add result comparison for det cpp_infer

deploy/cpp_infer/src/main.cpp

@@ -91,7 +91,7 @@ int main_det(std::vector<cv::String> cv_all_img_names) {
                    FLAGS_use_tensorrt, FLAGS_precision);
     
     for (int i = 0; i < cv_all_img_names.size(); ++i) {
-      LOG(INFO) << "The predict img: " << cv_all_img_names[i];
+//       LOG(INFO) << "The predict img: " << cv_all_img_names[i];
 
       cv::Mat srcimg = cv::imread(cv_all_img_names[i], cv::IMREAD_COLOR);
       if (!srcimg.data) {
@@ -106,6 +106,16 @@ int main_det(std::vector<cv::String> cv_all_img_names) {
       time_info[0] += det_times[0];
       time_info[1] += det_times[1];
       time_info[2] += det_times[2];
+    
+      if (FLAGS_benchmark) {
+          cout << cv_all_img_names[i] << '\t';
+          for (int n = 0; n < boxes.size(); n++) {
+            for (int m = 0; m < boxes[n].size(); m++) {
+              cout << boxes[n][m][0] << ' ' << boxes[n][m][1] << ' ';
+            }
+          }
+          cout << endl;
+      }        
     }
     
     if (FLAGS_benchmark) {

tests/compare_results.py

@@ -32,7 +32,6 @@ def run_shell_command(cmd):
     else:
         return None
 
-
 def parser_results_from_log_by_name(log_path, names_list):
     if not os.path.exists(log_path):
         raise ValueError("The log file {} does not exists!".format(log_path))
@@ -46,11 +45,13 @@ def parser_results_from_log_by_name(log_path, names_list):
         outs = run_shell_command(cmd)
         outs = outs.split("\n")[0]
         result = outs.split("{}".format(name))[-1]
-        result = json.loads(result)
+        try:
+            result = json.loads(result)
+        except:
+            result = np.array([int(r) for r in result.split()]).reshape(-1, 4)
         parser_results[name] = result
     return parser_results
 
-
 def load_gt_from_file(gt_file):
     if not os.path.exists(gt_file):
         raise ValueError("The log file {} does not exists!".format(gt_file))
@@ -60,7 +61,11 @@ def load_gt_from_file(gt_file):
     parser_gt = {}
     for line in data:
         image_name, result = line.strip("\n").split("\t")
-        result = json.loads(result)
+        image_name = image_name.split('/')[-1]
+        try:
+            result = json.loads(result)
+        except:
+            result = np.array([int(r) for r in result.split()]).reshape(-1, 4)
         parser_gt[image_name] = result
     return parser_gt