diff --git a/deploy/lite/ocr_db_crnn.cc b/deploy/lite/ocr_db_crnn.cc
index 011d4adbeb65732f12c263ddfec94afb84bf5969..0de953a4d9e2d52f8a2e43c71f3872d998e72b0b 100644
--- a/deploy/lite/ocr_db_crnn.cc
+++ b/deploy/lite/ocr_db_crnn.cc
@@ -172,7 +172,10 @@ void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes, cv::Mat img,
   cv::Mat resize_img;
 
   int index = 0;
+
+  std::vector<double> time_info = {0, 0, 0};
   for (int i = boxes.size() - 1; i >= 0; i--) {
+    auto preprocess_start = std::chrono::steady_clock::now();
     crop_img = GetRotateCropImage(srcimg, boxes[i]);
     if (use_direction_classify >= 1) {
       crop_img = RunClsModel(crop_img, predictor_cls);
@@ -191,7 +194,9 @@ void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes, cv::Mat img,
     auto *data0 = input_tensor0->mutable_data<float>();
 
     NeonMeanScale(dimg, data0, resize_img.rows * resize_img.cols, mean, scale);
+    auto preprocess_end = std::chrono::steady_clock::now();
     //// Run CRNN predictor
+    auto inference_start = std::chrono::steady_clock::now();
     predictor_crnn->Run();
 
     // Get output and run postprocess
@@ -199,8 +204,10 @@ void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes, cv::Mat img,
         std::move(predictor_crnn->GetOutput(0)));
     auto *predict_batch = output_tensor0->data<float>();
     auto predict_shape = output_tensor0->shape();
+    auto inference_end = std::chrono::steady_clock::now();
 
     // ctc decode
+    auto postprocess_start = std::chrono::steady_clock::now();
     std::string str_res;
     int argmax_idx;
     int last_index = 0;
@@ -224,7 +231,20 @@ void RunRecModel(std::vector<std::vector<std::vector<int>>> boxes, cv::Mat img,
     score /= count;
     rec_text.push_back(str_res);
     rec_text_score.push_back(score);
+    auto postprocess_end = std::chrono::steady_clock::now();
+
+    std::chrono::duration<float> preprocess_diff = preprocess_end - preprocess_start;
+    time_info[0] += double(preprocess_diff.count() * 1000);
+    std::chrono::duration<float> inference_diff = inference_end - inference_start;
+    time_info[1] += double(inference_diff.count() * 1000);
+    std::chrono::duration<float> postprocess_diff = postprocess_end - postprocess_start;
+    time_info[2] += double(postprocess_diff.count() * 1000);
+
   }
+
+times->push_back(time_info[0]);
+times->push_back(time_info[1]);
+times->push_back(time_info[2]);
 }
 
 std::vector<std::vector<std::vector<int>>>
@@ -312,7 +332,7 @@ std::shared_ptr<PaddlePredictor> loadModel(std::string model_file, int num_threa
   config.set_model_from_file(model_file);
 
   config.set_threads(num_threads);
-
+  std::cout<<num_threads<<std::endl;
   std::shared_ptr<PaddlePredictor> predictor =
       CreatePaddlePredictor<MobileConfig>(config);
   return predictor;
@@ -434,6 +454,9 @@ void system(char **argv){
   auto rec_predictor = loadModel(rec_model_file, std::stoi(num_threads));
   auto cls_predictor = loadModel(cls_model_file, std::stoi(num_threads));
 
+  std::vector<double> det_time_info = {0, 0, 0};
+  std::vector<double> rec_time_info = {0, 0, 0};
+
   for (int i = 0; i < cv_all_img_names.size(); ++i) {
     std::cout << "The predict img: " << cv_all_img_names[i] << std::endl;
     cv::Mat srcimg = cv::imread(cv_all_img_names[i], cv::IMREAD_COLOR);
@@ -459,8 +482,38 @@ void system(char **argv){
     //// print recognized text
     for (int i = 0; i < rec_text.size(); i++) {
       std::cout << i << "\t" << rec_text[i] << "\t" << rec_text_score[i]
-                << std::endl;
+                <<  std::endl;
+
     }
+
+    det_time_info[0] += det_times[0];
+    det_time_info[1] += det_times[1];
+    det_time_info[2] += det_times[2];
+    rec_time_info[0] += rec_times[0];
+    rec_time_info[1] += rec_times[1];
+    rec_time_info[2] += rec_times[2];
+  }
+  if (strcmp(argv[12], "True") == 0) {
+    AutoLogger autolog_det(det_model_file, 
+                       runtime_device,
+                       std::stoi(num_threads),
+                       std::stoi(batchsize), 
+                       "dynamic", 
+                       precision, 
+                       det_time_info, 
+                       cv_all_img_names.size());
+    AutoLogger autolog_rec(rec_model_file, 
+                       runtime_device,
+                       std::stoi(num_threads),
+                       std::stoi(batchsize), 
+                       "dynamic", 
+                       precision, 
+                       rec_time_info, 
+                       cv_all_img_names.size());
+
+    autolog_det.report();
+    std::cout << std::endl;
+    autolog_rec.report();
   }
 }
 
@@ -503,15 +556,15 @@ void det(int argc, char **argv) {
     auto img_vis = Visualization(srcimg, boxes);
     std::cout << boxes.size() << " bboxes have detected:" << std::endl;
 
-    // for (int i=0; i<boxes.size(); i++){
-    //   std::cout << "The " << i << " box:" << std::endl;
-    //   for (int j=0; j<4; j++){
-    //     for (int k=0; k<2; k++){
-    //       std::cout << boxes[i][j][k] << "\t";
-    //     }
-    //   }
-    //   std::cout << std::endl;
-    // }
+    for (int i=0; i<boxes.size(); i++){
+      std::cout << "The " << i << " box:" << std::endl;
+      for (int j=0; j<4; j++){
+        for (int k=0; k<2; k++){
+          std::cout << boxes[i][j][k] << "\t";
+        }
+      }
+      std::cout << std::endl;
+    }
     time_info[0] += times[0];
     time_info[1] += times[1];
     time_info[2] += times[2];
@@ -585,6 +638,9 @@ void rec(int argc, char **argv) {
       std::cout << i << "\t" << rec_text[i] << "\t" << rec_text_score[i]
                 << std::endl;
     }
+    time_info[0] += times[0];
+    time_info[1] += times[1];
+    time_info[2] += times[2];
   }
   // TODO: support autolog
   if (strcmp(argv[9], "True") == 0) {
diff --git a/test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_cpu.txt b/test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_cpu.txt
index af71ce3b870e27f9dc046f00a53f266950f6f112..51a9c1b1ce1c8a4610dc1fa33520a9eea31533c2 100644
--- a/test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_cpu.txt
+++ b/test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_cpu.txt
@@ -1,11 +1,12 @@
 ===========================lite_params===========================
 inference:./ocr_db_crnn det
-infer_model:ch_PP-OCRv2_det_infer|ch_PP-OCRv2_det_slim_quant_infer
 runtime_device:ARM_CPU
+det_infer_model:ch_PP-OCRv2_det_infer|ch_PP-OCRv2_det_slim_quant_infer
+rec_infer_model:ch_PP-OCRv2_rec_infer|ch_PP-OCRv2_rec_slim_quant_infer
+cls_infer_model:ch_ppocr_mobile_v2.0_cls_infer|ch_ppocr_mobile_v2.0_cls_slim_infer
 --cpu_threads:1|4
 --det_batch_size:1
 --rec_batch_size:1
---system_batch_size:1
 --image_dir:./test_data/icdar2015_lite/text_localization/ch4_test_images/
 --config_dir:./config.txt
 --rec_dict_dir:./ppocr_keys_v1.txt
diff --git a/test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_gpu_opencl.txt b/test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_gpu_opencl.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3ee00bc729658b1bed05cb3532f01222e8ec2668
--- /dev/null
+++ b/test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_gpu_opencl.txt
@@ -0,0 +1,13 @@
+===========================lite_params===========================
+inference:./ocr_db_crnn det
+runtime_device:ARM_GPU_OPENCL
+det_infer_model:ch_PP-OCRv2_det_infer|ch_PP-OCRv2_det_slim_quant_infer
+rec_infer_model:ch_PP-OCRv2_rec_infer|ch_PP-OCRv2_rec_slim_quant_infer
+cls_infer_model:ch_ppocr_mobile_v2.0_cls_infer|ch_ppocr_mobile_v2.0_cls_slim_infer
+--cpu_threads:1|4
+--det_batch_size:1
+--rec_batch_size:1
+--image_dir:./test_data/icdar2015_lite/text_localization/ch4_test_images/
+--config_dir:./config.txt
+--rec_dict_dir:./ppocr_keys_v1.txt
+--benchmark:True
diff --git a/test_tipc/configs/ppocr_system_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_cpu.txt b/test_tipc/configs/ppocr_system_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_cpu.txt
new file mode 100644
index 0000000000000000000000000000000000000000..d03ee1e8b0493ab0f3ca2b8c4bb55b6b0cfecdcc
--- /dev/null
+++ b/test_tipc/configs/ppocr_system_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_cpu.txt
@@ -0,0 +1,13 @@
+===========================lite_params===========================
+inference:./ocr_db_crnn system
+runtime_device:ARM_CPU
+det_infer_model:ch_PP-OCRv2_det_infer|ch_PP-OCRv2_det_slim_quant_infer
+rec_infer_model:ch_PP-OCRv2_rec_infer|ch_PP-OCRv2_rec_slim_quant_infer
+cls_infer_model:ch_ppocr_mobile_v2.0_cls_infer|ch_ppocr_mobile_v2.0_cls_slim_infer
+--cpu_threads:1|4
+--det_batch_size:1
+--rec_batch_size:1
+--image_dir:./test_data/icdar2015_lite/text_localization/ch4_test_images/
+--config_dir:./config.txt
+--rec_dict_dir:./ppocr_keys_v1.txt
+--benchmark:True
diff --git a/test_tipc/configs/ppocr_system_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_gpu_opencl.txt b/test_tipc/configs/ppocr_system_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_gpu_opencl.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a9fcafbf17878ec7ea42691359aa6ae36ccd522e
--- /dev/null
+++ b/test_tipc/configs/ppocr_system_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_gpu_opencl.txt
@@ -0,0 +1,13 @@
+===========================lite_params===========================
+inference:./ocr_db_crnn system
+runtime_device:ARM_GPU_OPENCL
+det_infer_model:ch_PP-OCRv2_det_infer|ch_PP-OCRv2_det_slim_quant_infer
+rec_infer_model:ch_PP-OCRv2_rec_infer|ch_PP-OCRv2_rec_slim_quant_infer
+cls_infer_model:ch_ppocr_mobile_v2.0_cls_infer|ch_ppocr_mobile_v2.0_cls_slim_infer
+--cpu_threads:1|4
+--det_batch_size:1
+--rec_batch_size:1
+--image_dir:./test_data/icdar2015_lite/text_localization/ch4_test_images/
+--config_dir:./config.txt
+--rec_dict_dir:./ppocr_keys_v1.txt
+--benchmark:True
diff --git a/test_tipc/docs/test_lite_arm_cpu_cpp.md b/test_tipc/docs/test_lite_arm_cpp.md
similarity index 51%
rename from test_tipc/docs/test_lite_arm_cpu_cpp.md
rename to test_tipc/docs/test_lite_arm_cpp.md
index 6f58026a315dabb8810e56b6d694733c1c72019c..2125e17cc6857ce2f156d9403e8f7a339779dc9c 100644
--- a/test_tipc/docs/test_lite_arm_cpu_cpp.md
+++ b/test_tipc/docs/test_lite_arm_cpp.md
@@ -1,6 +1,6 @@
-# Lite\_arm\_cpu\_cpp预测功能测试
+# Lite\_arm\_cpp预测功能测试
 
-Lite\_arm\_cpu\_cpp预测功能测试的主程序为`test_lite_arm_cpu_cpp.sh`，可以在ARM CPU上基于Lite预测库测试模型的C++推理功能。
+Lite\_arm\_cpp预测功能测试的主程序为`test_lite_arm_cpp.sh`，可以在ARM CPU上基于Lite预测库测试模型的C++推理功能。
 
 ## 1. 测试结论汇总
 
@@ -12,10 +12,11 @@ Lite\_arm\_cpu\_cpp预测功能测试的主程序为`test_lite_arm_cpu_cpp.sh`
 - threads：包括1和4
 - predictor数量：包括多predictor预测和单predictor预测
 - 预测库来源：包括下载方式和编译方式
+- 测试硬件：ARM\_CPU/ARM\_GPU_OPENCL
 
-| 模型类型 | batch-size | threads | predictor数量 | 预测库来源 |
-|  :----:   |  :----:  | :----:  |  :----:  |  :----:  |
-| 正常模型/量化模型 | 1 | 1/4 |  1 | 下载方式 |
+| 模型类型 | batch-size | threads | predictor数量 | 预测库来源 | 测试硬件 |
+|  :----:   |  :----:  | :----:  |  :----:  |  :----:  |  :----:  |
+| 正常模型/量化模型 | 1 | 1/4 |  1/2 | 下载方式 | ARM\_CPU/ARM\_GPU_OPENCL |
 
 
 ## 2. 测试流程
@@ -23,19 +24,38 @@ Lite\_arm\_cpu\_cpp预测功能测试的主程序为`test_lite_arm_cpu_cpp.sh`
 
 ### 2.1 功能测试
 
-先运行`prepare_lite.sh`，运行后会在当前路径下生成`test_lite.tar`，其中包含了测试数据、测试模型和用于预测的可执行文件。将`test_lite.tar`上传到被测试的手机上，在手机的终端解压该文件，进入`test_lite`目录中，然后运行`test_lite_arm_cpu_cpp.sh`进行测试，最终在`test_lite/output`目录下生成`lite_*.log`后缀的日志文件。
+先运行`prepare_lite_cpp.sh`，运行后会在当前路径下生成`test_lite.tar`，其中包含了测试数据、测试模型和用于预测的可执行文件。将`test_lite.tar`上传到被测试的手机上，在手机的终端解压该文件，进入`test_lite`目录中，然后运行`test_lite_arm_cpp.sh`进行测试，最终在`test_lite/output`目录下生成`lite_*.log`后缀的日志文件。
+
+#### 2.1.1 测试ARM\_CPU
 
 ```shell
 
 # 数据和模型准备
-bash test_tipc/prepare_lite.sh ./test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_cpu.txt
+bash test_tipc/prepare_lite_cpp.sh ./test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_cpu.txt
 
 # 手机端测试:
-bash test_lite_arm_cpu_cpp.sh model_linux_gpu_normal_normal_lite_cpp_arm_cpu.txt
+bash test_lite_arm_cpp.sh model_linux_gpu_normal_normal_lite_cpp_arm_cpu.txt
 
 ```  
 
-**注意**：由于运行该项目需要bash等命令，传统的adb方式不能很好的安装。所以此处推荐通在手机上开启虚拟终端的方式连接电脑，连接方式可以参考[安卓手机termux连接电脑](./termux_for_android.md)。
+#### 2.1.2 ARM\_GPU\_OPENCL
+
+```shell
+
+# 数据和模型准备
+bash test_tipc/prepare_lite_cpp.sh ./test_tipc/configs/ppocr_det_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_gpu_opencl.txt
+
+# 手机端测试:
+bash test_lite_arm_cpp.sh model_linux_gpu_normal_normal_lite_cpp_arm_gpu_opencl.txt
+
+```  
+
+
+**注意**：
+
+1.由于运行该项目需要bash等命令，传统的adb方式不能很好的安装。所以此处推荐通在手机上开启虚拟终端的方式连接电脑，连接方式可以参考[安卓手机termux连接电脑](./termux_for_android.md)。
+
+2.如果测试文本检测和识别完整的pipeline，在执行`prepare_lite_cpp.sh`时，配置文件需替换为`test_tipc/configs/ppocr_system_mobile/model_linux_gpu_normal_normal_lite_cpp_arm_cpu.tx`。在手机端测试阶段，配置文件同样修改为该文件。
 
 #### 运行结果
 
diff --git a/test_tipc/prepare_lite.sh b/test_tipc/prepare_lite.sh
deleted file mode 100644
index 6a08d96298592c829547df9fa30ef4149ddc5b00..0000000000000000000000000000000000000000
--- a/test_tipc/prepare_lite.sh
+++ /dev/null
@@ -1,55 +0,0 @@
-#!/bin/bash
-source ./test_tipc/common_func.sh
-FILENAME=$1
-dataline=$(cat ${FILENAME})
-# parser params
-IFS=$'\n'
-lines=(${dataline})
-IFS=$'\n'
-lite_model_list=$(func_parser_value "${lines[2]}")
-
-# prepare lite .nb model
-pip install paddlelite==2.9
-current_dir=${PWD}
-IFS="|"
-model_path=./inference_models
-for model in ${lite_model_list[*]}; do
-    inference_model_url=https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/${model}.tar
-    inference_model=${inference_model_url##*/}
-    wget -nc  -P ${model_path} ${inference_model_url}
-    cd ${model_path} && tar -xf ${inference_model} && cd ../
-    model_dir=${model_path}/${inference_model%.*}
-    model_file=${model_dir}/inference.pdmodel
-    param_file=${model_dir}/inference.pdiparams
-    paddle_lite_opt --model_dir=${model_dir} --model_file=${model_file} --param_file=${param_file} --valid_targets=arm --optimize_out=${model_dir}_opt
-done
-
-# prepare test data
-data_url=https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar
-model_path=./inference_models
-inference_model=${inference_model_url##*/}
-data_file=${data_url##*/}
-wget -nc  -P ./inference_models ${inference_model_url}
-wget -nc  -P ./test_data ${data_url}
-cd ./inference_models && tar -xf ${inference_model} && cd ../
-cd ./test_data && tar -xf ${data_file} && rm ${data_file} && cd ../
-
-# prepare lite env
-paddlelite_url=https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.9/inference_lite_lib.android.armv8.gcc.c++_shared.with_extra.with_cv.tar.gz
-paddlelite_zipfile=$(echo $paddlelite_url | awk -F "/" '{print $NF}')
-paddlelite_file=${paddlelite_zipfile:0:66}
-wget ${paddlelite_url} && tar -xf ${paddlelite_zipfile}
-mkdir -p  ${paddlelite_file}/demo/cxx/ocr/test_lite
-cp -r ${model_path}/*_opt.nb test_data ${paddlelite_file}/demo/cxx/ocr/test_lite
-cp ppocr/utils/ppocr_keys_v1.txt deploy/lite/config.txt ${paddlelite_file}/demo/cxx/ocr/test_lite
-cp -r ./deploy/lite/* ${paddlelite_file}/demo/cxx/ocr/
-cp ${paddlelite_file}/cxx/lib/libpaddle_light_api_shared.so ${paddlelite_file}/demo/cxx/ocr/test_lite
-cp ${FILENAME} test_tipc/test_lite_arm_cpu_cpp.sh test_tipc/common_func.sh ${paddlelite_file}/demo/cxx/ocr/test_lite
-cd ${paddlelite_file}/demo/cxx/ocr/
-git clone https://github.com/cuicheng01/AutoLog.git
-make -j
-sleep 1
-make -j
-cp ocr_db_crnn test_lite && cp test_lite/libpaddle_light_api_shared.so test_lite/libc++_shared.so
-tar -cf test_lite.tar ./test_lite && cp test_lite.tar ${current_dir} && cd ${current_dir}
-rm -rf ${paddlelite_file}* && rm -rf ${model_path}
diff --git a/test_tipc/prepare_lite_cpp.sh b/test_tipc/prepare_lite_cpp.sh
new file mode 100644
index 0000000000000000000000000000000000000000..eba794eefc1f89a42acef927d184cb2c543980f2
--- /dev/null
+++ b/test_tipc/prepare_lite_cpp.sh
@@ -0,0 +1,95 @@
+#!/bin/bash
+source ./test_tipc/common_func.sh
+FILENAME=$1
+dataline=$(cat ${FILENAME})
+# parser params
+IFS=$'\n'
+lines=(${dataline})
+IFS=$'\n'
+
+inference_cmd=$(func_parser_value "${lines[1]}")
+DEVICE=$(func_parser_value "${lines[2]}")
+det_lite_model_list=$(func_parser_value "${lines[3]}")
+rec_lite_model_list=$(func_parser_value "${lines[4]}")
+cls_lite_model_list=$(func_parser_value "${lines[5]}")
+
+if [[ $inference_cmd =~ "det" ]];then
+    lite_model_list=${det_lite_model_list}
+elif [[ $inference_cmd =~ "rec" ]];then
+    lite_model_list=(${rec_lite_model_list[*]} ${cls_lite_model_list[*]})
+elif [[ $inference_cmd =~ "system" ]];then
+    lite_model_list=(${det_lite_model_list[*]} ${rec_lite_model_list[*]} ${cls_lite_model_list[*]})
+else
+    echo "inference_cmd is wrong, please check."
+    exit 1
+fi
+
+if [ ${DEVICE} = "ARM_CPU" ];then
+    valid_targets="arm"
+    paddlelite_url="https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.10-rc/inference_lite_lib.android.armv8.gcc.c++_shared.with_extra.with_cv.tar.gz"
+    end_index="66"
+elif [ ${DEVICE} = "ARM_GPU_OPENCL" ];then
+    valid_targets="opencl"
+    paddlelite_url="https://github.com/PaddlePaddle/Paddle-Lite/releases/download/v2.10-rc/inference_lite_lib.armv8.clang.with_exception.with_extra.with_cv.opencl.tar.gz"
+    end_index="71"
+else
+    echo "DEVICE only suport ARM_CPU, ARM_GPU_OPENCL."
+    exit 2    
+fi
+
+# prepare lite .nb model
+pip install paddlelite==2.10-rc
+current_dir=${PWD}
+IFS="|"
+model_path=./inference_models
+
+for model in ${lite_model_list[*]}; do
+    if [[ $model =~ "PP-OCRv2" ]];then
+        inference_model_url=https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/${model}.tar
+    elif [[ $model =~ "v2.0" ]];then
+        inference_model_url=https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/${model}.tar
+    else 
+        echo "Model is wrong, please check."
+        exit 3
+    fi
+    inference_model=${inference_model_url##*/}
+    wget -nc  -P ${model_path} ${inference_model_url}
+    cd ${model_path} && tar -xf ${inference_model} && cd ../
+    model_dir=${model_path}/${inference_model%.*}
+    model_file=${model_dir}/inference.pdmodel
+    param_file=${model_dir}/inference.pdiparams
+    paddle_lite_opt --model_dir=${model_dir} --model_file=${model_file} --param_file=${param_file} --valid_targets=${valid_targets} --optimize_out=${model_dir}_opt
+done
+
+# prepare test data
+data_url=https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar
+model_path=./inference_models
+inference_model=${inference_model_url##*/}
+data_file=${data_url##*/}
+wget -nc  -P ./inference_models ${inference_model_url}
+wget -nc  -P ./test_data ${data_url}
+cd ./inference_models && tar -xf ${inference_model} && cd ../
+cd ./test_data && tar -xf ${data_file} && rm ${data_file} && cd ../
+
+# prepare lite env
+export http_proxy=http://172.19.57.45:3128
+export https_proxy=http://172.19.57.45:3128
+paddlelite_zipfile=$(echo $paddlelite_url | awk -F "/" '{print $NF}')
+paddlelite_file=${paddlelite_zipfile:0:${end_index}}
+wget ${paddlelite_url} && tar -xf ${paddlelite_zipfile}
+mkdir -p  ${paddlelite_file}/demo/cxx/ocr/test_lite
+cp -r ${model_path}/*_opt.nb test_data ${paddlelite_file}/demo/cxx/ocr/test_lite
+cp ppocr/utils/ppocr_keys_v1.txt deploy/lite/config.txt ${paddlelite_file}/demo/cxx/ocr/test_lite
+cp -r ./deploy/lite/* ${paddlelite_file}/demo/cxx/ocr/
+cp ${paddlelite_file}/cxx/lib/libpaddle_light_api_shared.so ${paddlelite_file}/demo/cxx/ocr/test_lite
+cp ${FILENAME} test_tipc/test_lite_arm_cpp.sh test_tipc/common_func.sh ${paddlelite_file}/demo/cxx/ocr/test_lite
+cd ${paddlelite_file}/demo/cxx/ocr/
+git clone https://github.com/cuicheng01/AutoLog.git
+unset http_proxy
+unset https_proxy
+make -j
+sleep 1
+make -j
+cp ocr_db_crnn test_lite && cp test_lite/libpaddle_light_api_shared.so test_lite/libc++_shared.so
+tar -cf test_lite.tar ./test_lite && cp test_lite.tar ${current_dir} && cd ${current_dir}
+rm -rf ${paddlelite_file}* && rm -rf ${model_path}
diff --git a/test_tipc/readme.md b/test_tipc/readme.md
index 9ab6f333d9dd74052dfd6eb71b60a8f257abd72d..99c92d65f2d42d67089f81c0211c0caf5f26c3bf 100644
--- a/test_tipc/readme.md
+++ b/test_tipc/readme.md
@@ -81,10 +81,11 @@ test_tipc/
 	├── cpp_ppocr_det_mobile_results_fp16.txt       # 预存的mobile版ppocr检测模型c++预测的fp16精度的结果
 	├── ...
 ├── prepare.sh                        # 完成test_*.sh运行所需要的数据和模型下载
+├── prepare_lite_cpp.sh               # 完成手机端test_*.sh运行所需要的数据、模型、可执行文件
 ├── test_train_inference_python.sh    # 测试python训练预测的主程序
 ├── test_inference_cpp.sh             # 测试c++预测的主程序
 ├── test_serving.sh                   # 测试serving部署预测的主程序
-├── test_lite_arm_cpu_cpp.sh          # 测试lite在arm_cpu上部署的C++预测的主程序
+├── test_lite_arm_cpp.sh          # 测试lite在arm上部署的C++预测的主程序
 ├── compare_results.py                # 用于对比log中的预测结果与results中的预存结果精度误差是否在限定范围内
 └── readme.md                         # 使用文档
 ```
@@ -123,5 +124,5 @@ test_tipc/
 [test_train_inference_python 使用](docs/test_train_inference_python.md)  
 [test_inference_cpp 使用](docs/test_inference_cpp.md)  
 [test_serving 使用](docs/test_serving.md)  
-[test_lite_arm_cpu_cpp 使用](docs/test_lite_arm_cpu_cpp.md)  
+[test_lite_arm_cpp 使用](docs/test_lite_arm_cpp.md)  
 [test_paddle2onnx 使用](docs/test_paddle2onnx.md)  
diff --git a/test_tipc/test_lite_arm_cpp.sh b/test_tipc/test_lite_arm_cpp.sh
new file mode 100644
index 0000000000000000000000000000000000000000..f119c1643add5fb132fb083a06ba6ef7450ecb81
--- /dev/null
+++ b/test_tipc/test_lite_arm_cpp.sh
@@ -0,0 +1,162 @@
+#!/bin/bash
+source ./common_func.sh
+export LD_LIBRARY_PATH=${PWD}:$LD_LIBRARY_PATH
+
+FILENAME=$1
+dataline=$(cat $FILENAME)
+# parser params
+IFS=$'\n'
+lines=(${dataline})
+
+# parser lite inference
+inference_cmd=$(func_parser_value "${lines[1]}")
+runtime_device=$(func_parser_value "${lines[2]}")
+det_model_list=$(func_parser_value "${lines[3]}")
+rec_model_list=$(func_parser_value "${lines[4]}")
+cls_model_list=$(func_parser_value "${lines[5]}")
+cpu_threads_list=$(func_parser_value "${lines[6]}")
+det_batch_size_list=$(func_parser_value "${lines[7]}")
+rec_batch_size_list=$(func_parser_value "${lines[8]}")
+infer_img_dir_list=$(func_parser_value "${lines[9]}")
+config_dir=$(func_parser_value "${lines[10]}")
+rec_dict_dir=$(func_parser_value "${lines[11]}")
+benchmark_value=$(func_parser_value "${lines[12]}")
+
+if [[ $inference_cmd =~ "det" ]]; then
+    lite_model_list=${det_lite_model_list}
+elif [[ $inference_cmd =~ "rec" ]]; then
+    lite_model_list=(${rec_lite_model_list[*]} ${cls_lite_model_list[*]})
+elif [[ $inference_cmd =~ "system" ]]; then
+    lite_model_list=(${det_lite_model_list[*]} ${rec_lite_model_list[*]} ${cls_lite_model_list[*]})
+else
+    echo "inference_cmd is wrong, please check."
+    exit 1
+fi
+
+LOG_PATH="./output"
+mkdir -p ${LOG_PATH}
+status_log="${LOG_PATH}/results.log"
+
+
+function func_test_det(){
+    IFS='|'
+    _script=$1
+    _det_model=$2
+    _log_path=$3
+    _img_dir=$4
+    _config=$5
+    if [[ $_det_model =~ "slim" ]]; then
+        precision="INT8"
+    else
+        precision="FP32"
+    fi
+
+    # lite inference
+    for num_threads in ${cpu_threads_list[*]}; do
+	for det_batchsize in ${det_batch_size_list[*]}; do
+            _save_log_path="${_log_path}/lite_${_det_model}_runtime_device_${runtime_device}_precision_${precision}_det_batchsize_${det_batchsize}_threads_${num_threads}.log"
+            command="${_script} ${_det_model} ${runtime_device} ${precision} ${num_threads} ${det_batchsize}  ${_img_dir} ${_config} ${benchmark_value} > ${_save_log_path} 2>&1"
+	    echo ${command}
+            eval ${command}
+            status_check $? "${command}" "${status_log}"
+        done
+    done
+}
+
+function func_test_rec(){
+    IFS='|'
+    _script=$1
+    _rec_model=$2
+    _cls_model=$3
+    _log_path=$4
+    _img_dir=$5
+    _config=$6
+    _rec_dict_dir=$7
+
+    if [[ $_det_model =~ "slim" ]]; then
+        _precision="INT8"
+    else
+        _precision="FP32"
+    fi
+
+    # lite inference
+    for num_threads in ${cpu_threads_list[*]}; do
+	for rec_batchsize in ${rec_batch_size_list[*]}; do
+            _save_log_path="${_log_path}/lite_${_rec_model}_${cls_model}_runtime_device_${runtime_device}_precision_${_precision}_rec_batchsize_${rec_batchsize}_threads_${num_threads}.log"
+            command="${_script} ${_rec_model} ${_cls_model} ${runtime_device} ${_precision} ${num_threads} ${rec_batchsize}  ${_img_dir} ${_config} ${_rec_dict_dir} ${benchmark_value} > ${_save_log_path} 2>&1"
+	    echo ${command}
+            eval ${command}
+            status_check $? "${command}" "${status_log}"
+        done
+    done
+}
+
+function func_test_system(){
+    IFS='|'
+    _script=$1
+    _det_model=$2
+    _rec_model=$3
+    _cls_model=$4
+    _log_path=$5
+    _img_dir=$6
+    _config=$7
+    _rec_dict_dir=$8
+    if [[ $_det_model =~ "slim" ]]; then
+        _precision="INT8"
+    else
+        _precision="FP32"
+    fi
+
+    # lite inference
+    for num_threads in ${cpu_threads_list[*]}; do
+	for det_batchsize in ${det_batch_size_list[*]}; do
+	   for rec_batchsize in ${rec_batch_size_list[*]}; do
+                _save_log_path="${_log_path}/lite_${_det_model}_${_rec_model}_${_cls_model}_runtime_device_${runtime_device}_precision_${_precision}_det_batchsize_${det_batchsize}_rec_batchsize_${rec_batchsize}_threads_${num_threads}.log"
+                command="${_script} ${_det_model} ${_rec_model} ${_cls_model} ${runtime_device} ${_precision} ${num_threads} ${det_batchsize}  ${_img_dir} ${_config} ${_rec_dict_dir} ${benchmark_value} > ${_save_log_path} 2>&1"
+	       echo ${command}
+               eval ${command}
+               status_check $? "${command}" "${status_log}"
+	    done
+        done
+    done
+}
+
+
+echo "################### run test ###################"
+
+if [[ $inference_cmd =~ "det" ]]; then
+    IFS="|"
+    det_model_list=(${det_model_list[*]})
+
+    for i in {0..1}; do
+        #run lite inference
+        for img_dir in ${infer_img_dir_list[*]}; do
+            func_test_det "${inference_cmd}" "${det_model_list[i]}_opt.nb" "${LOG_PATH}" "${img_dir}" "${config_dir}"
+        done
+    done
+
+elif [[ $inference_cmd =~ "rec" ]]; then
+    IFS="|"
+    rec_model_list=(${rec_model_list[*]})
+    cls_model_list=(${cls_model_list[*]})
+
+    for i in {0..1}; do
+        #run lite inference
+        for img_dir in ${infer_img_dir_list[*]}; do
+            func_test_rec "${inference_cmd}" "${rec_model}_opt.nb" "${cls_model_list[i]}_opt.nb" "${LOG_PATH}" "${img_dir}" "${rec_dict_dir}" "${config_dir}"
+        done
+    done
+
+elif [[ $inference_cmd =~ "system" ]]; then
+    IFS="|"
+    det_model_list=(${det_model_list[*]})
+    rec_model_list=(${rec_model_list[*]})
+    cls_model_list=(${cls_model_list[*]})
+
+    for i in {0..1}; do
+	#run lite inference
+        for img_dir in ${infer_img_dir_list[*]}; do
+            func_test_system "${inference_cmd}" "${det_model_list[i]}_opt.nb" "${rec_model_list[i]}_opt.nb" "${cls_model_list[i]}_opt.nb" "${LOG_PATH}" "${img_dir}" "${config_dir}" "${rec_dict_dir}"
+        done
+    done
+fi
diff --git a/test_tipc/test_lite_arm_cpu_cpp.sh b/test_tipc/test_lite_arm_cpu_cpp.sh
deleted file mode 100644
index 04eebbd28a334f7ac7819f8ff55d7b3192f4b490..0000000000000000000000000000000000000000
--- a/test_tipc/test_lite_arm_cpu_cpp.sh
+++ /dev/null
@@ -1,60 +0,0 @@
-#!/bin/bash
-source ./common_func.sh
-export LD_LIBRARY_PATH=${PWD}:$LD_LIBRARY_PATH
-
-FILENAME=$1
-dataline=$(cat $FILENAME)
-# parser params
-IFS=$'\n'
-lines=(${dataline})
-
-# parser lite inference
-lite_inference_cmd=$(func_parser_value "${lines[1]}")
-lite_model_dir_list=$(func_parser_value "${lines[2]}")
-runtime_device=$(func_parser_value "${lines[3]}")
-lite_cpu_threads_list=$(func_parser_value "${lines[4]}")
-lite_batch_size_list=$(func_parser_value "${lines[5]}")
-lite_infer_img_dir_list=$(func_parser_value "${lines[8]}")
-lite_config_dir=$(func_parser_value "${lines[9]}")
-lite_rec_dict_dir=$(func_parser_value "${lines[10]}")
-lite_benchmark_value=$(func_parser_value "${lines[11]}")
-
-
-LOG_PATH="./output"
-mkdir -p ${LOG_PATH}
-status_log="${LOG_PATH}/results.log"
-
-
-function func_lite(){
-    IFS='|'
-    _script=$1
-    _lite_model=$2
-    _log_path=$3
-    _img_dir=$4
-    _config=$5
-    if [[ $lite_model =~ "slim" ]]; then
-        precision="INT8"
-    else
-        precision="FP32"
-    fi
-
-    # lite inference
-    for num_threads in ${lite_cpu_threads_list[*]}; do
-	for batchsize in ${lite_batch_size_list[*]}; do
-            _save_log_path="${_log_path}/lite_${_lite_model}_runtime_device_${runtime_device}_precision_${precision}_batchsize_${batchsize}_threads_${num_threads}.log"
-            command="${_script} ${_lite_model} ${runtime_device} ${precision} ${num_threads} ${batchsize}  ${_img_dir} ${_config} ${lite_benchmark_value} > ${_save_log_path} 2>&1"
-            eval ${command}
-            status_check $? "${command}" "${status_log}"
-        done
-    done
-}
-
-
-echo "################### run test ###################"
-IFS="|"
-for lite_model in ${lite_model_dir_list[*]}; do
-    #run lite inference
-    for img_dir in ${lite_infer_img_dir_list[*]}; do
-        func_lite "${lite_inference_cmd}" "${lite_model}_opt.nb" "${LOG_PATH}" "${img_dir}" "${lite_config_dir}"
-    done
-done