update

deploy/lite/crnn_process.cc

@@ -12,14 +12,14 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "crnn_process.h"  //NOLINT
+#include "crnn_process.h" //NOLINT
 #include <algorithm>
 #include <memory>
 #include <string>
 
 const std::vector<int> rec_image_shape{3, 32, 320};
 
-cv::Mat CrnnResizeNormImg(cv::Mat img, float wh_ratio) {
+cv::Mat CrnnResizeNormImg(cv::Mat img, float wh_ratio, bool is_norm) {
   int imgC, imgH, imgW;
   imgC = rec_image_shape[0];
   imgW = rec_image_shape[2];
@@ -34,54 +34,31 @@ cv::Mat CrnnResizeNormImg(cv::Mat img, float wh_ratio) {
   else
     resize_w = int(ceilf(imgH * ratio));
   cv::Mat resize_img;
-  cv::resize(
-      img, resize_img, cv::Size(resize_w, imgH), 0.f, 0.f, cv::INTER_CUBIC);
+  cv::resize(img, resize_img, cv::Size(resize_w, imgH), 0.f, 0.f,
+             cv::INTER_LINEAR);
 
-  resize_img.convertTo(resize_img, CV_32FC3, 1 / 255.f);
+  if (!is_norm) {
+    return resize_img;
+  } else {
+    resize_img.convertTo(resize_img, CV_32FC3, 1 / 255.f);
 
-  for (int h = 0; h < resize_img.rows; h++) {
-    for (int w = 0; w < resize_img.cols; w++) {
-      resize_img.at<cv::Vec3f>(h, w)[0] =
-          (resize_img.at<cv::Vec3f>(h, w)[0] - 0.5) * 2;
-      resize_img.at<cv::Vec3f>(h, w)[1] =
-          (resize_img.at<cv::Vec3f>(h, w)[1] - 0.5) * 2;
-      resize_img.at<cv::Vec3f>(h, w)[2] =
-          (resize_img.at<cv::Vec3f>(h, w)[2] - 0.5) * 2;
+    for (int h = 0; h < resize_img.rows; h++) {
+      for (int w = 0; w < resize_img.cols; w++) {
+        resize_img.at<cv::Vec3f>(h, w)[0] =
+            (resize_img.at<cv::Vec3f>(h, w)[0] - 0.5) * 2;
+        resize_img.at<cv::Vec3f>(h, w)[1] =
+            (resize_img.at<cv::Vec3f>(h, w)[1] - 0.5) * 2;
+        resize_img.at<cv::Vec3f>(h, w)[2] =
+            (resize_img.at<cv::Vec3f>(h, w)[2] - 0.5) * 2;
+      }
     }
+
+    cv::Mat dist;
+    cv::copyMakeBorder(resize_img, dist, 0, 0, 0, int(imgW - resize_w),
+                       cv::BORDER_CONSTANT, {0, 0, 0});
+
+    return dist;
   }
-
-  cv::Mat dist;
-  cv::copyMakeBorder(resize_img,
-                     dist,
-                     0,
-                     0,
-                     0,
-                     int(imgW - resize_w),
-                     cv::BORDER_CONSTANT,
-                     {0, 0, 0});
-
-  return dist;
-}
-
-cv::Mat CrnnResizeImg(cv::Mat img, float wh_ratio) {
-  int imgC, imgH, imgW;
-  imgC = rec_image_shape[0];
-  imgW = rec_image_shape[2];
-  imgH = rec_image_shape[1];
-
-  imgW = int(32 * wh_ratio);
-
-  float ratio = float(img.cols) / float(img.rows);
-  int resize_w, resize_h;
-  if (ceilf(imgH * ratio) > imgW)
-    resize_w = imgW;
-  else
-    resize_w = int(ceilf(imgH * ratio));
-  cv::Mat resize_img;
-  cv::resize(
-      img, resize_img, cv::Size(resize_w, imgH), 0.f, 0.f, cv::INTER_LINEAR);
-
-  return resize_img;
 }
 
 std::vector<std::string> ReadDict(std::string path) {
@@ -140,9 +117,7 @@ cv::Mat GetRotateCropImage(cv::Mat srcimage,
   cv::Mat M = cv::getPerspectiveTransform(pointsf, pts_std);
 
   cv::Mat dst_img;
-  cv::warpPerspective(img_crop,
-                      dst_img,
-                      M,
+  cv::warpPerspective(img_crop, dst_img, M,
                       cv::Size(img_crop_width, img_crop_height),
                       cv::BORDER_REPLICATE);
 

deploy/lite/crnn_process.h

@@ -21,14 +21,12 @@
 #include <string>
 #include <vector>
 
-#include "math.h"  //NOLINT
+#include "math.h" //NOLINT
 #include "opencv2/core.hpp"
 #include "opencv2/imgcodecs.hpp"
 #include "opencv2/imgproc.hpp"
 
-cv::Mat CrnnResizeNormImg(cv::Mat img, float wh_ratio);
-
-cv::Mat CrnnResizeImg(cv::Mat img, float wh_ratio);
+cv::Mat CrnnResizeNormImg(cv::Mat img, float wh_ratio, bool is_norm);
 
 std::vector<std::string> ReadDict(std::string path);
 

deploy/lite/db_post_process.cc

@@ -276,4 +276,4 @@ FilterTagDetRes(std::vector<std::vector<std::vector<int>>> boxes, float ratio_h,
     root_points.push_back(boxes[n]);
   }
   return root_points;
-}
+}

deploy/lite/ocr_db_crnn.cc

@@ -107,8 +107,9 @@ cv::Mat DetResizeImg(const cv::Mat img, int max_size_len,
 
 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::vector<float> &rec_text_score) {
+                 std::vector<std::string> &rec_text,
+                 std::vector<float> &rec_text_score,
+                 std::vector<std::string> charactor_dict) {
   std::vector<float> mean = {0.5f, 0.5f, 0.5f};
   std::vector<float> scale = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f};
 
@@ -117,14 +118,12 @@ void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes, cv::Mat img,
   cv::Mat crop_img;
   cv::Mat resize_img;
 
-  auto charactor_dict = ReadDict(dict_path);
-
   int index = 0;
   for (int i = boxes.size() - 1; i >= 0; i--) {
     crop_img = GetRotateCropImage(srcimg, boxes[i]);
     float wh_ratio = float(crop_img.cols) / float(crop_img.rows);
 
-    resize_img = CrnnResizeImg(crop_img, wh_ratio);
+    resize_img = CrnnResizeNormImg(crop_img, wh_ratio, false);
     resize_img.convertTo(resize_img, CV_32FC3, 1 / 255.f);
 
     const float *dimg = reinterpret_cast<const float *>(resize_img.data);
@@ -227,13 +226,12 @@ RunDetModel(std::shared_ptr<PaddlePredictor> predictor, cv::Mat img,
   auto shape_out = output_tensor->shape();
 
   // Save output
-  float pred[shape_out[2]][shape_out[3]];
-  unsigned char cbuf[shape_out[2]][shape_out[3]];
+  float pred[shape_out[2] * shape_out[3]];
+  unsigned char cbuf[shape_out[2] * shape_out[3]];
 
   for (int i = 0; i < int(shape_out[2] * shape_out[3]); i++) {
-    pred[int(i / int(shape_out[3]))][int(i % shape_out[3])] = float(outptr[i]);
-    cbuf[int(i / int(shape_out[3]))][int(i % shape_out[3])] =
-        (unsigned char)((outptr[i]) * 255);
+    pred[i] = float(outptr[i]);
+    cbuf[i] = (unsigned char)((outptr[i]) * 255);
   }
 
   cv::Mat cbuf_map(shape_out[2], shape_out[3], CV_8UC1, (unsigned char *)cbuf);
@@ -333,13 +331,15 @@ int main(int argc, char **argv) {
   auto det_predictor = loadModel(det_model_file);
   auto rec_predictor = loadModel(rec_model_file);
 
+  auto charactor_dict = ReadDict(dict_path);
+
   cv::Mat srcimg = cv::imread(img_path, cv::IMREAD_COLOR);
   auto boxes = RunDetModel(det_predictor, srcimg, Config);
 
   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, rec_text, rec_text_score,
+              charactor_dict);
 
   auto end = std::chrono::system_clock::now();
   auto duration =

deploy/lite/readme.md

@@ -1,6 +1,6 @@
-# PaddleOCR 模型部署
+# PaddleOCR 端侧模型部署
 
-PaddleOCR是集训练、预测、端侧部署于一体的实用OCR工具库。本教程将介绍在安卓移动端部署PaddleOCR超轻量中文检测、识别模型的主要流程。
+本教程将介绍在移动端部署PaddleOCR超轻量中文检测、识别模型的详细步骤。
 
 
 ## 1. 准备环境
@@ -159,6 +159,7 @@ demo/cxx/ocr/
 |   |--11.jpg                           待测试图像
 |   |--ppocr_keys_v1.txt                字典文件
 |   |--libpaddle_light_api_shared.so    C++预测库文件
+|   |--config.txt                       DB-CRNN超参数配置
 |-- config.txt                  DB-CRNN超参数配置
 |-- crnn_process.cc             识别模型CRNN的预处理和后处理文件
 |-- crnn_process.h