update.

algorithm/common_det/cuda/common_det_cuda_impl.cpp

@@ -103,7 +103,7 @@ void infer_seg(IExecutionContext& context, cudaStream_t& stream, void **buffers,
   CUDA_CHECK(cudaMemcpyAsync(output2, buffers[2], batchSize * kOutputSize2 * sizeof(float), cudaMemcpyDeviceToHost, stream));
   cudaStreamSynchronize(stream);
 }
-void CommonObjectDetectorCUDAImpl::_prepare_buffers(int input_h, int input_w, int batchsize) {
+void CommonObjectDetectorCUDAImpl::_prepare_buffers(int input_h, int input_w) {
   assert(this->_engine->getNbBindings() == 2);
   // In order to bind the buffers, we need to know the names of the input and output tensors.
   // Note that indices are guaranteed to be less than IEngine::getNbBindings()
@@ -112,12 +112,12 @@ void CommonObjectDetectorCUDAImpl::_prepare_buffers(int input_h, int input_w, in
   assert(inputIndex == 0);
   assert(outputIndex == 1);
   // Create GPU buffers on device
-  CUDA_CHECK(cudaMalloc((void**)&(this->_gpu_buffers[0]), batchsize * 3 * input_h * input_w * sizeof(float)));
+  CUDA_CHECK(cudaMalloc((void**)&(this->_gpu_buffers[0]), kBatchSize * 3 * input_h * input_w * sizeof(float)));
-  CUDA_CHECK(cudaMalloc((void**)&(this->_gpu_buffers[1]), batchsize * kOutputSize * sizeof(float)));
+  CUDA_CHECK(cudaMalloc((void**)&(this->_gpu_buffers[1]), kBatchSize * kOutputSize * sizeof(float)));
 
-  this->_cpu_output_buffer = new float[batchsize * kOutputSize];
+  this->_cpu_output_buffer = new float[kBatchSize * kOutputSize];
 }
-void CommonObjectDetectorCUDAImpl::_prepare_buffers_seg(int input_h, int input_w, int batchsize) {
+void CommonObjectDetectorCUDAImpl::_prepare_buffers_seg(int input_h, int input_w) {
   assert(this->_engine->getNbBindings() == 3);
   // In order to bind the buffers, we need to know the names of the input and output tensors.
   // Note that indices are guaranteed to be less than IEngine::getNbBindings()
@@ -129,13 +129,13 @@ void CommonObjectDetectorCUDAImpl::_prepare_buffers_seg(int input_h, int input_w
   assert(outputIndex2 == 2);
 
   // Create GPU buffers on device
-  CUDA_CHECK(cudaMalloc((void**)&(this->_gpu_buffers[0]), batchsize * 3 * input_h * input_w * sizeof(float)));
+  CUDA_CHECK(cudaMalloc((void**)&(this->_gpu_buffers[0]), kBatchSize * 3 * input_h * input_w * sizeof(float)));
-  CUDA_CHECK(cudaMalloc((void**)&(this->_gpu_buffers[1]), batchsize * kOutputSize1 * sizeof(float)));
+  CUDA_CHECK(cudaMalloc((void**)&(this->_gpu_buffers[1]), kBatchSize * kOutputSize1 * sizeof(float)));
-  CUDA_CHECK(cudaMalloc((void**)&(this->_gpu_buffers[2]), batchsize * kOutputSize2 * sizeof(float)));
+  CUDA_CHECK(cudaMalloc((void**)&(this->_gpu_buffers[2]), kBatchSize * kOutputSize2 * sizeof(float)));
 
   // Alloc CPU buffers
-  this->_cpu_output_buffer1 = new float[batchsize * kOutputSize1];
+  this->_cpu_output_buffer1 = new float[kBatchSize * kOutputSize1];
-  this->_cpu_output_buffer2 = new float[batchsize * kOutputSize2];
+  this->_cpu_output_buffer2 = new float[kBatchSize * kOutputSize2];
 }
 void deserialize_engine(std::string& engine_name, IRuntime** runtime, ICudaEngine** engine, IExecutionContext** context) {
   std::ifstream file(engine_name, std::ios::binary);
@@ -172,8 +172,7 @@ void CommonObjectDetectorCUDAImpl::cudaDetect(
   std::vector<float>& boxes_h_,
   std::vector<int>& boxes_label_,
   std::vector<float>& boxes_score_,
-  std::vector<cv::Mat>& boxes_seg_,
+  std::vector<cv::Mat>& boxes_seg_
-  bool input_4k_
 )
 {
 #ifdef WITH_CUDA
@@ -184,51 +183,9 @@ void CommonObjectDetectorCUDAImpl::cudaDetect(
   double thrs_nms = base_->getThrsNms();
 
   std::vector<cv::Mat> img_batch;
-  if (input_4k_)
+  img_batch.push_back(img_);
-  {
+  // Preprocess
-    if (img_.cols == 3840 && img_.rows == 2160)
+  cuda_batch_preprocess(img_batch, this->_gpu_buffers[0], input_w, input_h, this->_stream);
-    {
-      cv::Mat patch1, patch2, patch3, patch4, patch5, patch6;
-      
-      img_.colRange(200, 1480).rowRange(0, 1280).copyTo(patch1);
-      img_.colRange(1280, 2560).rowRange(0, 1280).copyTo(patch2);
-      img_.colRange(2360, 3640).rowRange(0, 1280).copyTo(patch3);
-      
-      img_.colRange(200, 1480).rowRange(880, 2160).copyTo(patch4);
-      img_.colRange(1280, 2560).rowRange(880, 2160).copyTo(patch5);
-      img_.colRange(2360, 3640).rowRange(880, 2160).copyTo(patch6);
-      
-      img_batch.push_back(patch1);
-      img_batch.push_back(patch2);
-      img_batch.push_back(patch3);
-      img_batch.push_back(patch4);
-      img_batch.push_back(patch5);
-      img_batch.push_back(patch6);
-    }
-    else
-    {
-      throw std::runtime_error("SpireCV (106) Input image is NOT 4K (3840 x 2160)!");
-    }
-    if (with_segmentation)
-    {
-      throw std::runtime_error("SpireCV (106) Resolution 4K DO NOT Support Segmentation!");
-    }
-  }
-  else
-  {
-    img_batch.push_back(img_);
-  }
-  
-  if (input_4k_)
-  {
-    // Preprocess
-    cuda_batch_preprocess(img_batch, this->_gpu_buffers[0], 1280, 1280, this->_stream);
-  }
-  else
-  {
-    // Preprocess
-    cuda_batch_preprocess(img_batch, this->_gpu_buffers[0], input_w, input_h, this->_stream);
-  }
 
   // Run inference
   if (with_segmentation)
@@ -237,14 +194,7 @@ void CommonObjectDetectorCUDAImpl::cudaDetect(
   }
   else
   {
-    if (input_4k_)
+    infer(*this->_context, this->_stream, (void**)this->_gpu_buffers, this->_cpu_output_buffer, kBatchSize);
-    {
-      infer(*this->_context, this->_stream, (void**)this->_gpu_buffers, this->_cpu_output_buffer, 6);
-    }
-    else
-    {
-      infer(*this->_context, this->_stream, (void**)this->_gpu_buffers, this->_cpu_output_buffer, kBatchSize);
-    }
   }
 
   // NMS
@@ -258,102 +208,45 @@ void CommonObjectDetectorCUDAImpl::cudaDetect(
     batch_nms(res_batch, this->_cpu_output_buffer, img_batch.size(), kOutputSize, thrs_conf, thrs_nms);
   }
 
-
+  std::vector<Detection> res = res_batch[0];
-  if (input_4k_)
+  std::vector<cv::Mat> masks;
+  if (with_segmentation)
   {
-    for (size_t k = 0; k < res_batch.size(); k++)
+    masks = process_mask(&(this->_cpu_output_buffer2[0]), kOutputSize2, res, input_h, input_w);
-    {
+  }
-      std::vector<Detection> res = res_batch[k];
-      for (size_t j = 0; j < res.size(); j++)
-      {
-        cv::Rect r = get_rect(img_batch[k], res[j].bbox, 1280, 1280);
-        if (r.x < 0) r.x = 0;
-        if (r.y < 0) r.y = 0;
-        if (r.x + r.width >= 1280)  r.width = 1280 - r.x - 1;
-        if (r.y + r.height >= 1280) r.height = 1280 - r.y - 1;
-        if (r.width > 3 && r.height > 3)
-        {
-          if (0 == k)
-          {
-            boxes_x_.push_back(r.x + 200);
-            boxes_y_.push_back(r.y);
-          }
-          else if (1 == k)
-          {
-            boxes_x_.push_back(r.x + 1280);
-            boxes_y_.push_back(r.y);
-          }
-          else if (2 == k)
-          {
-            boxes_x_.push_back(r.x + 2360);
-            boxes_y_.push_back(r.y);
-          }
-          else if (3 == k)
-          {
-            boxes_x_.push_back(r.x + 200);
-            boxes_y_.push_back(r.y + 880);
-          }
-          else if (4 == k)
-          {
-            boxes_x_.push_back(r.x + 1280);
-            boxes_y_.push_back(r.y + 880);
-          }
-          else if (5 == k)
-          {
-            boxes_x_.push_back(r.x + 2360);
-            boxes_y_.push_back(r.y + 880);
-          }
-          boxes_w_.push_back(r.width);
-          boxes_h_.push_back(r.height);
 
-          boxes_label_.push_back((int)res[j].class_id);
+
-          boxes_score_.push_back(res[j].conf);
+
-        }
+  for (size_t j = 0; j < res.size(); j++) {
+    cv::Rect r = get_rect(img_, res[j].bbox, input_h, input_w);
+    if (r.x < 0) r.x = 0;
+    if (r.y < 0) r.y = 0;
+    if (r.x + r.width >= img_.cols)  r.width = img_.cols - r.x - 1;
+    if (r.y + r.height >= img_.rows) r.height = img_.rows - r.y - 1;
+    if (r.width > 5 && r.height > 5)
+    {
+      // cv::rectangle(img_show, r, cv::Scalar(0, 0, 255), 2);
+      // cv::putText(img_show, vehiclenames[(int)res[j].class_id], cv::Point(r.x, r.y - 1), cv::FONT_HERSHEY_PLAIN, 2.2, cv::Scalar(0, 0, 255), 2);
+      boxes_x_.push_back(r.x);
+      boxes_y_.push_back(r.y);
+      boxes_w_.push_back(r.width);
+      boxes_h_.push_back(r.height);
+
+      boxes_label_.push_back((int)res[j].class_id);
+      boxes_score_.push_back(res[j].conf);
+
+      if (with_segmentation)
+      {
+        cv::Mat mask_j = masks[j].clone();
+        boxes_seg_.push_back(mask_j);
       }
     }
   }
-  else
-  {
-
-    std::vector<Detection> res = res_batch[0];
-    std::vector<cv::Mat> masks;
-    if (with_segmentation)
-    {
-      masks = process_mask(&(this->_cpu_output_buffer2[0]), kOutputSize2, res, input_h, input_w);
-    }
-
-    for (size_t j = 0; j < res.size(); j++)
-    {
-      cv::Rect r = get_rect(img_, res[j].bbox, input_h, input_w);
-      if (r.x < 0) r.x = 0;
-      if (r.y < 0) r.y = 0;
-      if (r.x + r.width >= img_.cols)  r.width = img_.cols - r.x - 1;
-      if (r.y + r.height >= img_.rows) r.height = img_.rows - r.y - 1;
-      if (r.width > 5 && r.height > 5)
-      {
-        // cv::rectangle(img_show, r, cv::Scalar(0, 0, 255), 2);
-        // cv::putText(img_show, vehiclenames[(int)res[j].class_id], cv::Point(r.x, r.y - 1), cv::FONT_HERSHEY_PLAIN, 2.2, cv::Scalar(0, 0, 255), 2);
-        boxes_x_.push_back(r.x);
-        boxes_y_.push_back(r.y);
-        boxes_w_.push_back(r.width);
-        boxes_h_.push_back(r.height);
-
-        boxes_label_.push_back((int)res[j].class_id);
-        boxes_score_.push_back(res[j].conf);
-
-        if (with_segmentation)
-        {
-          cv::Mat mask_j = masks[j].clone();
-          boxes_seg_.push_back(mask_j);
-        }
-      }
-    }
   
-  }
 #endif
 }
 
-bool CommonObjectDetectorCUDAImpl::cudaSetup(CommonObjectDetectorBase* base_, bool input_4k_)
+bool CommonObjectDetectorCUDAImpl::cudaSetup(CommonObjectDetectorBase* base_)
 {
 #ifdef WITH_CUDA
   std::string dataset = base_->getDataset();
@@ -379,11 +272,6 @@ bool CommonObjectDetectorCUDAImpl::cudaSetup(CommonObjectDetectorBase* base_, bo
   {
     throw std::runtime_error("SpireCV (104) Error loading the CommonObject TensorRT model (File Not Exist)");
   }
-  
-  if (input_4k_ && with_segmentation)
-  {
-    throw std::runtime_error("SpireCV (106) Resolution 4K DO NOT Support Segmentation!");
-  }
 
   deserialize_engine(engine_fn, &this->_runtime, &this->_engine, &this->_context);
   CUDA_CHECK(cudaStreamCreate(&this->_stream));
@@ -394,20 +282,12 @@ bool CommonObjectDetectorCUDAImpl::cudaSetup(CommonObjectDetectorBase* base_, bo
   if (with_segmentation)
   {
     // Prepare cpu and gpu buffers
-    this->_prepare_buffers_seg(input_h, input_w, 1);
+    this->_prepare_buffers_seg(input_h, input_w);
   }
   else
   {
-    if (input_4k_)
+    // Prepare cpu and gpu buffers
-    {
+    this->_prepare_buffers(input_h, input_w);
-      // Prepare cpu and gpu buffers
-      this->_prepare_buffers(input_h, input_w, 6);
-    }
-    else
-    {
-      // Prepare cpu and gpu buffers
-      this->_prepare_buffers(input_h, input_w, 1);
-    }
   }
   return true;
 #endif

algorithm/common_det/cuda/common_det_cuda_impl.h

@@ -26,7 +26,7 @@ public:
   CommonObjectDetectorCUDAImpl();
   ~CommonObjectDetectorCUDAImpl();
 
-  bool cudaSetup(CommonObjectDetectorBase* base_, bool input_4k_);
+  bool cudaSetup(CommonObjectDetectorBase* base_);
   void cudaDetect(
     CommonObjectDetectorBase* base_,
     cv::Mat img_,
@@ -36,13 +36,12 @@ public:
     std::vector<float>& boxes_h_,
     std::vector<int>& boxes_label_,
     std::vector<float>& boxes_score_,
-    std::vector<cv::Mat>& boxes_seg_,
+    std::vector<cv::Mat>& boxes_seg_
-    bool input_4k_
   );
 
 #ifdef WITH_CUDA
-  void _prepare_buffers_seg(int input_h, int input_w, int batchsize);
+  void _prepare_buffers_seg(int input_h, int input_w);
-  void _prepare_buffers(int input_h, int input_w, int batchsize);
+  void _prepare_buffers(int input_h, int input_w);
   nvinfer1::IExecutionContext* _context;
   nvinfer1::IRuntime* _runtime;
   nvinfer1::ICudaEngine* _engine;

algorithm/common_det/sv_common_det.cpp

@@ -12,9 +12,8 @@
 namespace sv {
 
 
-CommonObjectDetector::CommonObjectDetector(bool input_4k)
+CommonObjectDetector::CommonObjectDetector()
 {
-  this->_input_4k = input_4k;
 #ifdef WITH_CUDA
   this->_cuda_impl = new CommonObjectDetectorCUDAImpl;
 #endif
@@ -26,7 +25,7 @@ CommonObjectDetector::~CommonObjectDetector()
 bool CommonObjectDetector::setupImpl()
 {
 #ifdef WITH_CUDA
-  return this->_cuda_impl->cudaSetup(this, this->_input_4k);
+  return this->_cuda_impl->cudaSetup(this);
 #endif
   return false;
 }
@@ -52,8 +51,7 @@ void CommonObjectDetector::detectImpl(
     boxes_h_,
     boxes_label_,
     boxes_score_,
-    boxes_seg_,
+    boxes_seg_
-    this->_input_4k
   );
 #endif
 }

algorithm/sot/ocv470/sot_ocv470_impl.cpp

@@ -39,8 +39,8 @@ bool SingleObjectTrackerOCV470Impl::ocv470Setup(SingleObjectTrackerBase* base_)
     TrackerNano::Params nano_params;
     nano_params.backbone = samples::findFile(backbone);
     nano_params.neckhead = samples::findFile(neckhead);
-    nano_params.backend = this->_backend;
+    nano_params.backend = cv::dnn::DNN_BACKEND_CUDA;
-    nano_params.target = this->_target;
+    nano_params.target = cv::dnn::DNN_TARGET_CUDA;
 
     _nano = TrackerNano::create(nano_params);
   }

include/sv_algorithm_base.h

@@ -104,6 +104,10 @@ public:
   std::string getAlgorithm();
   int getBackend();
   int getTarget();
+  double getObjectWs();
+  double getObjectHs();
+  int useWidthOrHeight();
+
 protected:
   virtual bool setupImpl();
   virtual void initImpl(cv::Mat img_, const cv::Rect& bounding_box_);
@@ -113,6 +117,9 @@ protected:
   std::string _algorithm;
   int _backend;
   int _target;
+  int _use_width_or_height;
+  double _object_ws;
+  double _object_hs;
 };
 
 
@@ -170,3 +177,4 @@ protected:
 
 }
 #endif
+

include/sv_common_det.h

@@ -16,7 +16,7 @@ class CommonObjectDetectorCUDAImpl;
 class CommonObjectDetector : public CommonObjectDetectorBase
 {
 public:
-  CommonObjectDetector(bool input_4k=false);
+  CommonObjectDetector();
   ~CommonObjectDetector();
 protected:
   bool setupImpl();
@@ -32,7 +32,6 @@ protected:
   );
 
   CommonObjectDetectorCUDAImpl* _cuda_impl;
-  bool _input_4k;
 };
 
 

include/sv_video_base.h

@@ -12,6 +12,9 @@
 #include <arpa/inet.h>
 #include <netinet/in.h>  // for sockaddr_in
 
+#include <mutex>
+#include <condition_variable>
+
 #define SV_RAD2DEG 57.2957795
 // #define X86_PLATFORM
 // #define JETSON_PLATFORM
@@ -358,7 +361,15 @@ protected:
   void _run();
 
   bool _is_running;
+
+// new mutex
+  std::mutex _frame_mutex;
+  std::condition_variable_any _frame_empty;
+
+//old flag
   bool _is_updated;
+
+
   std::thread _tt;
   cv::VideoCapture _cap;
   cv::Mat _frame;
@@ -377,6 +388,21 @@ protected:
   double _exposure;
 };
 
+void drawTargetsInFrame(
+  cv::Mat& img_,
+  const TargetsInFrame& tgts_,
+  int aruco_track_id,
+  bool with_all=true,
+  bool with_category=false,
+  bool with_tid=false,
+  bool with_seg=false,
+  bool with_box=false,
+  bool with_ell=false,
+  bool with_aruco=false,
+  bool with_yaw=false
+);
+
+
 
 void drawTargetsInFrame(
   cv::Mat& img_,
@@ -397,3 +423,4 @@ void list_dir(std::string dir, std::vector<std::string>& files, std::string suff
 
 }
 #endif
+

params/a-params/sv_algorithm_params.json

@@ -1,11 +1,11 @@
 {
     "CommonObjectDetector": {
-        "dataset": "COCO",
+        "dataset": "CAR",
         "inputSize": 640,
         "nmsThrs": 0.6,
-        "scoreThrs": 0.4,
+        "scoreThrs": 0.6,
         "useWidthOrHeight": 1,
-        "withSegmentation": true,
+        "withSegmentation": false,
         "datasetPersonVehicle": {
             "person": [0.5, 1.8],
             "car": [4.1, 1.5],
@@ -19,6 +19,9 @@
         "datasetDrone": {
             "drone": [0.4, 0.2]
         },
+        "datasetCAR": {
+            "car": [0.12, 0.1]
+        },
         "datasetCOCO": {
             "person": [-1, -1],
             "bicycle": [-1, -1],
@@ -114,7 +117,10 @@
     "SingleObjectTracker": {
         "algorithm": "nano",
         "backend": 0,
-        "target": 0
+        "target": 0,
+        "useWidthOrHeight": 0,
+        "sigleobjectW":0.126,
+        "sigleobjectH":-1
     },
     "MultipleObjectTracker": {
         "algorithm": "sort",
@@ -151,7 +157,7 @@
     "ArucoDetector": {
         "dictionaryId": 10,
         "markerIds": [-1],
-        "markerLengths": [0.2],
+        "markerLengths": [0.17],
         "adaptiveThreshConstant": 7,
         "adaptiveThreshWinSizeMax": 23,
         "adaptiveThreshWinSizeMin": 3,

samples/calib/calibrate_camera_charuco.cpp

@@ -124,7 +124,9 @@ int main(int argc, char *argv[]) {
         inputVideo.open(video);
         waitTime = 0;
     } else {
-        inputVideo.open(camId);
+    	char pipe[512];
+    	sprintf(pipe, "rtsp://192.168.2.64:554/H264?W=1280&H=720&FPS=30&BR=4000000");
+        inputVideo.open(pipe);
         waitTime = 10;
     }
 

samples/demo/aruco_detection.cpp

@@ -9,13 +9,13 @@ int main(int argc, char *argv[]) {
   // 实例化Aruco检测器类
   sv::ArucoDetector ad;
   // 手动导入相机参数，如果使用Amov的G1等吊舱或相机，则可以忽略该步骤，将自动下载相机参数文件
-  ad.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_640x480.yaml");
+  ad.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_1280x720.yaml");
   
   // 打开摄像头
   sv::Camera cap;
-  // cap.setWH(640, 480);
+  cap.setWH(1280, 720);
-  // cap.setFps(30);
+  cap.setFps(30);
-  cap.open(sv::CameraType::WEBCAM, 0);  // CameraID 0
+  cap.open(sv::CameraType::WEBCAM, 4);  // CameraID 0
   // 实例化OpenCV的Mat类，用于内存单帧图像
   cv::Mat img;
   int frame_id = 0;

samples/demo/detection_with_clicked_tracking.cpp

@@ -40,18 +40,18 @@ int main(int argc, char *argv[]) {
   // 实例化 框选目标跟踪类
   sv::SingleObjectTracker sot;
   // 手动导入相机参数，如果使用Amov的G1等吊舱或相机，则可以忽略该步骤，将自动下载相机参数文件
-  sot.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_640x480.yaml");
+  sot.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_1280x720.yaml");
 
 
   sv::CommonObjectDetector cod;
-  cod.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_640x480.yaml");
+  cod.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_1280x720.yaml");
 
 
   // 打开摄像头
   sv::Camera cap;
-  // cap.setWH(640, 480);
+  cap.setWH(1280, 720);
-  // cap.setFps(30);
+  cap.setFps(30);
-  cap.open(sv::CameraType::WEBCAM, 0);  // CameraID 0
+  cap.open(sv::CameraType::WEBCAM, 4);  // CameraID 0
   // cv::VideoCapture cap("/home/amov/SpireCV/test/tracking_1280x720.mp4");
   // 实例化OpenCV的Mat类，用于内存单帧图像
   cv::Mat img;

samples/demo/ellipse_detection.cpp

@@ -9,13 +9,13 @@ int main(int argc, char *argv[]) {
   // 实例化 椭圆 检测器类
   sv::EllipseDetector ed;
   // 手动导入相机参数，如果使用Amov的G1等吊舱或相机，则可以忽略该步骤，将自动下载相机参数文件
-  ed.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_640x480.yaml");
+  ed.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_1280x720.yaml");
   
   // 打开摄像头
   sv::Camera cap;
-  // cap.setWH(640, 480);
+  cap.setWH(1280, 720);
-  // cap.setFps(30);
+  cap.setFps(30);
-  cap.open(sv::CameraType::WEBCAM, 0);  // CameraID 0
+  cap.open(sv::CameraType::WEBCAM, 4);  // CameraID 0
   // 实例化OpenCV的Mat类，用于内存单帧图像
   cv::Mat img;
   int frame_id = 0;

samples/demo/gimbal_detection_with_clicked_tracking.cpp

@@ -66,7 +66,7 @@ int main(int argc, char *argv[])
   // 设置获取画面分辨率为720P
   cap.setWH(1280, 720);
   // 设置视频帧率为30帧
-  cap.setFps(30);
+  cap.setFps(60);
   // 开启相机
   cap.open(sv::CameraType::G1);
 
@@ -77,10 +77,10 @@ int main(int argc, char *argv[])
   // 实例化 框选目标跟踪类
   sv::SingleObjectTracker sot;
   // 手动导入相机参数，如果使用Amov的G1等吊舱或相机，则可以忽略该步骤，将自动下载相机参数文件
-  sot.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_640x480.yaml");
+  sot.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_1280x720.yaml");
 
   sv::CommonObjectDetector cod;
-  cod.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_640x480.yaml");
+  cod.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_1280x720.yaml");
 
   // 实例化OpenCV的Mat类，用于内存单帧图像
   cv::Mat img;
@@ -248,4 +248,4 @@ void GimableCallback(double &frame_ang_r, double &frame_ang_p, double &frame_ang
     count = 0;
   }
   count++;
-}
+}

samples/demo/gimbal_landing_marker_detection.cpp

@@ -3,7 +3,7 @@
 // 包含SpireCV SDK头文件
 #include <sv_world.h>
 // #include "gimbal_tools.hpp"
-
+#include <chrono>
 using namespace std;
 
 // 云台
@@ -43,11 +43,11 @@ int main(int argc, char *argv[])
   // 定义相机
   sv::Camera cap;
   // 设置相机流媒体地址为 192.168.2.64
-  cap.setIp("192.168.2.64");
+  cap.setIp("192.168.1.64");
   // 设置获取画面分辨率为720P
-  cap.setWH(1280, 720);
+  cap.setWH(640, 480);
   // 设置视频帧率为30帧
-  cap.setFps(30);
+  cap.setFps(120);
   // 开启相机
   cap.open(sv::CameraType::G1);
 
@@ -58,56 +58,63 @@ int main(int argc, char *argv[])
   // 实例化 圆形降落标志 检测器类
   sv::LandingMarkerDetector lmd;
   // 手动导入相机参数，如果使用Amov的G1等吊舱或相机，则可以忽略该步骤，将自动下载相机参数文件
-  lmd.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_1280x720.yaml");
+  lmd.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_640x480.yaml");
 
   // 实例化OpenCV的Mat类，用于内存单帧图像
   cv::Mat img;
   int frame_id = 0;
   while (1)
   {
+   auto time1 = std::chrono::duration_cast<std::chrono::nanoseconds>(std::chrono::system_clock::now().time_since_epoch()).count();
     // 实例化SpireCV的 单帧检测结果 接口类 TargetsInFrame
+    for(uint j = 0; j < 60; j++)
+    {
     sv::TargetsInFrame tgts(frame_id++);
     // 读取一帧图像到img
     cap.read(img);
-    cv::resize(img, img, cv::Size(lmd.image_width, lmd.image_height));
+    //cv::resize(img, img, cv::Size(lmd.image_width, lmd.image_height));
 
     // 执行 降落标志 检测
     lmd.detect(img, tgts);
     // 可视化检测结果，叠加到img上
-    sv::drawTargetsInFrame(img, tgts);
+    //sv::drawTargetsInFrame(img, tgts);
 
     // 控制台打印 降落标志 检测结果
-    printf("Frame-[%d]\n", frame_id);
+    //printf("Frame-[%d]\n", frame_id);
     // 打印当前检测的FPS
     printf("  FPS = %.2f\n", tgts.fps);
     // 打印当前相机的视场角（degree）
-    printf("  FOV (fx, fy) = (%.2f, %.2f)\n", tgts.fov_x, tgts.fov_y);
+    //printf("  FOV (fx, fy) = (%.2f, %.2f)\n", tgts.fov_x, tgts.fov_y);
-    for (int i = 0; i < tgts.targets.size(); i++)
+    //for (int i = 0; i < tgts.targets.size(); i++)
-    {
+    //{
       // 仅追踪 X 类型的标靶
-      if (tgts.targets[i].category_id == 2)
+      //if (tgts.targets[i].category_id == 2)
-      {
+      //{
-        gimbalTrack(tgts.targets[0].cx - 0.5f, tgts.targets[0].cy - 0.5f);
+        //gimbalTrack(tgts.targets[0].cx - 0.5f, tgts.targets[0].cy - 0.5f);
-      }
+      //}
 
-      printf("Frame-[%d], Marker-[%d]\n", frame_id, i);
+      //printf("Frame-[%d], Marker-[%d]\n", frame_id, i);
       // 打印每个 降落标志 的中心位置，cx，cy的值域为[0, 1]
-      printf("  Marker Center (cx, cy) = (%.3f, %.3f)\n", tgts.targets[i].cx, tgts.targets[i].cy);
+      //printf("  Marker Center (cx, cy) = (%.3f, %.3f)\n", tgts.targets[i].cx, tgts.targets[i].cy);
       // 打印每个 降落标志 的外接矩形框的宽度、高度，w，h的值域为(0, 1]
-      printf("  Marker Size (w, h) = (%.3f, %.3f)\n", tgts.targets[i].w, tgts.targets[i].h);
+      //printf("  Marker Size (w, h) = (%.3f, %.3f)\n", tgts.targets[i].w, tgts.targets[i].h);
       // 打印每个 降落标志 的置信度
-      printf("  Marker Score = %.3f\n", tgts.targets[i].score);
+      //printf("  Marker Score = %.3f\n", tgts.targets[i].score);
       // 打印每个 降落标志 的类别，字符串类型，"h"、"x"、"1"、"2"、"3"...
-      printf("  Marker Category = %s, Category ID = %d\n", tgts.targets[i].category.c_str(), tgts.targets[i].category_id);
+      //printf("  Marker Category = %s, Category ID = %d\n", tgts.targets[i].category.c_str(), tgts.targets[i].category_id);
       // 打印每个 降落标志 的视线角，跟相机视场相关
-      printf("  Marker Line-of-sight (ax, ay) = (%.3f, %.3f)\n", tgts.targets[i].los_ax, tgts.targets[i].los_ay);
+      //printf("  Marker Line-of-sight (ax, ay) = (%.3f, %.3f)\n", tgts.targets[i].los_ax, tgts.targets[i].los_ay);
       // 打印每个 降落标志 的3D位置（在相机坐标系下），跟降落标志实际半径、相机参数相关
-      printf("  Marker Position = (x, y, z) = (%.3f, %.3f, %.3f)\n", tgts.targets[i].px, tgts.targets[i].py, tgts.targets[i].pz);
+      //printf("  Marker Position = (x, y, z) = (%.3f, %.3f, %.3f)\n", tgts.targets[i].px, tgts.targets[i].py, //tgts.targets[i].pz);
-    }
+    //}
 
     // 显示检测结果img
     cv::imshow(RGB_WINDOW, img);
-    cv::waitKey(10);
+    cv::waitKey(1);
+    }
+    auto time2 = std::chrono::duration_cast<std::chrono::nanoseconds>(std::chrono::system_clock::now().time_since_epoch()).count();
+        auto Ts = time2 - time1;
+        std::cout << "Ts = " << Ts / (1000) << "us" << std::endl;
   }
 
   return 0;
@@ -144,4 +151,4 @@ void GimableCallback(double &frame_ang_r, double &frame_ang_p, double &frame_ang
     count = 0;
   }
   count++;
-}
+}

samples/demo/gimbal_udp_detection_info_sender.cpp

@@ -79,6 +79,7 @@ int main(int argc, char *argv[])
     sv::TargetsInFrame tgts(frame_id++);
     // 读取一帧图像到img
     cap.read(img);
+    continue;
 
     // 执行Aruco二维码检测
     ad.detect(img, tgts);

samples/demo/landing_marker_detection.cpp

@@ -2,7 +2,7 @@
 #include <string>
 // 包含SpireCV SDK头文件
 #include <sv_world.h>
-
+#include <chrono>
 using namespace std;
 
 int main(int argc, char *argv[]) {
@@ -13,14 +13,18 @@ int main(int argc, char *argv[]) {
 
   // 打开摄像头
   sv::Camera cap;
-  // cap.setWH(640, 480);
+  cap.setWH(640, 480);
-  // cap.setFps(30);
+  cap.setFps(60);
-  cap.open(sv::CameraType::WEBCAM, 0);  // CameraID 0
+  cap.open(sv::CameraType::WEBCAM, 4);  // CameraID 0
   // 实例化OpenCV的Mat类，用于内存单帧图像
   cv::Mat img;
   int frame_id = 0;
   while (1)
   {
+  auto time1 = std::chrono::duration_cast<std::chrono::nanoseconds>(std::chrono::system_clock::now().time_since_epoch()).count();
+    // 实例化SpireCV的 单帧检测结果 接口类 TargetsInFrame
+    for(uint j = 0; j < 60; j++)
+    {
     // 实例化SpireCV的 单帧检测结果 接口类 TargetsInFrame
     sv::TargetsInFrame tgts(frame_id++);
     // 读取一帧图像到img
@@ -33,39 +37,43 @@ int main(int argc, char *argv[]) {
     sv::drawTargetsInFrame(img, tgts);
 
     // 控制台打印 降落标志 检测结果
-    printf("Frame-[%d]\n", frame_id);
+    //printf("Frame-[%d]\n", frame_id);
     // 打印当前检测的FPS
     printf("  FPS = %.2f\n", tgts.fps);
     // 打印当前相机的视场角（degree）
-    printf("  FOV (fx, fy) = (%.2f, %.2f)\n", tgts.fov_x, tgts.fov_y);
+    //printf("  FOV (fx, fy) = (%.2f, %.2f)\n", tgts.fov_x, tgts.fov_y);
     // 打印当前输入图像的像素宽度和高度
-    printf("  Frame Size (width, height) = (%d, %d)\n", tgts.width, tgts.height);
+    //printf("  Frame Size (width, height) = (%d, %d)\n", tgts.width, tgts.height);
     for (int i=0; i<tgts.targets.size(); i++)
     {
-      printf("Frame-[%d], Marker-[%d]\n", frame_id, i);
+      //printf("Frame-[%d], Marker-[%d]\n", frame_id, i);
       // 打印每个 降落标志 的中心位置，cx，cy的值域为[0, 1]，以及cx，cy的像素值
-      printf("  Marker Center (cx, cy) = (%.3f, %.3f), in Pixels = ((%d, %d))\n",
+      //printf("  Marker Center (cx, cy) = (%.3f, %.3f), in Pixels = ((%d, %d))\n",
-        tgts.targets[i].cx, tgts.targets[i].cy,
+        //tgts.targets[i].cx, tgts.targets[i].cy,
-        int(tgts.targets[i].cx * tgts.width),
+        //int(tgts.targets[i].cx * tgts.width),
-        int(tgts.targets[i].cy * tgts.height));
+        //int(tgts.targets[i].cy * tgts.height));
       // 打印每个 降落标志 的外接矩形框的宽度、高度，w，h的值域为(0, 1]，以及w，h的像素值
-      printf("  Marker Size (w, h) = (%.3f, %.3f), in Pixels = ((%d, %d))\n",
+      //printf("  Marker Size (w, h) = (%.3f, %.3f), in Pixels = ((%d, %d))\n",
-        tgts.targets[i].w, tgts.targets[i].h,
+        //tgts.targets[i].w, tgts.targets[i].h,
-        int(tgts.targets[i].w * tgts.width),
+        //int(tgts.targets[i].w * tgts.width),
-        int(tgts.targets[i].h * tgts.height));
+        //int(tgts.targets[i].h * tgts.height));
       // 打印每个 降落标志 的置信度
-      printf("  Marker Score = %.3f\n", tgts.targets[i].score);
+     // printf("  Marker Score = %.3f\n", tgts.targets[i].score);
       // 打印每个 降落标志 的类别，字符串类型，"h"、"x"、"1"、"2"、"3"...
-      printf("  Marker Category = %s, Category ID = %d\n", tgts.targets[i].category.c_str(), tgts.targets[i].category_id);
+      //printf("  Marker Category = %s, Category ID = %d\n", tgts.targets[i].category.c_str(), tgts.targets[i].category_id);
       // 打印每个 降落标志 的视线角，跟相机视场相关
-      printf("  Marker Line-of-sight (ax, ay) = (%.3f, %.3f)\n", tgts.targets[i].los_ax, tgts.targets[i].los_ay);
+      //printf("  Marker Line-of-sight (ax, ay) = (%.3f, %.3f)\n", tgts.targets[i].los_ax, tgts.targets[i].los_ay);
       // 打印每个 降落标志 的3D位置（在相机坐标系下），跟降落标志实际半径、相机参数相关
-      printf("  Marker Position = (x, y, z) = (%.3f, %.3f, %.3f)\n", tgts.targets[i].px, tgts.targets[i].py, tgts.targets[i].pz);
+     // printf("  Marker Position = (x, y, z) = (%.3f, %.3f, %.3f)\n", tgts.targets[i].px, tgts.targets[i].py, tgts.targets[i].pz);
     }
     
     // 显示检测结果img
     cv::imshow("img", img);
     cv::waitKey(10);
+    }
+    auto time2 = std::chrono::duration_cast<std::chrono::nanoseconds>(std::chrono::system_clock::now().time_since_epoch()).count();
+        auto Ts = time2 - time1;
+        std::cout << "Ts = " << Ts / (1000) << "us" << std::endl;
   }
 
   return 0;

samples/demo/single_object_tracking.cpp

@@ -28,15 +28,16 @@ int main(int argc, char *argv[]) {
   // 实例化 框选目标跟踪类
   sv::SingleObjectTracker sot;
   // 手动导入相机参数，如果使用Amov的G1等吊舱或相机，则可以忽略该步骤，将自动下载相机参数文件
-  sot.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_640x480.yaml");
+  //sot.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_640x480.yaml");
-  // sot.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_1280x720.yaml");
+  sot.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_1280x720.yaml");
   // sot.loadCameraParams(sv::get_home() + "/SpireCV/calib_webcam_1920x1080.yaml");
   
   // 打开摄像头
   sv::Camera cap;
-  // cap.setWH(640, 480);
+  cap.setWH(1280, 720);
-  // cap.setFps(30);
+  cap.setFps(30);
-  cap.open(sv::CameraType::WEBCAM, 0);  // CameraID 0
+  cap.open(sv::CameraType::WEBCAM, 4);  // CameraID 0
+ 
   // cv::VideoCapture cap("/home/amov/SpireCV/test/tracking_1280x720.mp4");
   // 实例化OpenCV的Mat类，用于内存单帧图像
   cv::Mat img;

samples/test/camera_fps_test.cpp

@@ -0,0 +1,34 @@
+
+#include <sv_world.h>
+#include <iostream>
+#include <string>
+#include <chrono>
+
+int main(int argc, char *argv[])
+{
+    sv::Camera cap;
+    cap.setIp(argv[1]);
+    cap.setWH(640, 480);
+    cap.setFps(60);
+    cap.open(sv::CameraType::G1);
+    
+    //cap.open(sv::CameraType::WEBCAM, 4);
+
+    cv::Mat img;
+    //auto time1,time2;
+
+    while (1)
+    {
+        auto time1 = std::chrono::duration_cast<std::chrono::nanoseconds>(std::chrono::system_clock::now().time_since_epoch()).count();
+        //for (uint16_t i = 0; i < 120; i++)
+        //{
+            cap.read(img);
+            cv::imshow("TEST",img);
+            cv::waitKey(1);
+        //}
+        auto time2 = std::chrono::duration_cast<std::chrono::nanoseconds>(std::chrono::system_clock::now().time_since_epoch()).count();
+        auto Ts = time2 - time1;
+        std::cout << "read 120 count;Ts = " << Ts / (1000) << "us" << std::endl;
+        std::cout << "average FPS = " << (1000 * 1000 * 1000) / (Ts / 120) << std::endl;
+    }
+}

scripts/common/configs-downloading.sh

@@ -1,39 +0,0 @@
-#!/bin/bash -e
-
-root_dir=${HOME}"/SpireCV/models"
-root_server="https://download.amovlab.com/model"
-
-sv_params1=${HOME}"/SpireCV/sv_algorithm_params.json"
-sv_params2=${HOME}"/SpireCV/sv_algorithm_params_coco_640.json"
-sv_params3=${HOME}"/SpireCV/sv_algorithm_params_coco_1280.json"
-camera_params1=${HOME}"/SpireCV/calib_webcam_640x480.yaml"
-camera_params2=${HOME}"/SpireCV/calib_webcam_1280x720.yaml"
-
-
-if [ ! -d ${root_dir} ]; then
-  echo -e "\033[32m[INFO]: ${root_dir} not exist, creating it ... \033[0m"
-  mkdir -p ${root_dir}
-fi
-
-if [ ! -f ${sv_params1} ]; then
-  echo -e "\033[32m[INFO]: ${sv_params1} not exist, downloading ... \033[0m"
-  wget -O ${sv_params1} ${root_server}/install/a-params/sv_algorithm_params.json
-fi
-if [ ! -f ${sv_params2} ]; then
-  echo -e "\033[32m[INFO]: ${sv_params2} not exist, downloading ... \033[0m"
-  wget -O ${sv_params2} ${root_server}/install/a-params/sv_algorithm_params_coco_640.json
-fi
-if [ ! -f ${sv_params3} ]; then
-  echo -e "\033[32m[INFO]: ${sv_params3} not exist, downloading ... \033[0m"
-  wget -O ${sv_params3} ${root_server}/install/a-params/sv_algorithm_params_coco_1280.json
-fi
-
-if [ ! -f ${camera_params1} ]; then
-  echo -e "\033[32m[INFO]: ${camera_params1} not exist, downloading ... \033[0m"
-  wget -O ${camera_params1} ${root_server}/install/c-params/calib_webcam_640x480.yaml
-fi
-if [ ! -f ${camera_params2} ]; then
-  echo -e "\033[32m[INFO]: ${camera_params2} not exist, downloading ... \033[0m"
-  wget -O ${camera_params2} ${root_server}/install/c-params/calib_webcam_1280x720.yaml
-fi
-

scripts/common/ffmpeg425-install.sh

@@ -2,7 +2,7 @@
 
 
 sudo apt install -y \
-build-essential yasm cmake libtool libc6 libc6-dev unzip wget libeigen3-dev libfmt-dev \
+build-essential yasm cmake libtool libc6 libc6-dev unzip wget libfmt-dev \
 libnuma1 libnuma-dev libx264-dev libx265-dev libfaac-dev libssl-dev
 
 root_dir=${HOME}"/SpireCV"

scripts/common/gst-install-orin.sh

@@ -8,7 +8,6 @@ sudo apt install -y gstreamer1.0-tools gstreamer1.0-x gstreamer1.0-alsa
 sudo apt install -y gstreamer1.0-gl gstreamer1.0-gtk3 gstreamer1.0-qt5 
 sudo apt install -y gstreamer1.0-pulseaudio
 sudo apt install -y gtk-doc-tools
-sudo apt install -y libeigen3-dev libfmt-dev
 
 sudo apt -y install autotools-dev automake m4 perl
 sudo apt -y install libtool

scripts/common/gst-install.sh

@@ -8,7 +8,6 @@ sudo apt install -y gstreamer1.0-tools gstreamer1.0-x gstreamer1.0-alsa
 sudo apt install -y gstreamer1.0-gl gstreamer1.0-gtk3 gstreamer1.0-qt5 
 sudo apt install -y gstreamer1.0-pulseaudio
 sudo apt install -y gtk-doc-tools
-sudo apt install -y libeigen3-dev libfmt-dev
 
 git clone https://gitee.com/jario-jin/gst-rtsp-server-b18.git
 cd gst-rtsp-server-b18

scripts/jetson/opencv470-jetpack511-cuda-install.sh

@@ -1,54 +0,0 @@
-#!/bin/sh
-
-
-wget https://download.amovlab.com/model/deps/opencv-4.7.0.zip
-wget https://download.amovlab.com/model/deps/opencv_contrib-4.7.0.zip
-wget https://download.amovlab.com/model/deps/opencv_cache-4.7.0.zip
-
-
-package_dir="."
-mkdir ~/opencv_build
-
-
-if [ ! -d ""$package_dir"" ];then
-  echo "\033[31m[ERROR]: $package_dir not exist!: \033[0m"
-  exit 1
-fi
-
-sudo apt update
-sudo apt install -y build-essential
-sudo apt install -y cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
-sudo apt install -y libjasper1 libjasper-dev
-sudo apt install -y python3-dev python3-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev
-sudo apt install -y libdc1394-22-dev
-
-
-echo "\033[32m[INFO]:\033[0m unzip opencv-4.7.0.zip ..."
-unzip  -q -o $package_dir/opencv-4.7.0.zip -d ~/opencv_build
-
-echo "\033[32m[INFO]:\033[0m unzip opencv_contrib-4.7.0.zip ..."
-unzip  -q -o $package_dir/opencv_contrib-4.7.0.zip -d ~/opencv_build
-
-echo "\033[32m[INFO]:\033[0m unzip opencv_cache-4.7.0.zip ..."
-unzip  -q -o $package_dir/opencv_cache-4.7.0.zip -d ~/opencv_build
-
-
-sudo rm opencv-4.7.0.zip
-sudo rm opencv_contrib-4.7.0.zip
-sudo rm opencv_cache-4.7.0.zip
-
-cd ~/opencv_build/opencv-4.7.0
-mkdir .cache
-
-cp -r ~/opencv_build/opencv_cache-4.7.0/* ~/opencv_build/opencv-4.7.0/.cache/
-
-mkdir build
-cd build
-
-cmake -D CMAKE_BUILD_TYPE=Release -D WITH_CUDA=ON -D CUDA_ARCH_BIN=8.7 -D WITH_CUDNN=ON -D OPENCV_DNN_CUDA=ON -D WITH_CUBLAS=ON -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda -D OPENCV_ENABLE_NONFREE=ON -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib-4.7.0/modules ..
-
-make -j2
-sudo make install
-
-cd
-sudo rm -r ~/opencv_build

scripts/x86-cuda/x86-gst-install.sh

@@ -8,7 +8,6 @@ sudo apt install -y gstreamer1.0-tools gstreamer1.0-x gstreamer1.0-alsa
 sudo apt install -y gstreamer1.0-gl gstreamer1.0-gtk3 gstreamer1.0-qt5 
 sudo apt install -y gstreamer1.0-pulseaudio
 sudo apt install -y gtk-doc-tools
-sudo apt install -y libeigen3-dev libfmt-dev
 
 git clone https://gitee.com/jario-jin/gst-rtsp-server-b18.git
 cd gst-rtsp-server-b18

scripts/x86-cuda/x86-opencv470-cuda-install.sh

@@ -1,69 +0,0 @@
-#!/bin/sh
-
-
-wget https://download.amovlab.com/model/deps/opencv-4.7.0.zip
-wget https://download.amovlab.com/model/deps/opencv_contrib-4.7.0.zip
-wget https://download.amovlab.com/model/deps/opencv_cache_x86-4.7.0.zip
-
-
-package_dir="."
-mkdir ~/opencv_build
-
-
-if [ ! -d ""$package_dir"" ];then
-  echo "\033[31m[ERROR]: $package_dir not exist!: \033[0m"
-  exit 1
-fi
-
-# sudo add-apt-repository "deb http://security.ubuntu.com/ubuntu xenial-security main"
-# sudo add-apt-repository "deb http://mirrors.tuna.tsinghua.edu.cn/ubuntu-ports/ xenial main multiverse restricted universe"
-sudo apt update
-sudo apt install -y build-essential
-sudo apt install -y cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
-
-sudo add-apt-repository "deb http://security.ubuntu.com/ubuntu xenial-security main"
-sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 3B4FE6ACC0B21F32
-sudo apt update
-sudo apt install -y libjasper1 libjasper-dev
-
-sudo apt install -y python3-dev python3-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev
-sudo apt install -y libdc1394-22-dev
-
-
-echo "\033[32m[INFO]:\033[0m unzip opencv-4.7.0.zip ..."
-unzip  -q -o $package_dir/opencv-4.7.0.zip -d ~/opencv_build
-
-echo "\033[32m[INFO]:\033[0m unzip opencv_contrib-4.7.0.zip ..."
-unzip  -q -o $package_dir/opencv_contrib-4.7.0.zip -d ~/opencv_build
-
-echo "\033[32m[INFO]:\033[0m unzip opencv_cache_x86-4.7.0.zip ..."
-unzip  -q -o $package_dir/opencv_cache_x86-4.7.0.zip -d ~/opencv_build
-
-
-sudo rm opencv-4.7.0.zip
-sudo rm opencv_contrib-4.7.0.zip
-sudo rm opencv_cache_x86-4.7.0.zip
-
-cd ~/opencv_build/opencv-4.7.0
-mkdir .cache
-
-cp -r ~/opencv_build/opencv_cache_x86-4.7.0/* ~/opencv_build/opencv-4.7.0/.cache/
-
-mkdir build
-cd build
-
-cmake -D CMAKE_BUILD_TYPE=Release \
-      -D WITH_CUDA=ON \
-      -D WITH_CUDNN=ON \
-      -D OPENCV_DNN_CUDA=ON \
-      -D WITH_CUBLAS=ON \
-      -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda \
-      -D OPENCV_ENABLE_NONFREE=ON \
-      -D CMAKE_INSTALL_PREFIX=/usr/local \
-      -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib-4.7.0/modules ..
-
-make -j2
-sudo make install
-
-cd
-sudo rm -r ~/opencv_build

scripts/x86-cuda/x86-opencv470-install.sh

@@ -20,12 +20,7 @@ fi
 sudo apt update
 sudo apt install -y build-essential
 sudo apt install -y cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
-
-sudo add-apt-repository "deb http://security.ubuntu.com/ubuntu xenial-security main"
-sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 3B4FE6ACC0B21F32
-sudo apt update
 sudo apt install -y libjasper1 libjasper-dev
-
 sudo apt install -y python3-dev python3-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev
 sudo apt install -y libdc1394-22-dev
 

video_io/sv_video_base.cpp

@@ -368,6 +368,58 @@ void UDPServer::send(const TargetsInFrame& tgts_)
 }
 
 
+void drawTargetsInFrame(
+  cv::Mat& img_,
+  const TargetsInFrame& tgts_,
+  int aruco_track_id,
+  bool with_all,
+  bool with_category,
+  bool with_tid,
+  bool with_seg,
+  bool with_box,
+  bool with_ell,
+  bool with_aruco,
+  bool with_yaw
+)
+{
+  if (tgts_.rois.size() > 0 )
+  {
+    cv::Mat image_ret;
+    cv::addWeighted(img_, 0.5, cv::Mat::zeros(cv::Size(img_.cols, img_.rows), CV_8UC3), 0, 0, image_ret);
+    cv::Rect roi = cv::Rect(tgts_.rois[0].x1, tgts_.rois[0].y1, tgts_.rois[0].x2 - tgts_.rois[0].x1, tgts_.rois[0].y2 - tgts_.rois[0].y1);
+    img_(roi).copyTo(image_ret(roi));
+    image_ret.copyTo(img_);
+  }
+  std::vector<std::vector<cv::Point2f> > aruco_corners;
+  std::vector<int> aruco_ids;
+  for (Target tgt : tgts_.targets)
+  {
+    if ((with_all || with_aruco) && tgt.has_aruco && (tgt.tracked_id == aruco_track_id))
+    {
+      std::vector<cv::Point2f> a_corners;
+      int a_id;
+      if (tgt.getAruco(a_id, a_corners))  { aruco_ids.push_back(a_id); aruco_corners.push_back(a_corners); }
+      cv::circle(img_, cv::Point(int(tgt.cx * tgts_.width), int(tgt.cy * tgts_.height)), 4, cv::Scalar(0,255,0), 2);
+    }
+    if ((with_all || with_box) && tgt.has_box && (tgt.tracked_id == aruco_track_id))
+    {
+      Box b;
+      tgt.getBox(b);
+      cv::rectangle(img_, cv::Rect(b.x1, b.y1, b.x2-b.x1+1, b.y2-b.y1+1), cv::Scalar(0,0,255), 1, 1, 0);
+      if ((with_all || with_category) && tgt.has_category)
+      {
+        cv::putText(img_, tgt.category, cv::Point(b.x1, b.y1-4), cv::FONT_HERSHEY_DUPLEX, 0.4, cv::Scalar(255,0,0));
+      }
+    }
+  }
+  if ((with_all || with_aruco) && aruco_ids.size() > 0)
+  {
+    cv::aruco::drawDetectedMarkers(img_, aruco_corners, aruco_ids);
+  }
+}
+
+
+
 void drawTargetsInFrame(
   cv::Mat& img_,
   const TargetsInFrame& tgts_,
@@ -809,7 +861,7 @@ VideoWriterBase::VideoWriterBase()
 VideoWriterBase::~VideoWriterBase()
 {
   this->release();
-  // this->_tt.join();
+  this->_tt.join();
 }
 cv::Size VideoWriterBase::getSize()
 {
@@ -991,7 +1043,7 @@ CameraBase::CameraBase(CameraType type, int id)
 CameraBase::~CameraBase()
 {
   this->_is_running = false;
-  // this->_tt.join();
+  this->_tt.join();
 }
 void CameraBase::setWH(int width, int height)
 {
@@ -1103,33 +1155,57 @@ void CameraBase::_run()
 {
   while (this->_is_running && this->_cap.isOpened())
   {
-    this->_cap >> this->_frame;
+     //this->_cap >> this->_frame;
-    this->_is_updated = true;
+     //this->_is_updated = true;
-    std::this_thread::sleep_for(std::chrono::milliseconds(2));
+     //std::this_thread::sleep_for(std::chrono::milliseconds(2));
+
+    if(this->_cap.grab())
+    {
+      std::lock_guard<std::mutex> locker(this->_frame_mutex);
+      this->_cap.retrieve(this->_frame);      
+      this->_frame_empty.notify_all();
+    }
+    std::this_thread::sleep_for(std::chrono::milliseconds(1));
   }
 }
 bool CameraBase::read(cv::Mat& image)
 {
+  bool ret = false;
   if (this->_type == CameraType::WEBCAM || this->_type == CameraType::G1 || this->_type == CameraType::MIPI)
   {
-    int n_try = 0;
+    std::lock_guard<std::mutex> locker(this->_frame_mutex);
-    while (n_try < 5000)
+    if(this->_frame_empty.wait_for(this->_frame_mutex,std::chrono::milliseconds(2000)) == std::cv_status::no_timeout)
     {
-      if (this->_is_updated)
+      this->_frame.copyTo(image);
-      {
+      ret = true;
-        this->_is_updated = false;
+    }
-        this->_frame.copyTo(image);
+    else
-        break;
+    {
-      }
+      throw std::runtime_error("SpireCV (101) Camera cannot OPEN, check CAMERA_ID!");
-      std::this_thread::sleep_for(std::chrono::milliseconds(20));
-      n_try ++;
     }
   }
-  if (image.cols == 0 || image.rows == 0)
+  return ret;
-  {
+
-    throw std::runtime_error("SpireCV (101) Camera cannot OPEN, check CAMERA_ID!");
+   if (this->_type == CameraType::WEBCAM || this->_type == CameraType::G1 || this->_type == CameraType::MIPI)
-  }
+   {
-  return image.cols > 0 && image.rows > 0;
+     int n_try = 0;
+     while (n_try < 5000)
+     {
+       if (this->_is_updated)
+       {
+         this->_is_updated = false;
+         this->_frame.copyTo(image);
+         break;
+       }
+       std::this_thread::sleep_for(std::chrono::milliseconds(10));
+       n_try ++;
+     }
+   }
+   if (image.cols == 0 || image.rows == 0)
+   {
+     throw std::runtime_error("SpireCV (101) Camera cannot OPEN, check CAMERA_ID!");
+   }
+   return image.cols > 0 && image.rows > 0;
 }
 void CameraBase::release()
 {

video_io/sv_video_input.cpp

@@ -79,6 +79,7 @@ void Camera::openImpl()
   else if (this->_type == CameraType::MIPI)
   {
     char pipe[512];
+    this->_cap.open(this->_camera_id);
     if (this->_width <= 0 || this->_height <= 0)
     {
       this->_width = 1280;
@@ -89,7 +90,7 @@ void Camera::openImpl()
       this->_fps = 30;
     }
 
-    sprintf(pipe, "nvarguscamerasrc sensor-id=%d ! video/x-raw(memory:NVMM), width=(int)%d, height=(int)%d, format=(string)NV12, framerate=(fraction)%d/1 ! nvvidconv flip-method=0 ! video/x-raw, width=(int)%d, height=(int)%d, format=(string)BGRx ! videoconvert ! video/x-raw, format=(string)BGR ! appsink", this->_camera_id, this->_width, this->_height, this->_fps, this->_width, this->_height);
+    sprintf(pipe, "nvarguscamerasrc framerate=(fraction)%d/1 ! nvvidconv flip-method=0 ! video/x-raw, width=(int)%d, height=(int)%d, format=(string)BGRx ! videoconvert ! video/x-raw, format=(string)BGR ! appsink",this->_fps,this->_width,this->_height);
     this->_cap.open(pipe, cv::CAP_GSTREAMER);
  }
 }