diff --git a/deploy/cpp_infer/include/ocr_rec.h b/deploy/cpp_infer/include/ocr_rec.h
index c3d2b34c2234d77d796d88c307b207053191ded2..d585112b051daff7c03060836a4c065ba6e3949c 100644
--- a/deploy/cpp_infer/include/ocr_rec.h
+++ b/deploy/cpp_infer/include/ocr_rec.h
@@ -90,9 +90,6 @@ private:
   // post-process
   PostProcessor post_processor_;
 
-  cv::Mat GetRotateCropImage(const cv::Mat &srcimage,
-                             std::vector<std::vector<int>> box);
-
 }; // class CrnnRecognizer
 
 } // namespace PaddleOCR
diff --git a/deploy/cpp_infer/src/ocr_det.cpp b/deploy/cpp_infer/src/ocr_det.cpp
index 204dac0f5a8a3fd1c23b69ea14ece283b22aff97..a69f5ca1bd3ee7665f8b2f5610c67dd6feb7eb54 100644
--- a/deploy/cpp_infer/src/ocr_det.cpp
+++ b/deploy/cpp_infer/src/ocr_det.cpp
@@ -118,10 +118,10 @@ void DBDetector::Run(cv::Mat &img,
   auto preprocess_end = std::chrono::steady_clock::now();
     
   // Inference.
-  auto inference_start = std::chrono::steady_clock::now();
   auto input_names = this->predictor_->GetInputNames();
   auto input_t = this->predictor_->GetInputHandle(input_names[0]);
   input_t->Reshape({1, 3, resize_img.rows, resize_img.cols});
+  auto inference_start = std::chrono::steady_clock::now();
   input_t->CopyFromCpu(input.data());
   
   this->predictor_->Run();
@@ -165,8 +165,8 @@ void DBDetector::Run(cv::Mat &img,
       this->det_db_unclip_ratio_, this->use_polygon_score_);
 
   boxes = post_processor_.FilterTagDetRes(boxes, ratio_h, ratio_w, srcimg);
-  std::cout << "Detected boxes num: " << boxes.size() << endl;
   auto postprocess_end = std::chrono::steady_clock::now();
+  std::cout << "Detected boxes num: " << boxes.size() << endl;
 
   std::chrono::duration<float> preprocess_diff = preprocess_end - preprocess_start;
   times->push_back(double(preprocess_diff.count() * 1000));
diff --git a/deploy/cpp_infer/src/ocr_rec.cpp b/deploy/cpp_infer/src/ocr_rec.cpp
index 8b1b3ec307caf02fb9b357ad35280a28174da806..b64dcea5ae2a68485296c02cdb7689c60ea504f8 100644
--- a/deploy/cpp_infer/src/ocr_rec.cpp
+++ b/deploy/cpp_infer/src/ocr_rec.cpp
@@ -34,10 +34,10 @@ void CRNNRecognizer::Run(cv::Mat &img, std::vector<double> *times) {
   auto preprocess_end = std::chrono::steady_clock::now();
 
   // Inference.
-  auto inference_start = std::chrono::steady_clock::now();
   auto input_names = this->predictor_->GetInputNames();
   auto input_t = this->predictor_->GetInputHandle(input_names[0]);
   input_t->Reshape({1, 3, resize_img.rows, resize_img.cols});
+  auto inference_start = std::chrono::steady_clock::now();
   input_t->CopyFromCpu(input.data());
   this->predictor_->Run();
 
@@ -77,12 +77,12 @@ void CRNNRecognizer::Run(cv::Mat &img, std::vector<double> *times) {
     }
     last_index = argmax_idx;
   }
+  auto postprocess_end = std::chrono::steady_clock::now();
   score /= count;
   for (int i = 0; i < str_res.size(); i++) {
     std::cout << str_res[i];
   }
   std::cout << "\tscore: " << score << std::endl;
-  auto postprocess_end = std::chrono::steady_clock::now();
 
   std::chrono::duration<float> preprocess_diff = preprocess_end - preprocess_start;
   times->push_back(double(preprocess_diff.count() * 1000));
@@ -144,59 +144,4 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) {
   this->predictor_ = CreatePredictor(config);
 }
 
-cv::Mat CRNNRecognizer::GetRotateCropImage(const cv::Mat &srcimage,
-                                           std::vector<std::vector<int>> box) {
-  cv::Mat image;
-  srcimage.copyTo(image);
-  std::vector<std::vector<int>> points = box;
-
-  int x_collect[4] = {box[0][0], box[1][0], box[2][0], box[3][0]};
-  int y_collect[4] = {box[0][1], box[1][1], box[2][1], box[3][1]};
-  int left = int(*std::min_element(x_collect, x_collect + 4));
-  int right = int(*std::max_element(x_collect, x_collect + 4));
-  int top = int(*std::min_element(y_collect, y_collect + 4));
-  int bottom = int(*std::max_element(y_collect, y_collect + 4));
-
-  cv::Mat img_crop;
-  image(cv::Rect(left, top, right - left, bottom - top)).copyTo(img_crop);
-
-  for (int i = 0; i < points.size(); i++) {
-    points[i][0] -= left;
-    points[i][1] -= top;
-  }
-
-  int img_crop_width = int(sqrt(pow(points[0][0] - points[1][0], 2) +
-                                pow(points[0][1] - points[1][1], 2)));
-  int img_crop_height = int(sqrt(pow(points[0][0] - points[3][0], 2) +
-                                 pow(points[0][1] - points[3][1], 2)));
-
-  cv::Point2f pts_std[4];
-  pts_std[0] = cv::Point2f(0., 0.);
-  pts_std[1] = cv::Point2f(img_crop_width, 0.);
-  pts_std[2] = cv::Point2f(img_crop_width, img_crop_height);
-  pts_std[3] = cv::Point2f(0.f, img_crop_height);
-
-  cv::Point2f pointsf[4];
-  pointsf[0] = cv::Point2f(points[0][0], points[0][1]);
-  pointsf[1] = cv::Point2f(points[1][0], points[1][1]);
-  pointsf[2] = cv::Point2f(points[2][0], points[2][1]);
-  pointsf[3] = cv::Point2f(points[3][0], points[3][1]);
-
-  cv::Mat M = cv::getPerspectiveTransform(pointsf, pts_std);
-
-  cv::Mat dst_img;
-  cv::warpPerspective(img_crop, dst_img, M,
-                      cv::Size(img_crop_width, img_crop_height),
-                      cv::BORDER_REPLICATE);
-
-  if (float(dst_img.rows) >= float(dst_img.cols) * 1.5) {
-    cv::Mat srcCopy = cv::Mat(dst_img.rows, dst_img.cols, dst_img.depth());
-    cv::transpose(dst_img, srcCopy);
-    cv::flip(srcCopy, srcCopy, 0);
-    return srcCopy;
-  } else {
-    return dst_img;
-  }
-}
-
 } // namespace PaddleOCR