fix bad download link, opt lite doc

README.md

@@ -53,7 +53,7 @@ Mobile DEMO experience (based on EasyEdge and Paddle-Lite, supports iOS and Andr
 | ------------------------------------------------------------ | ---------------------------- | ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |
 | Chinese and English ultra-lightweight OCR model (8.1M)       | ch_ppocr_mobile_v1.1_xx      | Mobile & server   | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_pre.tar) |  
 | Chinese and English general OCR model (155.1M)               | ch_ppocr_server_v1.1_xx      | Server            | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/server/det/ch_ppocr_server_v1.1_det_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/server/det/ch_ppocr_server_v1.1_det_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_train.tar) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/server/rec/ch_ppocr_server_v1.1_rec_infer.tar) / [pre-trained model](https://paddleocr.bj.bcebos.com/20-09-22/server/rec/ch_ppocr_server_v1.1_rec_pre.tar) |  
-| Chinese and English ultra-lightweight compressed OCR model (3.5M) | ch_ppocr_mobile_slim_v1.1_xx | Mobile            | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/det/ch_ppocr_mobile_v1.1_det_prune_infer.tar) / [slim model](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/det/ch_ppocr_mobile_v1.1_det_prune_opt.nb) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_quant_infer.tar) / [slim model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_cls_quant_opt.nb) |    [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/rec/ch_ppocr_mobile_v1.1_rec_quant_infer.tar) / [slim model](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/rec/ch_ppocr_mobile_v1.1_rec_quant_opt.nb) |
+| Chinese and English ultra-lightweight compressed OCR model (3.5M) | ch_ppocr_mobile_slim_v1.1_xx | Mobile            | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/det/ch_ppocr_mobile_v1.1_det_prune_infer.tar) / [slim model](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/det/ch_ppocr_mobile_v1.1_det_prune_opt.nb) | [inference model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_quant_infer.tar) / [slim model](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_quant_opt.nb) |    [inference model](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/rec/ch_ppocr_mobile_v1.1_rec_quant_infer.tar) / [slim model](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/rec/ch_ppocr_mobile_v1.1_rec_quant_opt.nb) |
 
 For more model downloads (including multiple languages), please refer to [PP-OCR v1.1 series model downloads](./doc/doc_en/models_list_en.md)
 

README_ch.md

@@ -53,7 +53,7 @@ PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库，助力
 | ------------ | --------------- | ----------------|---- | ---------- | -------- |
 | 中英文超轻量OCR模型（8.1M） | ch_ppocr_mobile_v1.1_xx |移动端&服务器端|[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile/det/ch_ppocr_mobile_v1.1_det_train.tar)|[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_train.tar) |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile/rec/ch_ppocr_mobile_v1.1_rec_pre.tar)      |
 | 中英文通用OCR模型（155.1M）   |ch_ppocr_server_v1.1_xx|服务器端 |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/server/det/ch_ppocr_server_v1.1_det_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/server/det/ch_ppocr_server_v1.1_det_train.tar)          |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_train.tar)    |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/server/rec/ch_ppocr_server_v1.1_rec_infer.tar) / [预训练模型](https://paddleocr.bj.bcebos.com/20-09-22/server/rec/ch_ppocr_server_v1.1_rec_pre.tar)  |  
-| 中英文超轻量压缩OCR模型（3.5M） | ch_ppocr_mobile_slim_v1.1_xx| 移动端 |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/det/ch_ppocr_mobile_v1.1_det_prune_infer.tar) / [slim模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/det/ch_ppocr_mobile_v1.1_det_prune_opt.nb) |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_quant_infer.tar) / [slim模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_cls_quant_opt.nb)| [推理模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/rec/ch_ppocr_mobile_v1.1_rec_quant_infer.tar) / [slim模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/rec/ch_ppocr_mobile_v1.1_rec_quant_opt.nb)|  
+| 中英文超轻量压缩OCR模型（3.5M） | ch_ppocr_mobile_slim_v1.1_xx| 移动端 |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/det/ch_ppocr_mobile_v1.1_det_prune_infer.tar) / [slim模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/det/ch_ppocr_mobile_v1.1_det_prune_opt.nb) |[推理模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_quant_infer.tar) / [slim模型](https://paddleocr.bj.bcebos.com/20-09-22/cls/ch_ppocr_mobile_v1.1_cls_quant_opt.nb)| [推理模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/rec/ch_ppocr_mobile_v1.1_rec_quant_infer.tar) / [slim模型](https://paddleocr.bj.bcebos.com/20-09-22/mobile-slim/rec/ch_ppocr_mobile_v1.1_rec_quant_opt.nb)|  
 
 更多模型下载（包括多语言），可以参考[PP-OCR v1.1 系列模型下载](./doc/doc_ch/models_list.md)
 

deploy/lite/config.txt

 max_side_len  960
 det_db_thresh  0.3
 det_db_box_thresh  0.5
-det_db_unclip_ratio  1.6
+det_db_unclip_ratio  1.6
\ No newline at end of file
+use_direction_classify  0
\ No newline at end of file

deploy/lite/ocr_db_crnn.cc

@@ -114,6 +114,7 @@ cv::Mat RunClsModel(cv::Mat img, std::shared_ptr<PaddlePredictor> predictor_cls,
   cv::Mat srcimg;
   img.copyTo(srcimg);
   cv::Mat crop_img;
+  img.copyTo(crop_img);
   cv::Mat resize_img;
 
   int index = 0;
@@ -154,7 +155,8 @@ void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes, cv::Mat img,
                  std::vector<std::string> &rec_text,
                  std::vector<float> &rec_text_score,
                  std::vector<std::string> charactor_dict,
-                 std::shared_ptr<PaddlePredictor> predictor_cls) {
+                 std::shared_ptr<PaddlePredictor> predictor_cls,
+                 int use_direction_classify) {
   std::vector<float> mean = {0.5f, 0.5f, 0.5f};
   std::vector<float> scale = {1 / 0.5f, 1 / 0.5f, 1 / 0.5f};
 
@@ -166,7 +168,9 @@ void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes, cv::Mat img,
   int index = 0;
   for (int i = boxes.size() - 1; i >= 0; i--) {
     crop_img = GetRotateCropImage(srcimg, boxes[i]);
-    crop_img = RunClsModel(crop_img, predictor_cls);
+    if (use_direction_classify >= 1) {
+      crop_img = RunClsModel(crop_img, predictor_cls);
+    }
     float wh_ratio =
         static_cast<float>(crop_img.cols) / static_cast<float>(crop_img.rows);
 
@@ -378,6 +382,7 @@ int main(int argc, char **argv) {
 
   //// load config from txt file
   auto Config = LoadConfigTxt("./config.txt");
+  int use_direction_classify = int(Config["use_direction_classify"]);
 
   auto start = std::chrono::system_clock::now();
 
@@ -393,8 +398,9 @@ int main(int argc, char **argv) {
 
   std::vector<std::string> rec_text;
   std::vector<float> rec_text_score;
+
   RunRecModel(boxes, srcimg, rec_predictor, rec_text, rec_text_score,
-              charactor_dict, cls_predictor);
+              charactor_dict, cls_predictor, use_direction_classify);
 
   auto end = std::chrono::system_clock::now();
   auto duration =

deploy/lite/readme.md

@@ -79,7 +79,7 @@ inference_lite_lib.android.armv8/
 Paddle-Lite 提供了多种策略来自动优化原始的模型，其中包括量化、子图融合、混合调度、Kernel优选等方法，使用Paddle-lite的opt工具可以自动
 对inference模型进行优化，优化后的模型更轻量，模型运行速度更快。
 
-下述表格中提供了优化好的超轻量中文模型：
+下述表格中提供了一系列移动端模型：
 
 |模型版本|模型简介|模型大小|检测模型|文本方向分类模型|识别模型|Paddle-Lite版本|
 |-|-|-|-|-|-|-|
@@ -141,11 +141,9 @@ wget  https://paddleocr.bj.bcebos.com/ch_models/ch_rec_mv3_crnn_infer.tar && tar
 ./opt --model_file=./ch_rec_mv3_crnn/model --param_file=./ch_rec_mv3_crnn/params --optimize_out_type=naive_buffer --optimize_out=./ch_rec_mv3_crnn_opt --valid_targets=arm
 ```
 
-# 转换V1.1检测模型
-
 转换成功后，当前目录下会多出`.nb`结尾的文件，即是转换成功的模型文件。
 
-注意：使用paddle-lite部署时，需要使用opt工具优化后的模型。 opt 转换的输入模型是paddle保存的inference模型
+注意：使用paddle-lite部署时，需要使用opt工具优化后的模型。 opt 工具的输入模型是paddle保存的inference模型
 
 <a name="2.2与手机联调"></a>
 ### 2.2 与手机联调
@@ -204,7 +202,7 @@ demo/cxx/ocr/
 |   |--ch_ppocr_mobile_v1.1_rec_quant_opt.nb           优化后的识别模型文件
 |   |--ch_ppocr_mobile_cls_quant_opt.nb                优化后的文字方向分类器模型文件
 |   |--11.jpg                           待测试图像
-|   |--ppocr_keys_v1.txt                字典文件
+|   |--ppocr_keys_v1.txt                中文字典文件
 |   |--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
@@ -214,7 +212,27 @@ demo/cxx/ocr/
 |-- db_post_process.h
 |-- Makefile                    编译文件
 |-- ocr_db_crnn.cc              C++预测源文件
+```
 
+#### 注意：
+1. ppocr_keys_v1.txt是中文字典文件，如果使用的 nb 模型是英文数字或其他语言的模型，需要更换为对应语言的字典。
+PaddleOCR 在ppocr/utils/下存放了多种字典，包括：
+```
+french_dict.txt     # 法语字典
+german_dict.txt     # 德语字典
+ic15_dict.txt       # 英文字典
+japan_dict.txt      # 日语字典
+korean_dict.txt     # 韩语字典
+ppocr_keys_v1.txt   # 中文字典
+```
+
+2.  `config.txt` 包含了检测器、分类器的超参数，如下：
+```
+max_side_len  960         # 输入图像长宽大于960时，等比例缩放图像，使得图像最长边为960
+det_db_thresh  0.3        # 用于过滤DB预测的二值化图像，设置为0.-0.3对结果影响不明显
+det_db_box_thresh  0.5    # DB后处理过滤box的阈值，如果检测存在漏框情况，可酌情减小
+det_db_unclip_ratio  1.6  # 表示文本框的紧致程度，越小则文本框更靠近文本
+use_direction_classify  1  # 是否使用方向分类器，0表示不使用，1表示使用
 ```
 
  5. 启动调试
@@ -224,7 +242,7 @@ demo/cxx/ocr/
  ```
  # 执行编译，得到可执行文件ocr_db_crnn
  # ocr_db_crnn可执行文件的使用方式为:
- # ./ocr_db_crnn  检测模型文件  识别模型文件  测试图像路径
+ # ./ocr_db_crnn  检测模型文件 方向分类器模型文件  识别模型文件  测试图像路径  字典文件路径
  make -j
  # 将编译的可执行文件移动到debug文件夹中
  mv ocr_db_crnn ./debug/

deploy/lite/readme_en.md

@@ -178,6 +178,28 @@ demo/cxx/ocr/
 
 ```
 
+#### Note:
+1. ppocr_keys_v1.txt is a Chinese dictionary file.
+If the nb model is used for English recognition or other language recognition, dictionary file should be replaced with a dictionary of the corresponding language.
+PaddleOCR provides a variety of dictionaries under ppocr/utils/, including:
+```
+french_dict.txt     # french
+german_dict.txt     # german
+ic15_dict.txt       # english
+japan_dict.txt      # japan
+korean_dict.txt     # korean
+ppocr_keys_v1.txt   # chinese
+```
+
+2. `config.txt`  of the detector and classifier, as shown below:
+```
+max_side_len  960         #  Limit the maximum image height and width to 960
+det_db_thresh  0.3        # Used to filter the binarized image of DB prediction, setting 0.-0.3 has no obvious effect on the result
+det_db_box_thresh  0.5    # DDB post-processing filter box threshold, if there is a missing box detected, it can be reduced as appropriate
+det_db_unclip_ratio  1.6  # Indicates the compactness of the text box, the smaller the value, the closer the text box to the text
+use_direction_classify  1  # Whether to use the direction classifier, 0 means not to use, 1 means to use
+```
+
 5. Run Model on phone
 
 ```