_type = region_classes[i];
+        seg_info.vec_pt = poly_masks[i];
+
+        int k = seg_info.seg_type;
+        const cv::Scalar color(seg_colors[k][0], seg_colors[k][1], seg_colors[k][2]);
+
+        polylines(image, seg_info.vec_pt, true, color, 3, cv::LINE_AA);
+
         vec_road.push_back(seg_info);
     }
+    cv::imwrite("./direct.jpg", image);
+    image.release();
+
     return vec_road;
 }
@@ -202,17 +196,15 @@ int RoadSegAnalysis::check_reverse_driving(std::vector&lt;SegInfo&gt;&amp; vec_direct, sy_
     for (size_t i = 0; i < vec_direct.size(); i++) {
         SegInfo& region = vec_direct[i];
         if (region.seg_type == 1) {
-            std::vector<cv::Point> vec_pt;
-            for (size_t j = 0; j < region.vec_pt.size(); j++) {
-                double dist  = pointPolygonTest(polygon_pts, cv::Point2f(region.vec_pt[j].x_, region.vec_pt[j].y_), false);
+            for (size_t j = 0; j < polygon_pts.size(); j++) {
+                double dist  = pointPolygonTest(region.vec_pt, polygon_pts[j], false);
                 if (dist > 0) {
                     coming_count ++;
                 }
             }
         } else if (region.seg_type == 2) {
-            std::vector<cv::Point> vec_pt;
-            for (size_t j = 0; j < region.vec_pt.size(); j++) {
-                double dist  = pointPolygonTest(polygon_pts, cv::Point2f(region.vec_pt[j].x_, region.vec_pt[j].y_), false);
+            for (size_t j = 0; j < polygon_pts.size(); j++) {
+                double dist  = pointPolygonTest(region.vec_pt, polygon_pts[j], false);
                 if (dist > 0) {
                     leaving_count ++;
                 }
@@ -259,10 +251,10 @@ int RoadSegAnalysis::check_reverse_driving(std::vector&lt;SegInfo&gt;&amp; vec_direct, sy_
     return -1;
 }
-int RoadSegAnalysis::check_cross_line(std::vector<LineInfo>& vec_line, sy_rect src_rc) {
+int RoadSegAnalysis::check_cross_line(std::vector<LineInfo>& vec_line, sy_rect src_rc, int src_width, int src_height) {
-    float scale_w = 640.0 / src_rc.width_;
-	float scale_h = 360.0 / src_rc.height_;
+    float scale_w = 640.0 / src_width;
+    float scale_h = 360.0 / src_height;
     sy_rect rc;
     rc.left_ = src_rc.left_ * scale_w;
@@ -294,9 +286,8 @@ int RoadSegAnalysis::check_cross_line(std::vector&lt;LineInfo&gt;&amp; vec_line, sy_rect s
         if (line.line_type == 1 || line.line_type == 2) {
             // 黄实线
             int in_count = 0;
-            std::vector<cv::Point> vec_pt;
             for (size_t j = 0; j < line.vec_pt.size(); j++) {
-                double dist  = pointPolygonTest(polygon_pts, cv::Point2f(line.vec_pt[j].x_, line.vec_pt[j].y_), false);
+                double dist  = pointPolygonTest(polygon_pts, line.vec_pt[j], false);
                 if (dist > 0) {
                     in_count ++;
                 }
@@ -312,7 +303,16 @@ int RoadSegAnalysis::check_cross_line(std::vector&lt;LineInfo&gt;&amp; vec_line, sy_rect s
     return -1;
 }
-int RoadSegAnalysis::check_cross_region(std::vector<SegInfo>& vec_reg, sy_rect rc, int region_type) {
+int RoadSegAnalysis::check_cross_region(std::vector<SegInfo>& vec_reg, sy_rect src_rc, int src_width, int src_height, int region_type) {
+
+    float scale_w = 640.0 / src_width;
+    float scale_h = 360.0 / src_height;
+
+    sy_rect rc;
+    rc.left_ = src_rc.left_ * scale_w;
+    rc.width_ = src_rc.width_ * scale_w;
+    rc.top_ = src_rc.top_ * scale_h;
+    rc.height_ = src_rc.height_ * scale_h;
     std::vector<cv::Point> polygon_pts;
     cv::Point pt_lt;
@@ -336,11 +336,11 @@ int RoadSegAnalysis::check_cross_region(std::vector&lt;SegInfo&gt;&amp; vec_reg, sy_rect r
     for (size_t i = 0; i < vec_reg.size(); i++) {
         SegInfo& seg = vec_reg[i];
         if (seg.seg_type == region_type) {
-            // 黄实线
+            
             int in_count = 0;
-            std::vector<cv::Point> vec_pt;
+            // 车辆与region相交
             for (size_t j = 0; j < seg.vec_pt.size(); j++) {
-                double dist  = pointPolygonTest(polygon_pts, cv::Point2f(seg.vec_pt[j].x_, seg.vec_pt[j].y_), false);
+                double dist  = pointPolygonTest(polygon_pts, seg.vec_pt[j], false);
                 if (dist > 0) {
                     in_count ++;
                 }
@@ -350,76 +350,20 @@ int RoadSegAnalysis::check_cross_region(std::vector&lt;SegInfo&gt;&amp; vec_reg, sy_rect r
             {//有5个点就认为是压线了
                 return 1;
             }
+
+            // 车辆与region相交情形未检测出来，检测车辆在region中情形
+            for (size_t j = 0; j < polygon_pts.size(); j++) {
+                double dist  = pointPolygonTest(seg.vec_pt, polygon_pts[j], false);
+                if (dist > 0) {
+                    return 1;
+                }
+            }
         }
     }
     return -1;
 }
-// cv::Mat imshow_lanes(cv::Mat img, const rs_lane* lanes, int lane_count) {
-// 	float scale_w = img.cols / 640.0;
-// 	float scale_h = img.rows / 360.0;
-//     std::vector<std::pair<std::vector<cv::Point>, int>> combined;
-//     lanes_process(lanes, lane_count, combined, scale_w, scale_h);
-
-//     for (const auto& lane_info : combined) {
-//         const auto& xys = lane_info.first;
-//         int cls = lane_info.second;
-// 		cv::Scalar color(lane_colors[cls][0],lane_colors[cls][1],lane_colors[cls][2]);
-//         for (size_t i = 1; i < xys.size(); ++i) {
-//             cv::line(img, xys[i - 1], xys[i], color, 4);
-//         }
-//     }
-    
-//     return img;
-// }
-
-// void RoadSegAnalysis::post_direct(rs_result one_result, sy_img src){
-// 	int src_width = src.w_;
-// 	int src_height = src.h_;
-//     int w = 640;
-//     int h = 360;
-//     float alpha = 0.75;
-//     cv::Mat overlayed_direct_img(cv::Size(w,h), CV_8UC3, cv::Scalar(0, 0, 0));
-//     // 将车道线标签转换为彩色图像
-//     for (int i = 0; i < h; ++i) {
-//         for (int j = 0; j < w; ++j) {
-//             int idx = one_result.direct_seg[(i * w + j)];
-//             overlayed_direct_img.at<cv::Vec3b>(i, j)[0] = seg_colors[idx][0]; // R通道;
-//             overlayed_direct_img.at<cv::Vec3b>(i, j)[1] = seg_colors[idx][1]; // G通道
-//             overlayed_direct_img.at<cv::Vec3b>(i, j)[2] = seg_colors[idx][2]; // B通道
-//         }
-//     }
-//     cv::resize(overlayed_direct_img, overlayed_direct_img, cv::Size(src_width,src_height), 0, 0, cv::INTER_LINEAR); 
-//     // 将原始图像和彩色车道线图进行混合
-//     // cv::addWeighted(cvImg, alpha, overlayed_direct_img, 1 - alpha, 0, overlayed_direct_img);
-//     cv::Mat img_direct_lane = imshow_lanes(overlayed_direct_img, one_result.reg_array, one_result.lane_count);
-//     cv::imwrite("img_direct_lane.jpg", img_direct_lane);
-
-
-//     std::vector<std::pair<std::vector<cv::Point>, int>> combined;
-//     lanes_process(one_result.reg_array, one_result.lane_count, combined);
-//     std::vector<std::vector<cv::Point>> poly_masks, lanes, direct_masks, merge_masks;
-//     std::vector<int> region_classes, cats, direct_classes, merge_classes;
-//     cv::Mat background_mask;
-//     std::map<double, int> x_sort;
-//     bool large_resolution = false;
-//     if (src_height > 1920) large_resolution = true;
-//     cv::Mat seg_output = seg_post_process(large_resolution, one_result.seg_array, combined, poly_masks, region_classes, lanes, cats, x_sort, background_mask); //m_masks:mask前的结果  poly_masks后的结果
-//     cv::Mat direct_output = direct_post_process(large_resolution, one_result.direct_seg, direct_masks, direct_classes);
-//     cv::Mat merge_output = merge_direct_process(large_resolution, one_result.direct_seg, merge_masks, merge_classes);
-
-//     cv::Mat image(cv::Size(w,h), CV_8UC3, cv::Scalar(0, 0, 0));
-//     cv::Mat vis_image = mask_to_rgb(image, seg_output);
-//     cv::Mat direct_image = mask_to_rgb(image, direct_output);
-//     cv::Mat merge_image = mask_to_rgb(image, merge_output);
-//     cv::imwrite("vis_image.jpg", vis_image);
-//     cv::imwrite("direct_image.jpg", direct_image);
-//     cv::imwrite("merge_image.jpg", merge_image);
-//     cv::imwrite("background_mask.jpg", background_mask);
-// }
-
-
 cv::Mat RoadSegAnalysis::mask_to_rgb(cv::Mat img, cv::Mat mask) {
     cv::Mat masks = img.clone();
     int reg_cls = 8;
@@ -612,10 +556,6 @@ cv::Mat RoadSegAnalysis::seg_post_process(bool large_resolution, unsigned char *
                 if (x_sort.count(centr_x)) centr_x += 0.0001;
                 x_sort.insert(std::make_pair(centr_x, count));
                 ++ count;
-                // for (auto iter: contours_poly) {
-                //     std::cout << "contour " << iter << " " << cat << std::endl;
-                // }
-    
             }
         }    
     }
@@ -18,15 +18,15 @@ public:
     RoadSegAnalysis(/* args */);
     ~RoadSegAnalysis();
-    int init(int devId);
+    int init(int devId, std::string sdk_root);
     std::vector<RoadInfo> detect(vector<sy_img> vec_img);
     int check_reverse_driving(std::vector<SegInfo>& vec_direct, sy_rect rc, int src_width, int src_height, int head_or_tail);
-    int check_cross_line(std::vector<LineInfo>& vec_line, sy_rect rc);
+    int check_cross_line(std::vector<LineInfo>& vec_line, sy_rect rc, int src_width, int src_height);
-    int check_cross_region(std::vector<SegInfo>& vec_reg, sy_rect rc, int region_type);
+    int check_cross_region(std::vector<SegInfo>& vec_reg, sy_rect rc, int src_width, int src_height, int region_type);
 private:
     int release();
@@ -9,7 +9,7 @@ VehicleAnalysis::~VehicleAnalysis() {
     release();
 }
-int VehicleAnalysis::init(int devId, int max_batch_size) {
+int VehicleAnalysis::init(int devId, std::string sdk_root, int max_batch_size) {
 	param.vehicle_detect_config= SY_CONFIG_OPEN;  //1.开启车检测 SY_CONFIG_CLOSE  SY_CONFIG_OPEN
     param.vehicle_recg_config= SY_CONFIG_OPEN;     //4.开启车型识别
@@ -52,9 +52,11 @@ int VehicleAnalysis::init(int devId, int max_batch_size) {
 	//车颜色阈值
 	param.vc_thresld = 0.5;
+    string dbPath = sdk_root + "/models/vehicle_analysis/db/vr_h0725x210605_r191230.db";
+    string models_path = sdk_root + "/models/vehicle_analysis/";
 	//车型参数
-	param.dbPath="./models/vehicle_analysis/db/vr_h0725x210605_r191230.db";	
-	param.models_Path="./models/vehicle_analysis/";	//所有模型的地址
+	param.dbPath= (char*)dbPath.data();	
+	param.models_Path= (char*)models_path.data();	//所有模型的地址
     cout << "va_init start " << endl;
     // 内部有 ctx
@@ -38,7 +38,7 @@ public:
     VehicleAnalysis(/* args */);
     ~VehicleAnalysis();
-    int init(int devId, int max_batch_size);
+    int init(int devId, std::string sdk_root, int max_batch_size);
     va_result* detect(vector<sy_img> vec_img);
@@ -17,8 +17,10 @@ int VehicleHeadTail::init(head_tail_param param){
     LOG_INFO("head_tail version: head_tail_256.2024.12.18");
+    string model_path = param.sdk_root + "/models/car_head_tail/head_tail_256_241220_310P.om";
+
     m_cnn_cls = new CnnCls();
-    int ret = m_cnn_cls->Init("./models/car_head_tail/head_tail_256_241220_310P.om");
+    int ret = m_cnn_cls->Init(model_path.c_str());
     if (ret != SY_SUCCESS) {
         delete m_cnn_cls;
         m_cnn_cls = nullptr;
@@ -14,6 +14,7 @@ typedef struct head_tail_param
 {
     int devId;              //ָ指定显卡id
     int max_batch;
+    std::string sdk_root;
     head_tail_param() :devId(0), max_batch(8){};
 } head_tail_param;
@@ -9,11 +9,13 @@ VidClothes::~VidClothes()
     release();
 }
-int VidClothes::init(int devId){
+int VidClothes::init(int devId, std::string sdk_root){
     ACL_CALL(aclrtCreateContext(&ctx, devId), SY_SUCCESS, SY_FAILED);
+    std::string model_path = sdk_root + "/models/vid_clothes/vidClothes0325_310P.om";
+
     vidclothes_param param;
-    param.modelNames = "./models/vid_clothes/vidClothes0325_310P.om";
+    param.modelNames = (char*)model_path.data();
     param.thresld = 0.0;
     param.devId = devId;
@@ -7,7 +7,7 @@ public:
     VidClothes(/* args */);
     ~VidClothes();
-    int init(int devId);
+    int init(int devId, std::string sdk_root);
     vector<int> detect(vector<sy_img> vec_img);
-#include <iostream>
-#include <sstream>
-#include <fstream>
-
-#include "sy_common.h"
-#include "sy_errorinfo.h"
-#include "vehicle_analysis.h"
-#include "vehicle_result.h"
-
-#include "opencv2/opencv.hpp"
-#include "opencv2/imgcodecs/legacy/constants_c.h"
-#include "opencv2/imgproc/types_c.h"
-#include "time.h"
-#include "sys/time.h"
-
-#include "utils.h"
-#include "dvpp_process.h"
-
-using namespace std;
-using namespace cv;
-
-#include <chrono>
-#include <dirent.h>
-
-
-
-//static char colorLabel[13][8] = { "棕", "橙", "灰", "白", "粉", "紫", "红", "绿", "蓝", "银", "青", "黄", "黑" };
-static std::vector<std::string> CARCOLOR1 = {
-	"BROWN","ORANGE","GRAY","WHITE","PINK","PURPLE","RED","GREEN","BLUE",
-	"SILVER","CYAN","YELLOW","BLACK"
-};
-
-static char vsLabel[11][40] = { "diao", "guan",  "huo", "zha", "jiao","jiu",  "la", "xiao", "qing", "sui","wei" };
-
-
-double msecond() {
-    struct timeval tv;
-    gettimeofday(&tv, 0);
-    return (tv.tv_sec * 1000.0 + tv.tv_usec / 1000.0);
-}
-
-
-void getAllNm(std::string pthNm, std::vector<std::string>& fileList)
-{
-        DIR    *dir;
-    struct    dirent    *ptr;
-    dir = opendir(pthNm.c_str()); ///open the dir
-    int filenum = 0;
-    while((ptr = readdir(dir)) != NULL) ///read the list of this dir
-    {
-        // char* to string
-        std::string curNm = ptr->d_name;
-        if(curNm != "." && curNm != "..")
-        {
-                filenum++;
-                fileList.push_back(curNm);
-                //printf("file %d name: %s\n", filenum, curNm.c_str());
-        }
-   }
-    closedir(dir);
-}
-
-
-void CvBGR2NV21(Mat& bgr, unsigned char* yuv) {
-    int stride = (bgr.cols + 127) / 128 * 128;
-    int strideH = (bgr.rows + 15) / 16 * 16;
-    for (int i = 0; i < bgr.rows; i++) {
-        for (int j = 0; j < bgr.cols; j++) {
-            int B = bgr.at<cv::Vec3b>(i, j)[0];
-            int G = bgr.at<cv::Vec3b>(i, j)[1];
-            int R = bgr.at<cv::Vec3b>(i, j)[2];
-
-            int Y = (77 * R + 150 * G + 29 * B) >> 8;
-            yuv[i * stride + j] = (Y < 0) ? 0 : ((Y > 255) ? 255 : Y);
-            if (i % 2 == 0 && j % 2 == 0) {
-                int U = ((-44 * R - 87 * G + 131 * B) >> 8) + 128;
-                int V = ((131 * R - 110 * G - 21 * B) >> 8) + 128;
-                yuv[strideH * stride + i / 2 * stride + j] = (V < 0) ? 0 : ((V > 255) ? 255 : V);
-                yuv[strideH * stride + i / 2 * stride + j + 1] = (U < 0) ? 0 : ((U > 255) ? 255 : U);
-            }
-        }
-    }
-}
-
-
-
-
-
-
-
-int main() {
-
-	//ofstream oFile;
-    //打开要输出的文件
-    //oFile.open("va_result.csv", ios::out | ios::trunc);
-	//oFile << "image" << "," << "image_quality_score" << "," << "count" << "," << "vehicle_info" << endl;
-
-
-    cout << va_get_version() << endl;
-
-	//string imagepath= "./vpt/";
-	//string saveimagepath= "./result/";
-	//int gpuid = 0;
-		
-	//string imagepath= "/home/HwHiAiUser/WH/vehicle_analysis202105/data/vpt/";
-	//string imagepath= "/home/HwHiAiUser/WH/vehicle_analysis202105/data/bug/";
-	string img_file_path= "/data/wanghong/Atlas310pro/vehicle_analysis202303/data/bug/";
-	//string imagepath= "/home/HwHiAiUser/WH/vehicle_analysis202105/data/img/";
-	//string imagepath= "/home/HwHiAiUser/WH/vehicle_analysis202105/data/carset/";
-	string saveimagepath= "/data/wanghong/Atlas310pro/vehicle_analysis202303/data/result/";
-	int gpuid = 0;
-	
-	va_param param;	
-	param.vehicle_detect_config= SY_CONFIG_OPEN;  //1.开启车检测 SY_CONFIG_CLOSE  SY_CONFIG_OPEN
-	param.vehicle_color_config= SY_CONFIG_OPEN;  //3.开启车颜色识别
-	param.vehicle_recg_config= SY_CONFIG_OPEN;     //4.开启车型识别
-	param.vehicle_recg_supplement_config= SY_CONFIG_OPEN;     //4.开启车型识别补充识别
-	param.vehicle_plate_det_recg_config= SY_CONFIG_OPEN; //5.开启车牌检测识别	
-	param.vehicle_pendant_det_config= SY_CONFIG_OPEN; //6.开启车属性检测识别	
-	param.vehicle_illegal_config= SY_CONFIG_OPEN;  //7.开启车违规
-	param.vehicle_feature_config= SY_CONFIG_OPEN;  //8.开启车辆特征提取
-	param.vehicle_motor_tricycle_analysis_config= SY_CONFIG_OPEN;  //8.摩托车分析
-	param.vehicle_manned_config= SY_CONFIG_OPEN;  //8.开启载人分析	
-	
-	
-	param.gpuid=gpuid;
-		
-	//车检测参数	
-	//param.vehicle_det_param.process_min_l = 720;// 720;
-	//param.vehicle_det_param.process_max_l = 1280;//1280;	
-	//param.vehicle_det_param.thresld=0.3;
-	//param.min_obj_size=200;  //最小目标	
-	param.vehicle_det_thresld=0.4;
-	
-	//车牌检测参数
-	//param.vehicle_plate_det_param.process_min_l=320;
-	//param.vehicle_plate_det_param.process_max_l=320;	
-	//param.vehicle_plate_det_param.thresld=0.4;
-	param.vehicle_plate_det_thresld=0.5;
-	
-	//车属性检测参数
-	//param.vehicle_attribute_det_param.process_min_l=360;
-	//param.vehicle_attribute_det_param.process_max_l=640;	
-	//param.vehicle_attribute_det_param.thresld=0.3;
-	param.vehicle_attribute_det_thresld=0.5;
-	
-	//车logo检测参数
-	//param.vehicle_logo_det_param.process_min_l=512;
-	//param.vehicle_logo_det_param.process_max_l=512;	
-	//param.vehicle_logo_det_param.thresld=0.1;
-	param.vehicle_logo_det_thresld=0.1;	
-	
-	//车颜色阈值
-	param.vc_thresld = 0.5;
-	
-	//车型参数
-	param.dbPath="/data/wanghong/Atlas310pro/vehicle_analysis202303/vehicle_analysis/db/vr_h0725x210605_r191230.db";	
-	//param.dbPath="../db/vr_h0725x210605_r191230.db";
-	
-	param.models_Path="/data/wanghong/Atlas310pro/vehicle_analysis202303/vehicle_analysis/all_models/";	//所有模型的地址
-    //param.models_Path="../modelsPath/";	//所有模型的地址
-	
-	
-	int ret0= va_acl_init();
-	
-    void* handle = nullptr;	
-    cout << "init start " << endl;
-    int ret = va_init(&handle, param);
-    if (ret == 0) {
-        cout << "init success " << endl;
-	}
-	else
-		return ret;
-	
-	
-	
-	
-//	void* handle111 = nullptr;
-//	cout << "init2 start " << endl;
-//    int ret2 = va_init(&handle111, param);
-//    if (ret2 == 0) {
-//        cout << "init2 success " << endl;
-//	}
-//	else
-//	{
-//		cout << "init2 failed " << endl;
-//		return ret2;
-//	}
-	
-	
-	
-	double t3=0;
-	int count =0;
-	
-//temp
-    aclrtContext ctx;
-	ACL_CALL(aclrtCreateContext(&ctx, gpuid), ACL_ERROR_NONE, SY_FAILED);
-	ACL_CALL(aclrtSetCurrentContext(ctx), ACL_ERROR_NONE, SY_FAILED);
-		
-    aclrtStream stream = nullptr;
-	ACL_CALL(aclrtCreateStream(&stream), ACL_ERROR_NONE, SY_FAILED);
-    DvppProcess* dvpp = new DvppProcess();
-	dvpp->InitResource(stream);
-
-for(int iter =0;iter<100;iter++)
-{	
-	//ifstream infile("list.txt");	
-	//ifstream infile("list_bug.txt");	
-	//ifstream infile("list_700W.txt");
-	//ifstream infile("list_img.txt");
-	//string file;
-	std::vector<std::string> fileList;
-    getAllNm(img_file_path,fileList);
-    if (fileList.empty()) throw std::logic_error("No suitable images were found");
-
-		
-    for (auto & file : fileList)
-	{
-        string filename = img_file_path + file;
-		cout << "img path: " << filename << endl;
-		const int batch_size = 1;
-		printf("batch_size=%d \n",batch_size);
-
-		Mat cvImg = imread(filename.c_str());
-		sy_img imgs[batch_size];
-	
-		ACL_CALL(aclrtSetCurrentContext(ctx), ACL_ERROR_NONE, SY_FAILED);
-		ImageData src[batch_size], dvpp_data[batch_size];
-		if(1)
-		{				 
-			for (int b = 0; b < batch_size; b++) {
-				Utils::ReadImageFile(src[b], filename); //将二进制图像读入内存，并读取宽高信息
-				ACL_CALL(dvpp->CvtJpegToYuv420sp(dvpp_data[b], src[b]), SY_SUCCESS, SY_FAILED); //解码
-				imgs[b].w_ = dvpp_data[b].width;//dvpp_data[b].alignWidth;
-				imgs[b].h_ = dvpp_data[b].height;//dvpp_data[b].alignHeight;
-				imgs[b].data_ = dvpp_data[b].data.get();//(uint8_t*)Utils::CopyDataDeviceToLocal(dvpp_data[b].data.get(), dvpp_data[b].size);
-			}								
-		}
-		
-		ImageData img_data_dvpp[batch_size];
-		sy_img imgs_device[batch_size];
-		if(0)
-		{
-			uint32_t alignWidth = (cvImg.cols + 127) / 128 * 128;
-			uint32_t alignHeight = (cvImg.rows + 15) / 16 * 16;
-			uint32_t size = alignWidth * alignHeight * 1.5;
-			std::shared_ptr<uint8_t> data = shared_ptr<uint8_t>((new uint8_t[size]), 
-				[](uint8_t* p) {delete [] p;});
-			CvBGR2NV21(cvImg, data.get());
-		 
-			for (int i = 0; i < batch_size; i++) {
-				imgs[i].w_ = cvImg.cols;
-				imgs[i].h_ = cvImg.rows;
-				imgs[i].data_ = data.get();
-				//转到device输入
-				Utils::CopysyImageDataToDvpp(img_data_dvpp[i], imgs[i]);
-				imgs_device[i].w_ = img_data_dvpp[i].width;//dvpp_data[b].alignWidth;
-				imgs_device[i].h_ = img_data_dvpp[i].height;//dvpp_data[b].alignHeight;
-				imgs_device[i].data_ = img_data_dvpp[i].data.get();
-			}				
-		}
-		
-		if(0)
-		{
-			uint32_t alignWidth = (cvImg.cols + 127) / 128 * 128;
-			uint32_t alignHeight = (cvImg.rows + 15) / 16 * 16;
-			uint32_t size = alignWidth * alignHeight * 1.5;
-			std::shared_ptr<uint8_t> data = shared_ptr<uint8_t>((new uint8_t[size]), 
-				[](uint8_t* p) {delete [] p;});
-			CvBGR2NV21(cvImg, data.get());
-		 
-			for (int i = 0; i < batch_size; i++) {
-				imgs[i].w_ = cvImg.cols;
-				imgs[i].h_ = cvImg.rows;
-				imgs[i].data_ = data.get();
-			}
-			
-		}
-		
-		count++;
-		
-		va_result *result=new va_result[batch_size];
-		for(int b=0;b<batch_size;b++)
-		{
-			result[b].count=0;
-			result[b].info=new vehicle_info[100];
-			for(int c=0; c<100; c++)
-			{
-				result[b].info[c].vehicle_pendant_det_res.vpd_res=new v_pendant_d_info[300];	
-			}			
-		}
-		
-		double t1,t2;
-		t1 = msecond();
-		
-		std::cout << "Predict----------------------------------"<< std::endl;			
-		int ret = va_batch(handle, imgs, batch_size, result);
-		//int ret = va_batch(handle, imgs_device, batch_size, result);
-		t2 = msecond();
-		printf("va_teat info:va_batch time: %.2f\n", (t2 - t1));	
-		t3 += t2-t1;
-		
-		std::cout << "output----------------------------------"<< std::endl;
-		
-		for (int b = 0; b < batch_size; b++)
-		{				
-			if(param.vehicle_detect_config==SY_CONFIG_CLOSE)//不做车头检测时，应设result[b].count=1，即输入是车头图像，只含1辆车。
-				result[b].count=1;
-				
-			//oFile << file << ","<< result[b].count<< "," <<endl;;	
-			std::cout <<"car_count:" <<result[b].count<< std::endl;			
-			for(int c=0;c<result[b].count;c++)
-			{					
-				//temp，中间结果，输出车牌被置黑的车小图
-				//if(0)
-				//{
-				//	cv::Mat tmp(result[b].info[c].car_img_data_cpu[0].h_, result[b].info[c].car_img_data_cpu[0].w_, CV_8UC3, result[b].info[c].car_img_data_cpu[0].data_);
-				//	char str_i[100];
-				//	sprintf(str_i, "%d_",  c);
-				//	cv::imwrite((save_folder_roi+str_i+i).c_str(),tmp);
-				//}
-				
-				
-				std::string str_vehicle_type;
-				int vehicle_type=result[b].info[c].type;	
-				//std::cout << "vehicle_type="<<vehicle_type<< std::endl;					
-				if (vehicle_type==0)str_vehicle_type = "head";
-				else if (vehicle_type==1)str_vehicle_type = "rear";
-				else if (vehicle_type==2)str_vehicle_type = "motor";					
-				else if (vehicle_type==3)str_vehicle_type = "tricycle";
-				else if (vehicle_type==4)str_vehicle_type = "body";
-				else if (vehicle_type==5)str_vehicle_type = "body_nova";
-				std::cout << "		vehicle_type:"<<str_vehicle_type<< std::endl;
-					
-				//1.车头结果：蓝框//2.车窗结果：绿框
-				if(param.vehicle_detect_config==SY_CONFIG_OPEN)
-				{	
-					//车身
-					//std::cout << "vehicle_body_detect_res info:"<< std::endl;
-					if(result[b].info[c].vehicle_body_detect_res.rect.width_>0)
-					{
-						float vehicle_body_detect_res_score = result[b].info[c].vehicle_body_detect_res.score;
-						int x1=result[b].info[c].vehicle_body_detect_res.rect.left_;
-						int y1=result[b].info[c].vehicle_body_detect_res.rect.top_;
-						int x2=result[b].info[c].vehicle_body_detect_res.rect.left_+result[b].info[c].vehicle_body_detect_res.rect.width_;
-						int y2=result[b].info[c].vehicle_body_detect_res.rect.top_+result[b].info[c].vehicle_body_detect_res.rect.height_;					
-						std::cout << "		    vehicle_body_detect_res_score:" <<vehicle_body_detect_res_score<<",car_rect:[" <<x1<<"," <<y1<<"," <<x2-x1<<"," <<y2-y1<<"]"<< std::endl;
-							
-						Point lt(x1, y1);
-						Point rb(x2, y2);
-						rectangle(cvImg, lt, rb, cv::Scalar(0, 255,255), 4);						
-					}	
-					
-					//车头
-					//std::cout << "vehicle_detect_res info:"<< std::endl;
-					if(result[b].info[c].vehicle_detect_res.rect.width_>0)	
-					{						
-						float vehicle_detect_res_score = result[b].info[c].vehicle_detect_res.score;
-						int x1=result[b].info[c].vehicle_detect_res.rect.left_;
-						int y1=result[b].info[c].vehicle_detect_res.rect.top_;
-						int x2=result[b].info[c].vehicle_detect_res.rect.left_+result[b].info[c].vehicle_detect_res.rect.width_;
-						int y2=result[b].info[c].vehicle_detect_res.rect.top_+result[b].info[c].vehicle_detect_res.rect.height_;										
-						std::cout << "		    vehicle_detect_res_score:" <<vehicle_detect_res_score<<",car_rect:[" <<x1<<"," <<y1<<"," <<x2-x1<<"," <<y2-y1<<"]"<< std::endl;
-							
-						Point lt(x1, y1);
-						Point rb(x2, y2);
-						rectangle(cvImg, lt, rb, cv::Scalar(255, 0, 0), 4);	
-					}
-					
-					//车窗
-					//std::cout << "vwd output----"<< std::endl;
-					if(result[b].info[c].vehicle_win_detect_res.rect.width_>0)
-					{
-						float vehicle_win_detect_res_score = result[b].info[c].vehicle_win_detect_res.score;
-						int x1=result[b].info[c].vehicle_win_detect_res.rect.left_;
-						int y1=result[b].info[c].vehicle_win_detect_res.rect.top_;
-						int x2=result[b].info[c].vehicle_win_detect_res.rect.left_+result[b].info[c].vehicle_win_detect_res.rect.width_;
-						int y2=result[b].info[c].vehicle_win_detect_res.rect.top_+result[b].info[c].vehicle_win_detect_res.rect.height_;					
-						std::cout << "		    vehicle_win_detect_res_score:" <<vehicle_win_detect_res_score<<",win_rect:[" <<x1<<"," <<y1<<"," <<x2-x1<<"," <<y2-y1<<"]"<< std::endl;
-							
-						Point lt(x1, y1);
-						Point rb(x2, y2);
-						rectangle(cvImg, lt, rb, cv::Scalar(0, 255, 0), 4);
-					}					
-				}
-		
-				
-				//3.车颜色
-				if(param.vehicle_color_config==SY_CONFIG_OPEN&& (vehicle_type==0 || vehicle_type==1 || vehicle_type==4))
-				{
-					//std::cout << "vc output----"<< std::endl;
-					int index=result[b].info[c].vehicle_color_res.index;
-					float score=result[b].info[c].vehicle_color_res.score;
-					
-					if(score>0.5)
-					{
-						std::cout << "		car color info:"<< endl;
-						std::cout << "		    index:"<< index<<" score:"<< score<< std::endl;
-						
-						std::string str_i = CARCOLOR1[index];
-						cv::putText(cvImg, str_i,
-							cv::Point(result[b].info[c].vehicle_body_detect_res.rect.left_+5, result[b].info[c].vehicle_body_detect_res.rect.top_+50),
-							cv::FONT_HERSHEY_COMPLEX_SMALL,
-							1.3,
-							cv::Scalar(0, 0, 255),
-							2);
-					}
-				}
-				
-				
-				//4.VR车型识别
-				if(param.vehicle_recg_config==SY_CONFIG_OPEN  && (vehicle_type==0 || vehicle_type==1 || vehicle_type==4 ))
-				{
-					//std::cout << "vr output----"<< std::endl;
-
-					char *vehicle_brand=result[b].info[c].vehicle_recg_res.vehicle_brand;//车辆品牌
-					char* vehicle_subbrand=result[b].info[c].vehicle_recg_res.vehicle_subbrand;             //车辆子品牌
-					char* vehicle_issue_year=result[b].info[c].vehicle_recg_res.vehicle_issue_year;           //车辆年款
-					char* vehicle_type_=result[b].info[c].vehicle_recg_res.vehicle_type;                //车辆类型
-					char* freight_ton=result[b].info[c].vehicle_recg_res.freight_ton;                  //货车吨级
-					float name_score=result[b].info[c].vehicle_recg_res.name_score;                   //识别置信度
-					
-					float name_score_thre = 0;
-					//if(vehicle_type==0)name_score_thre=0.7;//车头车型识别建议阈值0.7
-					//if(vehicle_type==1)name_score_thre=0.8;//车尾车型识别建议阈值0.8
-					if(name_score > name_score_thre)
-					{
-						cout << "		vehicle_recg info: " << endl;
-						std::cout << "			name_score: " << name_score << std::endl;
-						std::cout << "			vehicle_brand: " << vehicle_brand << std::endl;
-						std::cout << "			vehicle_subbrand: " << vehicle_subbrand << std::endl;
-						std::cout << "			vehicle_issue_year: " << vehicle_issue_year << std::endl;
-						std::cout << " 			vehicle_type_: " << vehicle_type_ << std::endl;
-						std::cout << "			freight_ton: " << freight_ton << std::endl;
-
-						//printf("name_score:%f\n", name_score);
-						//printf("vehicle_brand:%s\n", vehicle_brand);
-						//printf("vehicle_subbrand:%s\n", vehicle_subbrand);
-						//printf("vehicle_issue_year:%s\n", vehicle_issue_year);
-						//printf("vehicle_type_:%s\n", vehicle_type_);
-						//printf("freight_ton:%s\n", freight_ton);
-					}
-				
-				}
-				
-				
-				//5.VP车牌检测识别
-				if(param.vehicle_plate_det_recg_config==SY_CONFIG_OPEN  && (vehicle_type==0 || vehicle_type==1))
-				{
-					std::cout << "		car plate info:"<< endl;
-					int special_type=result[b].info[c].vehicle_plate_det_recg_res.special_type;//常规车牌、临时车牌、低速车牌。0-common,1-temporary_license_plate,2-low_speed_license_plate.
-					std::cout << "		    special_type:" << special_type<< std::endl;
-					
-					float detect_score=result[b].info[c].vehicle_plate_det_recg_res.detect_score;
-					//std::cout << "detect_score:" << detect_score<< std::endl;
-					if(detect_score>0.3)
-					{						
-						int type=result[b].info[c].vehicle_plate_det_recg_res.type;
-						sy_rect rect=result[b].info[c].vehicle_plate_det_recg_res.rect;
-						
-						int x1=rect.left_;
-						int y1=rect.top_;
-						int x2=rect.left_+rect.width_;
-						int y2=rect.top_+rect.height_;		
-						std::cout << "		    vp_type:"<<type<<",vp_det_score:" <<detect_score <<",vp_rect:[" <<x1<<"," <<y1<<"," <<x2-x1<<"," <<y2-y1<<"]"<< std::endl;													
-						
-						Point lt(x1, y1);
-						Point rb(x2, y2);
-						rectangle(cvImg, lt, rb, cv::Scalar(0, 0, 255), 4);
-							
-							
-						
-						//车牌识别结果
-						float num_score=result[b].info[c].vehicle_plate_det_recg_res.num_score;
-						std::string plate_recg="";
-						//if(num_score>0.99)//车牌识别建议置信度阈值0.99
-						{
-							
-							//printf("plate: ");
-							for (int m = 0; m < PLATENUM; m++)
-							{
-								//printf("%s", result[b].info[c].vehicle_plate_det_recg_res.recg[m].character);
-								plate_recg=plate_recg + result[b].info[c].vehicle_plate_det_recg_res.recg[m].character;
-							}
-							//printf("\n");
-							
-							//printf("maxprob: ");
-							//for (int m = 0; m < PLATENUM; m++)
-							//{
-							//	printf("%f ", result[b].info[c].vehicle_plate_det_recg_res.vehicle_plate_infos[0].recg[m].maxprob);
-							//}
-							//printf("\n");
-
-							
-							//std::cout << "type:" << type<<"  num_score:" <<num_score<<"  " << std::endl;
-							std::cout <<"		    "<<plate_recg<< ",vp_num_score:" << num_score<< std::endl;
-								
-						}
-						
-						
-						char str_cc[100];
-						memset(str_cc, 0, sizeof(str_cc));
-						cv::Point2f p1;
-						p1.x = x1;
-						p1.y = y1-60;
-						//sprintf(str_cc, "det_%.2f_recg_%.2f_%s",detectScore,numScore,plate_recg.c_str()); 
-						sprintf(str_cc, "det_%.2f",detect_score); 
-						cv::putText(cvImg, str_cc, 
-						  p1,
-						  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						  1.3,
-						  cv::Scalar(0, 0, 255),
-						  2);
-						  
-						memset(str_cc, 0, sizeof(str_cc));
-						p1.x = x1;
-						p1.y = y1-30;
-						sprintf(str_cc, "recg_%.2f",num_score); 
-						cv::putText(cvImg, str_cc, 
-						  p1,
-						  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						  1.3,
-						  cv::Scalar(0, 0, 255),
-						  2);
-						 
-						memset(str_cc, 0, sizeof(str_cc));
-						p1.x = x1;
-						p1.y = y1;
-						sprintf(str_cc, "%s",plate_recg.c_str()); 
-						cv::putText(cvImg, str_cc, 
-						  p1,
-						  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						  1.3,
-						  cv::Scalar(0, 0, 255),
-						  2);
-
-					}
-					
-				}
-				
-				//6.车属性结果：
-				if(param.vehicle_pendant_det_config==SY_CONFIG_OPEN && (vehicle_type==0|| vehicle_type==4))
-				{
-					std::cout << "		vehicle_pendant_det_res info:"<< endl;
-					int vpd_num = result[b].info[c].vehicle_pendant_det_res.count;
-					//std::cout << vpd_num<< std::endl;
-					std::cout << "		    vpd_num:"<<vpd_num<< endl;
-					for(int p=0; p<vpd_num; p++)
-					{
-						int index = result[b].info[c].vehicle_pendant_det_res.vpd_res[p].index;
-						float detect_score = result[b].info[c].vehicle_pendant_det_res.vpd_res[p].confidence;
-						int driver_copilot_info = result[b].info[c].vehicle_pendant_det_res.vpd_res[p].driver_copilot_info;
-						int x1=result[b].info[c].vehicle_pendant_det_res.vpd_res[p].rect.left_;
-						int y1=result[b].info[c].vehicle_pendant_det_res.vpd_res[p].rect.top_;
-						int x2=result[b].info[c].vehicle_pendant_det_res.vpd_res[p].rect.left_+result[b].info[c].vehicle_pendant_det_res.vpd_res[p].rect.width_;
-						int y2=result[b].info[c].vehicle_pendant_det_res.vpd_res[p].rect.top_+result[b].info[c].vehicle_pendant_det_res.vpd_res[p].rect.height_;					
-		
-						//std::cout <<p<<" ["<<x1<<" "<<y1<<" "<<x2-x1<<" "<<y2-y1<<"] "<<detectScore<<" "<<index<<" "<<driver_copilot_info<< std::endl;
-						std::cout << "		    vpd id:"<<p<<" index:"<<index<<",vpd_det_score:" <<detect_score <<",vpd_rect:[" <<x1<<"," <<y1<<"," <<x2-x1<<"," <<y2-y1<<"]"<<" driver_copilot_info:"<<driver_copilot_info<< std::endl;
-							
-						
-						Point lt(x1, y1);
-						Point rb(x2, y2);
-						rectangle(cvImg, lt, rb, cv::Scalar(255, 255, 0), 4);
-						
-						//车属性人脸特征
-						//f(index ==1)//人脸
-						//{
-						//	std::cout << "		    vpd face feature:[";
-						//	/*for(int f=0;f<VPD_FACE_FEATURESIZE;f++)
-						//	{
-						//		float fea = result[b].info[c].vehicle_pendant_det_res.vpd_res[p].feature[f];
-						//		//std::cout << "feature "<<f<<":"<<fea<<std::endl; 
-						//		std::cout <<fea<< " ";
-						//	}*/
-						//	std::cout << "]"<< std::endl;
-						//	//std::cout << "face feature:"<<result[b].info[c].vehicle_pendant_det_res.vpd_res[p].feature[0]<<" "<<result[b].info[c].vehicle_pendant_det_res.vpd_res[p].feature[1]<<" "<<result[b].info[c].vehicle_pendant_det_res.vpd_res[p].feature[2]<<std::endl; 
-						//}						
-					}
-				}
-				
-				//7.VID车违规结果-----------
-				if(param.vehicle_illegal_config==SY_CONFIG_OPEN  && vehicle_type==0)
-				{		
-					std::cout << "		vehicle_illegal_det_res info:"<< endl;
-					vid_result cur_result = result[b].info[c].vehicle_illegal_det_res;
-					//副驾驶copilot
-					{
-						//有人没人判断，阈值0.6
-						std::string str_person="UNCERTAINTY";
-						if(cur_result.copilot.person.status==SOMEBODY)
-							str_person ="PERSON";
-						else if(cur_result.copilot.person.status==NOBODY)
-							str_person ="NOPERSON";				
-						//cv::putText(batch_mat[b], str_person, 
-						//	  cv::Point(5, 25),
-						//	  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						//	  1.3,
-						//	  cv::Scalar(255, 0, 0),
-						//	  2);
-						
-						//打电话，阈值0.9
-						std::string str_call="UNCERTAINTY";
-						if(cur_result.copilot.call.status==lEGAL)
-							str_call ="lEGAL";//str_call ="NOCALL";
-						else if(cur_result.copilot.call.status==ILLEGAL)
-							str_call ="ILLEGAL";//str_call ="CALL";
-						//cv::putText(batch_mat[b], str_call, 
-						//	  cv::Point(5, 50),
-						//	  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						//	  1.3,
-						//	  cv::Scalar(255, 0, 0),
-						//	  2);
-							  
-						//使用电话、阈值0.89
-						std::string str_phone="UNCERTAINTY";
-						if(cur_result.copilot.phone.status==lEGAL)
-							str_phone ="lEGAL";//str_phone ="NOPHONE";
-						else if(cur_result.copilot.phone.status==ILLEGAL)
-							str_phone ="ILLEGAL";//str_phone ="USEPHONE";
-						//cv::putText(batch_mat[b], str_phone, 
-						//	  cv::Point(5, 75),
-						//	  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						//	  1.3,
-						//	  cv::Scalar(255, 0, 0),
-						//	  2);
-						
-						//系安全带，阈值0.5
-						std::string str_belt="UNCERTAINTY";
-						if(cur_result.copilot.belt.status==lEGAL)
-							str_belt ="lEGAL";//str_belt ="SAFETYBELT";
-						else if(cur_result.copilot.belt.status==ILLEGAL)
-							str_belt ="ILLEGAL";
-
-						//cv::putText(batch_mat[b], str_belt, 
-						//	  cv::Point(5, 75),
-						//	  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						//	  1.3,
-						//	  cv::Scalar(255, 0, 0),
-						//	  2);
-							  
-						//抽烟，阈值0.9
-						std::string str_smoke="UNCERTAINTY";
-						if(cur_result.copilot.smoke.status==ILLEGAL)
-							str_smoke ="ILLEGAL";//str_smoke ="SMOKE";
-						else if(cur_result.copilot.smoke.status==lEGAL)
-							str_smoke ="lEGAL";//str_smoke ="NOSMOKE";
-						//cv::putText(batch_mat[b], str_smoke, 
-						//	  cv::Point(5, 100),
-						//	  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						//	  1.3,
-						//	  cv::Scalar(255, 0, 0),
-						//	  2);
-
-						//std::cout << "copilot: "<<str_person<< " "<<str_call<< " "<<str_phone<< " "<<str_belt<< " "<<str_smoke<< std::endl;						
-						//std::cout << "copilot confidence: "<<cur_result.copilot.person.confidence<< " "<<cur_result.copilot.call.confidence<< " "<<cur_result.copilot.phone.confidence<< " "<<cur_result.copilot.belt.confidence<< " "<<cur_result.copilot.smoke.confidence<< std::endl;
-					    std::cout << "		    copilot:  "<<"person:"<<str_person<< " call:"<<str_call<< " phone:"<<str_phone<< " belt:"<<str_belt<< " smoke:"<<str_smoke<< std::endl;						
-					    std::cout << "		    copilot confidence:  "<<"person:"<<cur_result.copilot.person.confidence<< " call:"<<cur_result.copilot.call.confidence<< " phone:"<<cur_result.copilot.phone.confidence<< " belt:"<<cur_result.copilot.belt.confidence<< " smoke:"<<cur_result.copilot.smoke.confidence<< std::endl;
-						
-					}
-					
-					//驾驶driver
-					{
-						//有人没人判断，阈值0.6
-						std::string str_person="UNCERTAINTY";
-						if(cur_result.driver.person.status==SOMEBODY)
-							str_person ="PERSON";
-						else if(cur_result.driver.person.status==NOBODY)
-							str_person ="NOPERSON";				
-						//cv::putText(batch_mat[b], str_person, 
-						//	  cv::Point(5, 150),
-						//	  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						//	  1.3,
-						//	  cv::Scalar(255, 0, 0),
-						//	  2);
-						
-						//打电话，阈值0.9
-						std::string str_call="UNCERTAINTY";
-						if(cur_result.driver.call.status==lEGAL)
-							str_call ="lEGAL";//str_call ="NOCALL";
-						else if(cur_result.driver.call.status==ILLEGAL)
-							str_call ="ILLEGAL";//str_call ="CALL";
-						//cv::putText(batch_mat[b], str_call, 
-						//	  cv::Point(5, 175),
-						//	  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						//	  1.3,
-						//	  cv::Scalar(255, 0, 0),
-						//	  2);
-							  
-						//使用电话，阈值0.89
-						std::string str_phone="UNCERTAINTY";
-						if(cur_result.driver.phone.status==lEGAL)
-							str_phone ="lEGAL";//str_phone ="NOPHONE";
-						else if(cur_result.driver.phone.status==ILLEGAL)
-							str_phone ="ILLEGAL";//str_phone ="USEPHONE";
-						//cv::putText(batch_mat[b], str_phone, 
-						//	  cv::Point(5, 200),
-						//	  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						//	  1.3,
-						//	  cv::Scalar(255, 0, 0),
-						//	  2);
-						
-						//系安全带，阈值0.5
-						std::string str_belt="UNCERTAINTY";
-						if(cur_result.driver.belt.status==lEGAL)
-							str_belt ="lEGAL";//str_belt ="SAFETYBELT";
-						else if(cur_result.driver.belt.status==ILLEGAL)
-							str_belt ="ILLEGAL";//str_belt ="NOSAFETYBELT";
-
-						//cv::putText(batch_mat[b], str_belt, 
-						//	  cv::Point(5, 200),
-						//	  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						//	  1.3,
-						//	  cv::Scalar(255, 0, 0),
-						//	  2);
-							  
-						//抽烟，阈值0.9
-						std::string str_smoke="UNCERTAINTY";
-						if(cur_result.driver.smoke.status==ILLEGAL)
-							str_smoke ="ILLEGAL";//str_smoke ="SMOKE";
-						else if(cur_result.driver.smoke.status==lEGAL)
-							str_smoke ="lEGAL";//str_smoke ="NOSMOKE";
-						//cv::putText(batch_mat[b], str_smoke, 
-						//	  cv::Point(5, 225),
-						//	  cv::FONT_HERSHEY_COMPLEX_SMALL,
-						//	  1.3,
-						//	  cv::Scalar(255, 0, 0),
-						//	  2);
-						
-						//std::cout << "driver: "<<str_person<< " "<<str_call<< " "<<str_phone<< " "<<str_belt<< " "<<str_smoke<< std::endl;
-						//std::cout << "driver confidence: "<<cur_result.driver.person.confidence<< " "<<cur_result.driver.call.confidence<< " "<<cur_result.driver.phone.confidence<< " "<<cur_result.driver.belt.confidence<< " "<<cur_result.driver.smoke.confidence<< std::endl;
-					     std::cout << "		    driver:  person:"<<str_person<< " call:"<<str_call<< " phone:"<<str_phone<< " belt:"<<str_belt<< " smoke:"<<str_smoke<< std::endl;
-						std::cout << "		    driver confidence:  person:"<<cur_result.driver.person.confidence<< " call:"<<cur_result.driver.call.confidence<< " phone:"<<cur_result.driver.phone.confidence<< " belt:"<<cur_result.driver.belt.confidence<< " smoke:"<<cur_result.driver.smoke.confidence<< std::endl;
-						
-					}				
-				}
-				
-				
-				
-				
-				//8.车特征
-				if(param.vehicle_feature_config==SY_CONFIG_OPEN && (vehicle_type==0 || vehicle_type==1))
-				{
-					std::cout << "		vehicle_fea_res info: "<<std::endl;
-					std::cout << "		    [";	
-					for(int f=0;f<VA_FEATURESIZE;f++)
-					{
-						float fea=result[b].info[c].vehicle_fea_res.feature[f];
-						//std::cout << "feature "<<f<<":"<<fea<<std::endl; 
-						std::cout <<fea<<" ";
-					}
-					std::cout <<"]"<<std::endl;
-					//std::cout << "feature 0 :"<<result[b].info[c].vehicle_fea_res.feature[0]<<std::endl; 
-					//std::cout << "feature 1 :"<<result[b].info[c].vehicle_fea_res.feature[1]<<std::endl; 
-					//std::cout << "feature 2 :"<<result[b].info[c].vehicle_fea_res.feature[2]<<std::endl; 
-					//std::cout << "feature 3 :"<<result[b].info[c].vehicle_fea_res.feature[3]<<std::endl; 
-					//std::cout << "feature 4 :"<<result[b].info[c].vehicle_fea_res.feature[4]<<std::endl; 
-					//std::cout << "feature 5 :"<<result[b].info[c].vehicle_fea_res.feature[5]<<std::endl; 
-					
-					//test
-					//for(int f=0;f<10;f++)
-					//{
-					//	float fea=result[b].info[c].vehicle_fea_res.feature[f];
-					//	std::cout << "feature "<<f<<":"<<fea<<std::endl; 
-					//}
-				}
-
-				//11.摩托车三轮车分析
-				 if(param.vehicle_motor_tricycle_analysis_config==SY_CONFIG_OPEN && (vehicle_type==2 || vehicle_type==3))
-				 {
-					 //std::cout << "mta output----"<< std::endl;
-					 
-					 if(vehicle_type==2)//摩托车
-					 {
-						//摩托车载人
-						//int status=result[b].info[c].mta_res.motor_manned.status;	
-						//float score=result[b].info[c].mta_res.motor_manned.confidence;
-						//if(status == MOTOR_MANNED)
-						//	std::cout << "motor info: MOTOR_MANNED, prob: " << score << std::endl;
-						//else if(status == MOTOR_NOT_MANNED)
-						//	std::cout << "motor info: MOTOR_NOT_MANNED, prob: " << score << std::endl;
-						
-						//摩托车驾驶人是否戴安全帽
-						int status=result[b].info[c].mta_res.motor_driver_helmeted.status;
-						float score=result[b].info[c].mta_res.motor_driver_helmeted.confidence;
-						if(status == MOTOR_DRIVER_HELMETED)
-							std::cout << "		    motor info: MOTOR_DRIVER_HELMETED, prob: " << score << std::endl;
-						else if(status == MOTOR_DRIVER_NOT_HELMETED)
-							std::cout << "		    motor info: MOTOR_DRIVER_NOT_HELMETED, prob: " << score << std::endl;	
-						
-					 }
-				 }
-							 //载人输出
-				//if(param.vehicle_manned_config==SY_CONFIG_OPEN && (vehicle_type==0 || vehicle_type==1 || vehicle_type==3))
-				if(param.vehicle_manned_config==SY_CONFIG_OPEN && vehicle_type!=5)
-				{
-					std::cout << "----------------------manned output----"<< std::endl;
-					int hs_count = result[b].info[c].manned_res.hs_count;
-					std::cout <<"manned_hs_count:"<< hs_count << std::endl;
-					for(int lo=0;lo<hs_count;lo++)
-					{
-						int x1=result[b].info[c].manned_res.hs_rect[lo].rect.left_;
-						int y1=result[b].info[c].manned_res.hs_rect[lo].rect.top_;
-						int x2=result[b].info[c].manned_res.hs_rect[lo].rect.left_+result[b].info[c].manned_res.hs_rect[lo].rect.width_;
-						int y2=result[b].info[c].manned_res.hs_rect[lo].rect.top_+result[b].info[c].manned_res.hs_rect[lo].rect.height_;					
-
-						std::cout <<"manned_hs_rect:"<< x1 <<" "<< y1<<" " <<x2<<"  " << y2<< std::endl;
-						
-						Point lt(x1, y1);
-						Point rb(x2, y2);
-						rectangle(cvImg, lt, rb, cv::Scalar(0, 255, 255), 4);
-					}						
-				}				
-			}
-
-			//测试相似度比对函数，batch_size设为2
-			//double similarity=va_compute_similarity(result[0].info[0].vehicle_fea_res.feature, result[1].info[0].vehicle_fea_res.feature, FEATURESIZE);
-			//std::cout << "similarity: "<<similarity<<std::endl; 
-			
-			
-			
-			//cv::Mat showImg;
-			//showImg=batch_mat[b].clone();
-			//cv::resize(batch_mat[b], showImg, cv::Size(batch_mat[b].cols/2,batch_mat[b].rows/2));
-			//cv::imshow("image", showImg);
-			//cv::waitKey(0);			
-			cv::imwrite((saveimagepath+file).c_str(),cvImg);
-													 
-		}
-		
-
-			
-
-
-		
-		//delete result
-		for(int b=0;b<batch_size;b++)
-		{
-			for(int c=0; c<100; c++)
-			{
-				if(result[b].info[c].vehicle_pendant_det_res.vpd_res!=NULL)
-					delete[] result[b].info[c].vehicle_pendant_det_res.vpd_res;
-				
-			}
-			if(result[b].info!=NULL)
-			   delete[] result[b].info;
-		}
-		if(result!=NULL)
-			   delete[] result;
-
-	} 
-}
-	
-	std::cout << "va_release---------------------"<< std::endl;
-    va_release(&handle);
-	//va_release(&handle111);
-	va_acl_release();
- 
-	printf("va_teat info:va_batch time: t3=%.2f\n", t3/count);
-	
-	//oFile.close();
-		
-    return 0;
-}
@@ -10,8 +10,7 @@ int main() {
     VillageParam param;
     param.dev_id = 0;
-    param.db_path = "";
-    param.model_path = "";
+    param.sdk_path = ".";
     int ret = village_pic_init(&vaHandle, param);
     vector<string> vec_path;
@@ -5,10 +5,13 @@
 #include <vector>
 #include "vehicle_analysis.h"
+#include "opencv2/opencv.hpp"
+#include "opencv2/imgcodecs/legacy/constants_c.h"
+#include "opencv2/imgproc/types_c.h"
+
 struct VillageParam {
     int dev_id;
-    std::string db_path;
-    std::string model_path;
+    std::string sdk_path;
 };
 typedef struct pendant_info
@@ -57,12 +60,12 @@ typedef struct VehicleInfo {
 struct LineInfo{
     int line_type;
-    std::vector<sy_point> vec_pt;
+    std::vector<cv::Point> vec_pt;
 };
 struct SegInfo {
     int seg_type;
-    std::vector<sy_point> vec_pt;
+    std::vector<cv::Point> vec_pt;
 };
 typedef struct AnalysisResult {