update .gitignore and delete unused code

.gitignore

@@ -19,3 +19,4 @@ output/
 
 *.log
 .clang-format
+.clang_format.hook

deploy/lite/ocr_db_crnn.cc

@@ -12,8 +12,8 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include <chrono>
 #include "paddle_api.h" // NOLINT
+#include <chrono>
 
 #include "crnn_process.h"
 #include "db_post_process.h"
@@ -22,9 +22,7 @@ using namespace paddle::lite_api;  // NOLINT
 using namespace std;
 
 // fill tensor with mean and scale and trans layout: nhwc -> nchw, neon speed up
-void neon_mean_scale(const float* din,
-                     float* dout,
-                     int size,
+void neon_mean_scale(const float *din, float *dout, int size,
                      const std::vector<float> mean,
                      const std::vector<float> scale) {
   if (mean.size() != 3 || scale.size() != 3) {
@@ -68,8 +66,7 @@ void neon_mean_scale(const float* din,
 }
 
 // resize image to a size multiple of 32 which is required by the network
-cv::Mat DetResizeImg(const cv::Mat img,
-                     int max_size_len,
+cv::Mat DetResizeImg(const cv::Mat img, int max_size_len,
                      std::vector<float> &ratio_hw) {
   int w = img.cols;
   int h = img.rows;
@@ -108,11 +105,9 @@ cv::Mat DetResizeImg(const cv::Mat img,
   return resize_img;
 }
 
-void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes,
-                 cv::Mat img,
+void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes, cv::Mat img,
                  std::shared_ptr<PaddlePredictor> predictor_crnn,
-                 std::string dict_path,
-                 std::vector<std::string>& rec_text,
+                 std::string dict_path, std::vector<std::string> &rec_text,
                  std::vector<float> &rec_text_score) {
   std::vector<float> mean = {0.5f, 0.5f, 0.5f};
   std::vector<float> scale = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f};
@@ -139,8 +134,8 @@ void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes,
     input_tensor0->Resize({1, 3, resize_img.rows, resize_img.cols});
     auto *data0 = input_tensor0->mutable_data<float>();
 
-    neon_mean_scale(
-        dimg, data0, resize_img.rows * resize_img.cols, mean, scale);
+    neon_mean_scale(dimg, data0, resize_img.rows * resize_img.cols, mean,
+                    scale);
     //// Run CRNN predictor
     predictor_crnn->Run();
 
@@ -158,7 +153,8 @@ void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes,
       pred_idx.push_back(int(rec_idx[n]));
     }
 
-    if (pred_idx.size() < 1e-3) continue;
+    if (pred_idx.size() < 1e-3)
+      continue;
 
     index += 1;
     std::string pred_txt = "";
@@ -198,9 +194,8 @@ void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes,
   }
 }
 
-std::vector<std::vector<std::vector<int>>> RunDetModel(
-    std::shared_ptr<PaddlePredictor> predictor,
-    cv::Mat img,
+std::vector<std::vector<std::vector<int>>>
+RunDetModel(std::shared_ptr<PaddlePredictor> predictor, cv::Mat img,
             std::map<std::string, double> Config) {
   // Read img
   int max_side_len = int(Config["max_side_len"]);
@@ -232,12 +227,6 @@ std::vector<std::vector<std::vector<int>>> RunDetModel(
   auto *outptr = output_tensor->data<float>();
   auto shape_out = output_tensor->shape();
 
-  int64_t out_numl = 1;
-  double sum = 0;
-  for (auto i : shape_out) {
-    out_numl *= i;
-  }
-
   // Save output
   float pred[shape_out[2]][shape_out[3]];
   unsigned char cbuf[shape_out[2]][shape_out[3]];
@@ -289,16 +278,16 @@ cv::Mat Visualization(cv::Mat srcimg,
     cv::polylines(img_vis, ppt, npt, 1, 1, CV_RGB(0, 255, 0), 2, 8, 0);
   }
 
-  cv::imwrite("./imgs/vis.jpg", img_vis);
-  std::cout << "The detection visualized image saved in ./imgs/vis.jpg"
-            << std::endl;
+  cv::imwrite("./vis.jpg", img_vis);
+  std::cout << "The detection visualized image saved in ./vis.jpg" << std::endl;
   return img_vis;
 }
 
 std::vector<std::string> split(const std::string &str,
                                const std::string &delim) {
   std::vector<std::string> res;
-  if ("" == str) return res;
+  if ("" == str)
+    return res;
   char *strs = new char[str.length() + 1];
   std::strcpy(strs, str.c_str());
 
@@ -350,8 +339,8 @@ int main(int argc, char** argv) {
 
   std::vector<std::string> rec_text;
   std::vector<float> rec_text_score;
-  RunRecModel(
-      boxes, srcimg, rec_predictor, dict_path, rec_text, rec_text_score);
+  RunRecModel(boxes, srcimg, rec_predictor, dict_path, rec_text,
+              rec_text_score);
 
   auto end = std::chrono::system_clock::now();
   auto duration =