add flexible configuration for disable det model(C++)

deploy/cpp_shitu/src/main.cpp

@@ -37,17 +37,14 @@
 using namespace std;
 using namespace cv;
 
-DEFINE_string(config,
-"", "Path of yaml file");
-DEFINE_string(c,
-"", "Path of yaml file");
+DEFINE_string(config, "", "Path of yaml file");
+DEFINE_string(c, "", "Path of yaml file");
 
-void DetPredictImage(const std::vector <cv::Mat> &batch_imgs,
-                     const std::vector <std::string> &all_img_paths,
+void DetPredictImage(const std::vector<cv::Mat> &batch_imgs,
+                     const std::vector<std::string> &all_img_paths,
                      const int batch_size, Detection::ObjectDetector *det,
-                     std::vector <Detection::ObjectResult> &im_result,
-                     std::vector<int> &im_bbox_num, std::vector<double> &det_t,
-                     const bool visual_det = false,
+                     std::vector<Detection::ObjectResult> &im_result,
+                     std::vector<double> &det_t, const bool visual_det = false,
                      const bool run_benchmark = false,
                      const std::string &output_dir = "output") {
   int steps = ceil(float(all_img_paths.size()) / batch_size);
@@ -65,7 +62,7 @@ void DetPredictImage(const std::vector <cv::Mat> &batch_imgs,
     // }
 
     // Store all detected result
-        std::vector <Detection::ObjectResult> result;
+    std::vector<Detection::ObjectResult> result;
     std::vector<int> bbox_num;
     std::vector<double> det_times;
     bool is_rbox = false;
@@ -104,7 +101,7 @@ void DetPredictImage(const std::vector <cv::Mat> &batch_imgs,
             }
           }
         }
-                im_bbox_num.push_back(detect_num);
+        // im_bbox_num.push_back(detect_num);
         item_start_idx = item_start_idx + bbox_num[i];
 
         // Visualization result
@@ -136,16 +133,17 @@ void DetPredictImage(const std::vector <cv::Mat> &batch_imgs,
 }
 
 void PrintResult(std::string &img_path,
-                 std::vector <Detection::ObjectResult> &det_result,
-                 std::vector<int> &indeices, VectorSearch &vector_search,
+                 std::vector<Detection::ObjectResult> &det_result,
+                 std::vector<int> &indeices, VectorSearch *vector_search_ptr,
                  SearchResult &search_result) {
   printf("%s:\n", img_path.c_str());
   for (int i = 0; i < indeices.size(); ++i) {
     int t = indeices[i];
-        printf("\tresult%d: bbox[%d, %d, %d, %d], score: %f, label: %s\n", i,
+    printf(
+        "\tresult%d: bbox[%d, %d, %d, %d], score: %f, label: %s\n", i,
         det_result[t].rect[0], det_result[t].rect[1], det_result[t].rect[2],
         det_result[t].rect[3], det_result[t].confidence,
-               vector_search.GetLabel(search_result.I[search_result.return_k * t])
+        vector_search_ptr->GetLabel(search_result.I[search_result.return_k * t])
             .c_str());
   }
 }
@@ -168,10 +166,21 @@ int main(int argc, char **argv) {
   YamlConfig config(yaml_path);
   config.PrintConfigInfo();
 
-    // initialize detector, rec_Model, vector_search
-    Feature::FeatureExtracter feature_extracter(config.config_file);
-    Detection::ObjectDetector detector(config.config_file);
-    VectorSearch searcher(config.config_file);
+  // initialize detector
+  Detection::ObjectDetector *detector_ptr = nullptr;
+  if (config.config_file["Global"]["det_inference_model_dir"].Type() !=
+          YAML::NodeType::Null &&
+      !config.config_file["Global"]["det_inference_model_dir"]
+           .as<std::string>()
+           .empty()) {
+    detector_ptr = new Detection::ObjectDetector(config.config_file);
+  }
+
+  // initialize feature_extractor
+  Feature::FeatureExtracter *feature_extracter_ptr =
+      new Feature::FeatureExtracter(config.config_file);
+  // initialize vector_searcher
+  VectorSearch *vector_searcher_ptr = new VectorSearch(config.config_file);
 
   // config
   const int batch_size = config.config_file["Global"]["batch_size"].as<int>();
@@ -196,9 +205,9 @@ int main(int argc, char **argv) {
   // load image_file_path
   std::string path =
       config.config_file["Global"]["infer_imgs"].as<std::string>();
-    std::vector <std::string> img_files_list;
+  std::vector<std::string> img_files_list;
   if (cv::utils::fs::isDirectory(path)) {
-        std::vector <cv::String> filenames;
+    std::vector<cv::String> filenames;
     cv::glob(path, filenames);
     for (auto f : filenames) {
       img_files_list.push_back(f);
@@ -213,11 +222,11 @@ int main(int argc, char **argv) {
   std::vector<double> search_times = {0, 0, 0};
   int instance_num = 0;
   // for read images
-    std::vector <cv::Mat> batch_imgs;
-    std::vector <std::string> img_paths;
+  std::vector<cv::Mat> batch_imgs;
+  std::vector<std::string> img_paths;
   // for detection
-    std::vector <Detection::ObjectResult> det_result;
-    std::vector<int> det_bbox_num;
+  std::vector<Detection::ObjectResult> det_result;
+
   // for vector search
   std::vector<float> features;
   std::vector<float> feature;
@@ -243,9 +252,11 @@ int main(int argc, char **argv) {
     batch_imgs.push_back(srcimg);
     img_paths.push_back(img_path);
 
-        // step1: get all detection results
-        DetPredictImage(batch_imgs, img_paths, batch_size, &detector, det_result,
-                        det_bbox_num, det_times, visual_det, false);
+    // step1: get all detection results if enable detector
+    if (detector_ptr != nullptr) {
+      DetPredictImage(batch_imgs, img_paths, batch_size, detector_ptr,
+                      det_result, det_times, visual_det, false);
+    }
 
     // select max_det_results bbox
     if (det_result.size() > max_det_results) {
@@ -257,7 +268,6 @@ int main(int argc, char **argv) {
     Detection::ObjectResult result_whole_img = {
         {0, 0, srcimg.cols - 1, srcimg.rows - 1}, 0, 1.0};
     det_result.push_back(result_whole_img);
-        det_bbox_num[0] = det_result.size() + 1;
 
     // step3: extract feature for all boxes in an inmage
     SearchResult search_result;
@@ -266,20 +276,22 @@ int main(int argc, char **argv) {
       int h = det_result[j].rect[3] - det_result[j].rect[1];
       cv::Rect rect(det_result[j].rect[0], det_result[j].rect[1], w, h);
       cv::Mat crop_img = srcimg(rect);
-            feature_extracter.Run(crop_img, feature, cls_times);
+      feature_extracter_ptr->Run(crop_img, feature, cls_times);
       features.insert(features.end(), feature.begin(), feature.end());
     }
 
     // step4: get search result
     auto search_start = std::chrono::steady_clock::now();
-        search_result = searcher.Search(features.data(), det_result.size());
+    search_result =
+        vector_searcher_ptr->Search(features.data(), det_result.size());
     auto search_end = std::chrono::steady_clock::now();
 
     // nms for search result
     for (int i = 0; i < det_result.size(); ++i) {
       det_result[i].confidence = search_result.D[search_result.return_k * i];
     }
-        NMSBoxes(det_result, searcher.GetThreshold(), rec_nms_thresold, indeices);
+    NMSBoxes(det_result, vector_searcher_ptr->GetThreshold(), rec_nms_thresold,
+             indeices);
     auto nms_end = std::chrono::steady_clock::now();
     std::chrono::duration<float> search_diff = search_end - search_start;
     search_times[1] += double(search_diff.count() * 1000);
@@ -289,12 +301,12 @@ int main(int argc, char **argv) {
 
     // print result
     if (not benchmark or (benchmark and idx >= warmup_iter))
-            PrintResult(img_path, det_result, indeices, searcher, search_result);
+      PrintResult(img_path, det_result, indeices, vector_searcher_ptr,
+                  search_result);
 
     // for postprocess
     batch_imgs.clear();
     img_paths.clear();
-        det_bbox_num.clear();
     det_result.clear();
     feature.clear();
     features.clear();
@@ -320,10 +332,12 @@ int main(int argc, char **argv) {
         config.config_file["Global"]["cpu_num_threads"].as<int>();
     int batch_size = config.config_file["Global"]["batch_size"].as<int>();
     std::vector<int> shape =
-                config.config_file["Global"]["image_shape"].as < std::vector < int >> ();
+        config.config_file["Global"]["image_shape"].as<std::vector<int>>();
     std::string det_shape = std::to_string(shape[0]);
-        for (int i = 1; i < shape.size(); ++i)
+
+    for (int i = 1; i < shape.size(); ++i) {
       det_shape = det_shape + ", " + std::to_string(shape[i]);
+    }
 
     AutoLogger autolog_det("Det", use_gpu, use_tensorrt, enable_mkldnn,
                            cpu_num_threads, batch_size, det_shape, presion,