code format

deploy/cpp/readme.md

@@ -215,9 +215,9 @@ cp ../configs/inference_cls.yaml tools/
 #### 2.3.2 执行
 
 ```shell
-./build/clas_system -c inference_cls.yaml
+./build/clas_system -c tools/inference_cls.yaml
 # or
-./build/clas_system -config inference_cls.yaml
+./build/clas_system -config tools/inference_cls.yaml
 ```
 
 最终屏幕上会输出结果，如下图所示。

deploy/cpp_shitu/src/feature_extracter.cpp

@@ -18,7 +18,7 @@
 
 namespace Feature {
 
-void FeatureExtracter::LoadModel(const std::string &model_path,
+    void FeatureExtracter::LoadModel(const std::string &model_path,
                                      const std::string &params_path) {
         paddle_infer::Config config;
         config.SetModel(model_path, params_path);
@@ -52,9 +52,9 @@ void FeatureExtracter::LoadModel(const std::string &model_path,
         config.DisableGlogInfo();
 
         this->predictor_ = CreatePredictor(config);
-}
+    }
 
-void FeatureExtracter::Run(cv::Mat &img, std::vector<float> &out_data,
+    void FeatureExtracter::Run(cv::Mat &img, std::vector<float> &out_data,
                                std::vector<double> &times) {
         cv::Mat resize_img;
         std::vector<double> time;
@@ -108,12 +108,12 @@ void FeatureExtracter::Run(cv::Mat &img, std::vector<float> &out_data,
         times[0] += time[0];
         times[1] += time[1];
         times[2] += time[2];
-}
+    }
 
-void FeatureExtracter::FeatureNorm(std::vector<float> &featuer) {
+    void FeatureExtracter::FeatureNorm(std::vector<float> &featuer) {
         float featuer_sqrt = std::sqrt(std::inner_product(
                 featuer.begin(), featuer.end(), featuer.begin(), 0.0f));
         for (int i = 0; i < featuer.size(); ++i)
             featuer[i] /= featuer_sqrt;
-}
+    }
 } // namespace Feature

deploy/cpp_shitu/src/main.cpp

@@ -37,13 +37,15 @@
 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 <Detection::ObjectResult> &im_result,
                      std::vector<int> &im_bbox_num, std::vector<double> &det_t,
                      const bool visual_det = false,
                      const bool run_benchmark = false,
@@ -63,7 +65,7 @@ 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;
@@ -134,7 +136,7 @@ void DetPredictImage(const std::vector<cv::Mat> &batch_imgs,
 }
 
 void PrintResult(std::string &img_path,
-                 std::vector<Detection::ObjectResult> &det_result,
+                 std::vector <Detection::ObjectResult> &det_result,
                  std::vector<int> &indeices, VectorSearch &vector_search,
                  SearchResult &search_result) {
     printf("%s:\n", img_path.c_str());
@@ -194,9 +196,9 @@ 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);
@@ -211,10 +213,10 @@ 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 <Detection::ObjectResult> det_result;
     std::vector<int> det_bbox_num;
     // for vector search
     std::vector<float> features;
@@ -318,7 +320,7 @@ 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)
             det_shape = det_shape + ", " + std::to_string(shape[i]);