diff --git a/deploy/cpp/CMakeLists.txt b/deploy/cpp/CMakeLists.txt
index 453be9bd742d2f4a6c10ebf3c2908a29d51c397f..0bc0be9aa949dfb89f726555bac16066127502fb 100644
--- a/deploy/cpp/CMakeLists.txt
+++ b/deploy/cpp/CMakeLists.txt
@@ -4,10 +4,10 @@ project(PaddleObjectDetector CXX C)
 option(WITH_MKL        "Compile demo with MKL/OpenBlas support,defaultuseMKL."          ON)
 option(WITH_GPU        "Compile demo with GPU/CPU, default use CPU."                    ON)
 option(WITH_TENSORRT   "Compile demo with TensorRT."                                    OFF)
-option(USE_PADDLE_20RC1 "Compile demo with paddle_inference_lib 2.0rc1"                 ON)
 
 
 SET(PADDLE_DIR "" CACHE PATH "Location of libraries")
+SET(PADDLE_LIB_NAME "" CACHE STRING "libpaddle_inference")
 SET(OPENCV_DIR "" CACHE PATH "Location of libraries")
 SET(CUDA_LIB "" CACHE PATH "Location of libraries")
 SET(CUDNN_LIB "" CACHE PATH "Location of libraries")
@@ -153,41 +153,23 @@ endif()
 
 
 if (WIN32)
-    if (USE_PADDLE_20RC1)
-        # 2.0rc1 win32 shared lib name is paddle_fluid.dll and paddle_fluid.lib
-        if(EXISTS "${PADDLE_DIR}/paddle/fluid/inference/paddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX}")
+    if(EXISTS "${PADDLE_DIR}/paddle/fluid/inference/${PADDLE_LIB_NAME}${CMAKE_STATIC_LIBRARY_SUFFIX}")
         set(DEPS
-            ${PADDLE_DIR}/paddle/fluid/inference/paddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
-        else()
-            set(DEPS
-                ${PADDLE_DIR}/paddle/lib/paddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
-        endif()
+            ${PADDLE_DIR}/paddle/fluid/inference/${PADDLE_LIB_NAME}${CMAKE_STATIC_LIBRARY_SUFFIX})
     else()
-        # before 2.0rc1 win32 shared lib name is libpaddle_fluid.dll and libpaddle_fluid.lib
-        if(EXISTS "${PADDLE_DIR}/paddle/fluid/inference/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX}")
-            set(DEPS
-                ${PADDLE_DIR}/paddle/fluid/inference/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
-        else()
-            set(DEPS
-                ${PADDLE_DIR}/paddle/lib/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
-        endif()
+        set(DEPS
+            ${PADDLE_DIR}/paddle/lib/${PADDLE_LIB_NAME}${CMAKE_STATIC_LIBRARY_SUFFIX})
     endif()
 endif()
 
 
 if (WIN32)
-    if (USE_PADDLE_20RC1)
-        # 2.0rc1 win32 shared lib name is paddle_fluid.dll and paddle_fluid.lib
-        set(DEPS ${PADDLE_DIR}/paddle/lib/paddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
-    else()
-        # before 2.0rc1 win32 shared lib name is libpaddle_fluid.dll and libpaddle_fluid.lib
-        set(DEPS ${PADDLE_DIR}/paddle/lib/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
-    endif()
+    set(DEPS ${PADDLE_DIR}/paddle/lib/${PADDLE_LIB_NAME}${CMAKE_STATIC_LIBRARY_SUFFIX})
 else()
-    # linux shared lib name is libpaddle_fluid.so
-    set(DEPS ${PADDLE_DIR}/paddle/lib/libpaddle_fluid${CMAKE_SHARED_LIBRARY_SUFFIX})
+    set(DEPS ${PADDLE_DIR}/paddle/lib/${PADDLE_LIB_NAME}${CMAKE_SHARED_LIBRARY_SUFFIX})
 endif()
 
+message("PADDLE_LIB_NAME:" ${PADDLE_LIB_NAME})
 message("DEPS:" $DEPS)
 
 if (NOT WIN32)
@@ -248,12 +230,12 @@ if (WIN32 AND WITH_MKL)
         COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/mklml.dll ./release/mklml.dll
         COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/libiomp5md.dll ./release/libiomp5md.dll
         COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mkldnn/lib/mkldnn.dll ./release/mkldnn.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/paddle/lib/${PADDLE_LIB_NAME}.dll ./release/${PADDLE_LIB_NAME}.dll
     )
 endif()
 
-
-if (WIN32 AND USE_PADDLE_20RC1)
+if (WIN32)
     add_custom_command(TARGET main POST_BUILD
-        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/paddle/lib/paddle_fluid.dll ./release/paddle_fluid.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/paddle/lib/${PADDLE_LIB_NAME}.dll ./release/${PADDLE_LIB_NAME}.dll
     )
 endif()
diff --git a/deploy/cpp/docs/Jetson_build.md b/deploy/cpp/docs/Jetson_build.md
new file mode 100644
index 0000000000000000000000000000000000000000..27130f58020fb08b69d8f8662986cfd45b8aa44e
--- /dev/null
+++ b/deploy/cpp/docs/Jetson_build.md
@@ -0,0 +1,199 @@
+# Jetson平台编译指南
+
+## 说明
+`NVIDIA Jetson`设备是具有`NVIDIA GPU`的嵌入式设备，可以将目标检测算法部署到该设备上。本文档是在`Jetson`硬件上部署`PaddleDetection`模型的教程。
+
+本文档以`Jetson TX2`硬件、`JetPack 4.3`版本为例进行说明。
+
+`Jetson`平台的开发指南请参考[NVIDIA Jetson Linux Developer Guide](https://docs.nvidia.com/jetson/l4t/index.html).
+
+## Jetson环境搭建
+`Jetson`系统软件安装，请参考[NVIDIA Jetson Linux Developer Guide](https://docs.nvidia.com/jetson/l4t/index.html).
+
+* (1) 查看硬件系统的l4t的版本号
+```
+cat /etc/nv_tegra_release
+```
+* (2) 根据硬件，选择硬件可安装的`JetPack`版本，硬件和`JetPack`版本对应关系请参考[jetpack-archive](https://developer.nvidia.com/embedded/jetpack-archive).
+
+* (3) 下载`JetPack`，请参考[NVIDIA Jetson Linux Developer Guide](https://docs.nvidia.com/jetson/l4t/index.html) 中的`Preparing a Jetson Developer Kit for Use`章节内容进行刷写系统镜像。
+
+## 下载或编译`Paddle`预测库
+本文档使用`Paddle`在`JetPack4.3`上预先编译好的预测库，请根据硬件在[安装与编译 Linux 预测库](https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/05_inference_deployment/inference/build_and_install_lib_cn.html) 中选择对应版本的`Paddle`预测库。
+
+这里选择[nv_jetson_cuda10_cudnn7.6_trt6(jetpack4.3)](https://paddle-inference-lib.bj.bcebos.com/2.0.0-nv-jetson-jetpack4.3-all/paddle_inference.tgz), `Paddle`版本`2.0.0-rc0`,`CUDA`版本`10.0`,`CUDNN`版本`7.6`，`TensorRT`版本`6`。
+
+若需要自己在`Jetson`平台上自定义编译`Paddle`库，请参考文档[安装与编译 Linux 预测库](https://www.paddlepaddle.org.cn/documentation/docs/zh/advanced_guide/inference_deployment/inference/build_and_install_lib_cn.html) 的`NVIDIA Jetson嵌入式硬件预测库源码编译`部分内容。
+
+### Step1: 下载代码
+
+ `git clone https://github.com/PaddlePaddle/PaddleDetection.git`
+
+**说明**：其中`C++`预测代码在`/root/projects/PaddleDetection/deploy/cpp` 目录，该目录不依赖任何`PaddleDetection`下其他目录。
+
+
+### Step2: 下载PaddlePaddle C++ 预测库 fluid_inference
+
+解压下载的[nv_jetson_cuda10_cudnn7.6_trt6(jetpack4.3)](https://paddle-inference-lib.bj.bcebos.com/2.0.1-nv-jetson-jetpack4.3-all/paddle_inference.tgz) 。
+
+下载并解压后`/root/projects/fluid_inference`目录包含内容为：
+```
+fluid_inference
+├── paddle # paddle核心库和头文件
+|
+├── third_party # 第三方依赖库和头文件
+|
+└── version.txt # 版本和编译信息
+```
+
+**注意:** 预编译库`nv-jetson-cuda10-cudnn7.6-trt6`使用的`GCC`版本是`7.5.0`，其他都是使用`GCC 4.8.5`编译的。使用高版本的GCC可能存在`ABI`兼容性问题，建议降级或[自行编译预测库](https://www.paddlepaddle.org.cn/documentation/docs/zh/advanced_guide/inference_deployment/inference/build_and_install_lib_cn.html)。
+
+
+### Step4: 编译
+
+编译`cmake`的命令在`scripts/build.sh`中，请根据实际情况修改主要参数，其主要内容说明如下：
+
+注意，`TX2`平台的`CUDA`、`CUDNN`需要通过`JetPack`安装。
+
+```
+# 是否使用GPU(即是否使用 CUDA)
+WITH_GPU=ON
+
+# 是否使用MKL or openblas，TX2需要设置为OFF
+WITH_MKL=OFF
+
+# 是否集成 TensorRT(仅WITH_GPU=ON 有效)
+WITH_TENSORRT=ON
+
+# TensorRT 的include路径
+TENSORRT_INC_DIR=/usr/include/aarch64-linux-gnu
+
+# TensorRT 的lib路径
+TENSORRT_LIB_DIR=/usr/lib/aarch64-linux-gnu
+
+# Paddle 预测库路径
+PADDLE_DIR=/path/to/fluid_inference/
+
+# Paddle 预测库名称
+PADDLE_LIB_NAME=paddle_inference
+
+# Paddle 的预测库是否使用静态库来编译
+# 使用TensorRT时，Paddle的预测库通常为动态库
+WITH_STATIC_LIB=OFF
+
+# CUDA 的 lib 路径
+CUDA_LIB=/usr/local/cuda-10.0/lib64
+
+# CUDNN 的 lib 路径
+CUDNN_LIB=/usr/lib/aarch64-linux-gnu
+
+# OPENCV_DIR 的路径
+# linux平台请下载：https://bj.bcebos.com/paddleseg/deploy/opencv3.4.6gcc4.8ffmpeg.tar.gz2，并解压到deps文件夹下
+# TX2平台请下载：https://paddlemodels.bj.bcebos.com/TX2_JetPack4.3_opencv_3.4.10_gcc7.5.0.zip，并解压到deps文件夹下
+OPENCV_DIR=/path/to/opencv
+
+# 请检查以上各个路径是否正确
+
+# 以下无需改动
+cmake .. \
+    -DWITH_GPU=${WITH_GPU} \
+    -DWITH_MKL=OFF \
+    -DWITH_TENSORRT=${WITH_TENSORRT} \
+    -DTENSORRT_DIR=${TENSORRT_DIR} \
+    -DPADDLE_DIR=${PADDLE_DIR} \
+    -DWITH_STATIC_LIB=${WITH_STATIC_LIB} \
+    -DCUDA_LIB=${CUDA_LIB} \
+    -DCUDNN_LIB=${CUDNN_LIB} \
+    -DOPENCV_DIR=${OPENCV_DIR} \
+    -DPADDLE_LIB_NAME={PADDLE_LIB_NAME}
+make
+```
+
+例如设置如下：
+```
+# 是否使用GPU(即是否使用 CUDA)
+WITH_GPU=ON
+
+# 是否使用MKL or openblas
+WITH_MKL=OFF
+
+# 是否集成 TensorRT(仅WITH_GPU=ON 有效)
+WITH_TENSORRT=OFF
+
+# TensorRT 的include路径
+TENSORRT_INC_DIR=/usr/include/aarch64-linux-gnu
+
+# TensorRT 的lib路径
+TENSORRT_LIB_DIR=/usr/lib/aarch64-linux-gnu
+
+# Paddle 预测库路径
+PADDLE_DIR=/home/nvidia/PaddleDetection_infer/fluid_inference/
+
+# Paddle 预测库名称
+PADDLE_LIB_NAME=paddle_inference
+
+# Paddle 的预测库是否使用静态库来编译
+# 使用TensorRT时，Paddle的预测库通常为动态库
+WITH_STATIC_LIB=OFF
+
+# CUDA 的 lib 路径
+CUDA_LIB=/usr/local/cuda-10.0/lib64
+
+# CUDNN 的 lib 路径
+CUDNN_LIB=/usr/lib/aarch64-linux-gnu/
+```
+
+修改脚本设置好主要参数后，执行`build`脚本：
+ ```shell
+ sh ./scripts/build.sh
+ ```
+
+### Step5: 预测及可视化
+编译成功后，预测入口程序为`build/main`其主要命令参数说明如下：
+|  参数   | 说明  |
+|  ----  | ----  |
+| --model_dir  | 导出的预测模型所在路径 |
+| --image_path  | 要预测的图片文件路径 |
+| --video_path  | 要预测的视频文件路径 |
+| --camera_id | Option | 用来预测的摄像头ID，默认为-1（表示不使用摄像头预测）|
+| --use_gpu  | 是否使用 GPU 预测, 支持值为0或1(默认值为0)|
+| --gpu_id  |  指定进行推理的GPU device id(默认值为0)|
+| --run_mode | 使用GPU时，默认为fluid, 可选（fluid/trt_fp32/trt_fp16）|
+| --run_benchmark | 是否重复预测来进行benchmark测速 ｜
+| --output_dir | 输出图片所在的文件夹, 默认为output ｜
+
+**注意**: 如果同时设置了`video_path`和`image_path`，程序仅预测`video_path`。
+
+
+`样例一`：
+```shell
+#不使用`GPU`测试图片 `/root/projects/images/test.jpeg`  
+./main --model_dir=/root/projects/models/yolov3_darknet --image_path=/root/projects/images/test.jpeg
+```
+
+图片文件`可视化预测结果`会保存在当前目录下`output.jpg`文件中。
+
+
+`样例二`:
+```shell
+#使用 `GPU`预测视频`/root/projects/videos/test.mp4`
+./main --model_dir=/root/projects/models/yolov3_darknet --video_path=/root/projects/images/test.mp4 --use_gpu=1
+```
+视频文件目前支持`.mp4`格式的预测，`可视化预测结果`会保存在当前目录下`output.mp4`文件中。
+
+
+## 性能测试
+测试环境为：硬件: TX2，JetPack版本: 4.3, Paddle预测库: 1.8.4，CUDA: 10.0, CUDNN: 7.5, TensorRT: 5.0.  
+
+去掉前100轮warmup时间，测试100轮的平均时间，单位ms/image，只计算模型运行时间，不包括数据的处理和拷贝。
+
+
+|模型 | 输入| AnalysisPredictor(ms) |
+|---|----|---|
+| yolov3_mobilenet_v1 |  608*608  | 56.243858
+| faster_rcnn_r50_1x  | 1333*1333  | 73.552460
+| faster_rcnn_r50_vd_fpn_2x | 1344*1344 | 87.582146
+| mask_rcnn_r50_fpn_1x | 1344*1344  | 107.317848
+| mask_rcnn_r50_vd_fpn_2x | 1344*1344  | 87.98.708122
+| ppyolo_r18vd | 320*320  |  22.876789
+| ppyolo_2x | 608*608  | 68.562050
diff --git a/deploy/cpp/docs/linux_build.md b/deploy/cpp/docs/linux_build.md
index 1ddb7a150e11e4ec6c5fa1b62d6606fc60719a83..60c609663002c05e75f811ae1431e58cf4a333da 100644
--- a/deploy/cpp/docs/linux_build.md
+++ b/deploy/cpp/docs/linux_build.md
@@ -1,10 +1,10 @@
 # Linux平台编译指南
 
 ## 说明
-本文档在 `Linux`平台使用`GCC 4.8.5` 和 `GCC 4.9.4`测试过，如果需要使用更高G++版本编译使用，则需要重新编译Paddle预测库，请参考: [从源码编译Paddle预测库](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/advanced_guide/inference_deployment/inference/build_and_install_lib_cn.html)。本文档使用的预置的opencv库是在ubuntu 16.04上用gcc4.8编译的，如果需要在ubuntu 16.04以外的系统环境编译，那么需自行编译opencv库。
+本文档在 `Linux`平台使用`GCC 8.2`测试过，如果需要使用其他G++版本编译使用，则需要重新编译Paddle预测库，请参考: [从源码编译Paddle预测库](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/advanced_guide/inference_deployment/inference/build_and_install_lib_cn.html)。本文档使用的预置的opencv库是在ubuntu 16.04上用gcc4.8编译的，如果需要在ubuntu 16.04以外的系统环境编译，那么需自行编译opencv库。
 
 ## 前置条件
-* G++ 4.8.2 ~ 4.9.4
+* G++ 8.2
 * CUDA 9.0 / CUDA 10.0, cudnn 7+ （仅在使用GPU版本的预测库时需要）
 * CMake 3.0+
 
@@ -19,7 +19,7 @@
 
 ### Step2: 下载PaddlePaddle C++ 预测库 fluid_inference
 
-PaddlePaddle C++ 预测库针对不同的`CPU`和`CUDA`版本提供了不同的预编译版本，请根据实际情况下载:  [C++预测库下载列表](https://www.paddlepaddle.org.cn/documentation/docs/zh/2.0-rc1/guides/05_inference_deployment/inference/build_and_install_lib_cn.html)
+PaddlePaddle C++ 预测库针对不同的`CPU`和`CUDA`版本提供了不同的预编译版本，请根据实际情况下载:  [C++预测库下载列表](https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/05_inference_deployment/inference/build_and_install_lib_cn.html)
 
 
 下载并解压后`/root/projects/fluid_inference`目录包含内容为：
@@ -58,6 +58,9 @@ TENSORRT_LIB_DIR=/path/to/TensorRT/lib
 # Paddle 预测库路径
 PADDLE_DIR=/path/to/fluid_inference
 
+# Paddle 预测库名称
+PADDLE_LIB_NAME=paddle_inference
+
 # CUDA 的 lib 路径
 CUDA_LIB=/path/to/cuda/lib
 
@@ -76,7 +79,8 @@ cmake .. \
     -DPADDLE_DIR=${PADDLE_DIR} \
     -DCUDA_LIB=${CUDA_LIB} \
     -DCUDNN_LIB=${CUDNN_LIB} \
-    -DOPENCV_DIR=${OPENCV_DIR}
+    -DOPENCV_DIR=${OPENCV_DIR} \
+    -DPADDLE_LIB_NAME={PADDLE_LIB_NAME}
 make
 
 ```
diff --git a/deploy/cpp/docs/windows_vs2019_build.md b/deploy/cpp/docs/windows_vs2019_build.md
index 7cfb63a62757225e7db17f7435d4847584c02825..aca5d3ab970cb4aa9aac9a6ea26b2a7c621acac2 100644
--- a/deploy/cpp/docs/windows_vs2019_build.md
+++ b/deploy/cpp/docs/windows_vs2019_build.md
@@ -24,7 +24,7 @@ git clone https://github.com/PaddlePaddle/PaddleDetection.git
 
 ### Step2: 下载PaddlePaddle C++ 预测库 fluid_inference
 
-PaddlePaddle C++ 预测库针对不同的`CPU`和`CUDA`版本提供了不同的预编译版本，请根据实际情况下载:  [C++预测库下载列表](https://www.paddlepaddle.org.cn/documentation/docs/zh/2.0-rc1/guides/05_inference_deployment/inference/windows_cpp_inference.html)
+PaddlePaddle C++ 预测库针对不同的`CPU`和`CUDA`版本提供了不同的预编译版本，请根据实际情况下载:  [C++预测库下载列表](https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/05_inference_deployment/inference/windows_cpp_inference.html)
 
 解压后`D:\projects\fluid_inference`目录包含内容为：
 ```
@@ -62,18 +62,18 @@ cd D:\projects\PaddleDetection\deploy\cpp
 | *CUDNN_LIB | CUDNN的库路径 |
 | OPENCV_DIR  | OpenCV的安装路径， |
 | PADDLE_DIR | Paddle预测库的路径 |
-| USE_PADDLE_20RC1 | 是否使用2.0rc1预测库。如果使用2.0rc1，在windows环境下预测库名称发生变化，且仅支持动态库方式编译 |
+| PADDLE_LIB_NAME | Paddle 预测库名称 |
 
 **注意：** 1. 使用`CPU`版预测库，请把`WITH_GPU`的勾去掉 2. 如果使用的是`openblas`版本，请把`WITH_MKL`勾去掉
 
 执行如下命令项目文件：
 ```
-cmake . -G "Visual Studio 16 2019" -A x64 -T host=x64 -DWITH_GPU=ON -DWITH_MKL=ON -DCMAKE_BUILD_TYPE=Release -DCUDA_LIB=path_to_cuda_lib -DCUDNN_LIB=path_to_cudnn_lib -DPADDLE_DIR=path_to_paddle_lib -DOPENCV_DIR=path_to_opencv
+cmake . -G "Visual Studio 16 2019" -A x64 -T host=x64 -DWITH_GPU=ON -DWITH_MKL=ON -DCMAKE_BUILD_TYPE=Release -DCUDA_LIB=path_to_cuda_lib -DCUDNN_LIB=path_to_cudnn_lib -DPADDLE_DIR=path_to_paddle_lib -DPADDLE_LIB_NAME=paddle_inference -DOPENCV_DIR=path_to_opencv
 ```
 
 例如：
 ```
-cmake . -G "Visual Studio 16 2019" -A x64 -T host=x64 -DWITH_GPU=ON -DWITH_MKL=ON -DCMAKE_BUILD_TYPE=Release -DCUDA_LIB=D:\projects\packages\cuda10_0\lib\x64 -DCUDNN_LIB=D:\projects\packages\cuda10_0\lib\x64 -DPADDLE_DIR=D:\projects\packages\fluid_inference -DOPENCV_DIR=D:\projects\packages\opencv3_4_6
+cmake . -G "Visual Studio 16 2019" -A x64 -T host=x64 -DWITH_GPU=ON -DWITH_MKL=ON -DCMAKE_BUILD_TYPE=Release -DCUDA_LIB=D:\projects\packages\cuda10_0\lib\x64 -DCUDNN_LIB=D:\projects\packages\cuda10_0\lib\x64 -DPADDLE_DIR=D:\projects\packages\fluid_inference -DPADDLE_LIB_NAME=paddle_inference -DOPENCV_DIR=D:\projects\packages\opencv3_4_6
 ```
 
 3. 编译
diff --git a/deploy/cpp/include/preprocess_op.h b/deploy/cpp/include/preprocess_op.h
index e48639b553867dff859cef4816558df7654edcfb..26a91cc9eb74008919cbac12e736afff6bb9ad72 100644
--- a/deploy/cpp/include/preprocess_op.h
+++ b/deploy/cpp/include/preprocess_op.h
@@ -38,7 +38,7 @@ class ImageBlob {
   // Buffer for image data after preprocessing
   std::vector<float> im_data_;
   // in net data shape(after pad)
-  std::vector<int> in_net_shape_;
+  std::vector<float> in_net_shape_;
   // Evaluation image width and height
   //std::vector<float>  eval_im_size_f_;
   // Scale factor for image size to origin image size
diff --git a/deploy/cpp/scripts/build.sh b/deploy/cpp/scripts/build.sh
index a32b1d383256f0d775dba41d16b99468558e9135..803fbab7d7fe7cfbc7ce1bcc7543692a24d27cb4 100644
--- a/deploy/cpp/scripts/build.sh
+++ b/deploy/cpp/scripts/build.sh
@@ -7,17 +7,17 @@ WITH_MKL=ON
 # 是否集成 TensorRT(仅WITH_GPU=ON 有效)
 WITH_TENSORRT=OFF
 
-# 是否使用2.0rc1预测库
-USE_PADDLE_20RC1=ON
+# paddle 预测库lib名称，由于不同平台不同版本预测库lib名称不同，请查看所下载的预测库中`paddle_inference/lib/`文件夹下`lib`的名称
+PADDLE_LIB_NAME=libpaddle_inference
 
 # TensorRT 的include路径
-TENSORRT_INC_DIR=/path/to/tensorrt/lib
+TENSORRT_INC_DIR=/path/to/tensorrt/include
 
 # TensorRT 的lib路径
-TENSORRT_LIB_DIR=/path/to/tensorrt/include
+TENSORRT_LIB_DIR=/path/to/tensorrt/lib
 
 # Paddle 预测库路径
-PADDLE_DIR=/path/to/fluid_inference/
+PADDLE_DIR=/paddle/to/paddle_inference
 
 # CUDA 的 lib 路径
 CUDA_LIB=/path/to/cuda/lib
@@ -72,7 +72,8 @@ cmake .. \
     -DWITH_STATIC_LIB=${WITH_STATIC_LIB} \
     -DCUDA_LIB=${CUDA_LIB} \
     -DCUDNN_LIB=${CUDNN_LIB} \
-    -DOPENCV_DIR=${OPENCV_DIR}
+    -DOPENCV_DIR=${OPENCV_DIR} \
+    -DPADDLE_LIB_NAME=${PADDLE_LIB_NAME}
 
 make
 echo "make finished!"
diff --git a/deploy/cpp/src/main.cc b/deploy/cpp/src/main.cc
index 6fb49769288f12f7c71345f03f689d6a67757f19..00dd325680b39df3900689e98fae6f32b58ec99e 100644
--- a/deploy/cpp/src/main.cc
+++ b/deploy/cpp/src/main.cc
@@ -207,9 +207,6 @@ int main(int argc, char** argv) {
     return -1;
   }
   // Load model and create a object detector
-  const std::vector<int> trt_min_shape = {1, FLAGS_trt_min_shape, FLAGS_trt_min_shape};
-  const std::vector<int> trt_max_shape = {1, FLAGS_trt_max_shape, FLAGS_trt_max_shape};
-  const std::vector<int> trt_opt_shape = {1, FLAGS_trt_opt_shape, FLAGS_trt_opt_shape};
   PaddleDetection::ObjectDetector det(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_run_mode,
                         FLAGS_gpu_id, FLAGS_use_dynamic_shape, FLAGS_trt_min_shape,
                         FLAGS_trt_max_shape, FLAGS_trt_opt_shape);
diff --git a/deploy/cpp/src/object_detector.cc b/deploy/cpp/src/object_detector.cc
index 969425dcedc1ec532951d7919aff215026a423ff..95b8dbb2217cd9dd28761f82724214a68a1a0ebe 100644
--- a/deploy/cpp/src/object_detector.cc
+++ b/deploy/cpp/src/object_detector.cc
@@ -68,9 +68,9 @@ void ObjectDetector::LoadModel(const std::string& model_dir,
       // set use dynamic shape
       if (use_dynamic_shape) {
         // set DynamicShsape for image tensor
-        const std::vector<int> min_input_shape = {1, trt_min_shape, trt_min_shape};
-        const std::vector<int> max_input_shape = {1, trt_max_shape, trt_max_shape};
-        const std::vector<int> opt_input_shape = {1, trt_opt_shape, trt_opt_shape};
+        const std::vector<int> min_input_shape = {1, 3, trt_min_shape, trt_min_shape};
+        const std::vector<int> max_input_shape = {1, 3, trt_max_shape, trt_max_shape};
+        const std::vector<int> opt_input_shape = {1, 3, trt_opt_shape, trt_opt_shape};
         const std::map<std::string, std::vector<int>> map_min_input_shape = {{"image", min_input_shape}};
         const std::map<std::string, std::vector<int>> map_max_input_shape = {{"image", max_input_shape}};
         const std::map<std::string, std::vector<int>> map_opt_input_shape = {{"image", opt_input_shape}};
diff --git a/deploy/cpp/src/preprocess_op.cc b/deploy/cpp/src/preprocess_op.cc
index 8edd3eb1f2b7957649f7075bbcd20ba582c841a7..6a2be41799620ec681aed18db05ab5df4b281052 100644
--- a/deploy/cpp/src/preprocess_op.cc
+++ b/deploy/cpp/src/preprocess_op.cc
@@ -26,8 +26,8 @@ void InitInfo::Run(cv::Mat* im, ImageBlob* data) {
   };
   data->scale_factor_ = {1., 1.};
   data->in_net_shape_ = {
-      static_cast<int>(im->rows),
-      static_cast<int>(im->cols)
+      static_cast<float>(im->rows),
+      static_cast<float>(im->cols)
   };
 }
 
@@ -63,12 +63,12 @@ void Permute::Run(cv::Mat* im, ImageBlob* data) {
 void Resize::Run(cv::Mat* im, ImageBlob* data) {
   auto resize_scale = GenerateScale(*im);
   data->im_shape_ = {
-      static_cast<int>(im->cols * resize_scale.first),
-      static_cast<int>(im->rows * resize_scale.second)
+      static_cast<float>(im->cols * resize_scale.first),
+      static_cast<float>(im->rows * resize_scale.second)
   };
   data->in_net_shape_ = {
-      static_cast<int>(im->cols * resize_scale.first),
-      static_cast<int>(im->rows * resize_scale.second)
+      static_cast<float>(im->cols * resize_scale.first),
+      static_cast<float>(im->rows * resize_scale.second)
   };
   cv::resize(
       *im, *im, cv::Size(), resize_scale.first, resize_scale.second, interp_);
@@ -126,8 +126,8 @@ void PadStride::Run(cv::Mat* im, ImageBlob* data) {
     cv::BORDER_CONSTANT,
     cv::Scalar(0));
   data->in_net_shape_ = {
-    static_cast<int>(im->rows),
-    static_cast<int>(im->cols),
+    static_cast<float>(im->rows),
+    static_cast<float>(im->cols),
   };
 
 }
diff --git a/static/deploy/cpp/CMakeLists.txt b/static/deploy/cpp/CMakeLists.txt
index 0517825795dce9ae4c550e174eb642bd2273d6bd..0bc0be9aa949dfb89f726555bac16066127502fb 100644
--- a/static/deploy/cpp/CMakeLists.txt
+++ b/static/deploy/cpp/CMakeLists.txt
@@ -3,10 +3,11 @@ project(PaddleObjectDetector CXX C)
 
 option(WITH_MKL        "Compile demo with MKL/OpenBlas support,defaultuseMKL."          ON)
 option(WITH_GPU        "Compile demo with GPU/CPU, default use CPU."                    ON)
-option(WITH_STATIC_LIB "Compile demo with static/shared library, default use static."   ON)
-option(WITH_TENSORRT "Compile demo with TensorRT."   OFF)
+option(WITH_TENSORRT   "Compile demo with TensorRT."                                    OFF)
+
 
 SET(PADDLE_DIR "" CACHE PATH "Location of libraries")
+SET(PADDLE_LIB_NAME "" CACHE STRING "libpaddle_inference")
 SET(OPENCV_DIR "" CACHE PATH "Location of libraries")
 SET(CUDA_LIB "" CACHE PATH "Location of libraries")
 SET(CUDNN_LIB "" CACHE PATH "Location of libraries")
@@ -36,6 +37,7 @@ endif()
 if (NOT DEFINED PADDLE_DIR OR ${PADDLE_DIR} STREQUAL "")
     message(FATAL_ERROR "please set PADDLE_DIR with -DPADDLE_DIR=/path/paddle_influence_dir")
 endif()
+message("PADDLE_DIR IS:"${PADDLE_DIR})
 
 if (NOT DEFINED OPENCV_DIR OR ${OPENCV_DIR} STREQUAL "")
     message(FATAL_ERROR "please set OPENCV_DIR with -DOPENCV_DIR=/path/opencv")
@@ -70,6 +72,8 @@ link_directories("${PADDLE_DIR}/third_party/install/xxhash/lib")
 link_directories("${PADDLE_DIR}/paddle/lib/")
 link_directories("${CMAKE_CURRENT_BINARY_DIR}")
 
+
+
 if (WIN32)
   include_directories("${PADDLE_DIR}/paddle/fluid/inference")
   include_directories("${PADDLE_DIR}/paddle/include")
@@ -89,10 +93,6 @@ if (WIN32)
     set(CMAKE_C_FLAGS_RELEASE  "${CMAKE_C_FLAGS_RELEASE} /bigobj /MT")
     set(CMAKE_CXX_FLAGS_DEBUG  "${CMAKE_CXX_FLAGS_DEBUG} /bigobj /MTd")
     set(CMAKE_CXX_FLAGS_RELEASE   "${CMAKE_CXX_FLAGS_RELEASE} /bigobj /MT")
-    if (WITH_STATIC_LIB)
-        safe_set_static_flag()
-        add_definitions(-DSTATIC_LIB)
-    endif()
 else()
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -g -o2 -fopenmp -std=c++11")
     set(CMAKE_STATIC_LIBRARY_PREFIX "")
@@ -113,8 +113,8 @@ endif()
 
 if (NOT WIN32)
   if (WITH_TENSORRT AND WITH_GPU)
-	  include_directories("${TENSORRT_INC_DIR}")
-	  link_directories("${TENSORRT_LIB_DIR}")
+	  include_directories("${TENSORRT_INC_DIR}/")
+	  link_directories("${TENSORRT_LIB_DIR}/")
   endif()
 endif(NOT WIN32)
 
@@ -148,31 +148,30 @@ if(WITH_MKL)
     endif ()
   endif()
 else()
-  if (WIN32)
-    set(MATH_LIB ${PADDLE_DIR}/third_party/install/openblas/lib/openblas${CMAKE_STATIC_LIBRARY_SUFFIX})
-  else()
-    set(MATH_LIB ${PADDLE_DIR}/third_party/install/openblas/lib/libopenblas${CMAKE_STATIC_LIBRARY_SUFFIX})
-  endif()
+  set(MATH_LIB ${PADDLE_DIR}/third_party/install/openblas/lib/libopenblas${CMAKE_STATIC_LIBRARY_SUFFIX})
 endif()
 
+
 if (WIN32)
-    if(EXISTS "${PADDLE_DIR}/paddle/fluid/inference/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX}")
+    if(EXISTS "${PADDLE_DIR}/paddle/fluid/inference/${PADDLE_LIB_NAME}${CMAKE_STATIC_LIBRARY_SUFFIX}")
         set(DEPS
-            ${PADDLE_DIR}/paddle/fluid/inference/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
+            ${PADDLE_DIR}/paddle/fluid/inference/${PADDLE_LIB_NAME}${CMAKE_STATIC_LIBRARY_SUFFIX})
     else()
         set(DEPS
-            ${PADDLE_DIR}/paddle/lib/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
+            ${PADDLE_DIR}/paddle/lib/${PADDLE_LIB_NAME}${CMAKE_STATIC_LIBRARY_SUFFIX})
     endif()
 endif()
 
-if(WITH_STATIC_LIB)
-    set(DEPS
-        ${PADDLE_DIR}/paddle/lib/libpaddle_fluid${CMAKE_STATIC_LIBRARY_SUFFIX})
+
+if (WIN32)
+    set(DEPS ${PADDLE_DIR}/paddle/lib/${PADDLE_LIB_NAME}${CMAKE_STATIC_LIBRARY_SUFFIX})
 else()
-    set(DEPS
-        ${PADDLE_DIR}/paddle/lib/libpaddle_fluid${CMAKE_SHARED_LIBRARY_SUFFIX})
+    set(DEPS ${PADDLE_DIR}/paddle/lib/${PADDLE_LIB_NAME}${CMAKE_SHARED_LIBRARY_SUFFIX})
 endif()
 
+message("PADDLE_LIB_NAME:" ${PADDLE_LIB_NAME})
+message("DEPS:" $DEPS)
+
 if (NOT WIN32)
     set(DEPS ${DEPS}
         ${MATH_LIB} ${MKLDNN_LIB}
@@ -220,6 +219,7 @@ endif()
 set(DEPS ${DEPS} ${OpenCV_LIBS})
 add_executable(main src/main.cc src/preprocess_op.cc src/object_detector.cc)
 ADD_DEPENDENCIES(main ext-yaml-cpp)
+message("DEPS:" $DEPS)
 target_link_libraries(main ${DEPS})
 
 if (WIN32 AND WITH_MKL)
@@ -230,5 +230,12 @@ if (WIN32 AND WITH_MKL)
         COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/mklml.dll ./release/mklml.dll
         COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mklml/lib/libiomp5md.dll ./release/libiomp5md.dll
         COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/third_party/install/mkldnn/lib/mkldnn.dll ./release/mkldnn.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/paddle/lib/${PADDLE_LIB_NAME}.dll ./release/${PADDLE_LIB_NAME}.dll
+    )
+endif()
+
+if (WIN32)
+    add_custom_command(TARGET main POST_BUILD
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_DIR}/paddle/lib/${PADDLE_LIB_NAME}.dll ./release/${PADDLE_LIB_NAME}.dll
     )
 endif()
diff --git a/static/deploy/cpp/docs/Jetson_build.md b/static/deploy/cpp/docs/Jetson_build.md
index 0262ffbd1bf8bea2d62fcac7fda5080c6d472697..14850700e71cb8f3219b5ff2d4d01b5a30a9b250 100644
--- a/static/deploy/cpp/docs/Jetson_build.md
+++ b/static/deploy/cpp/docs/Jetson_build.md
@@ -34,7 +34,7 @@ cat /etc/nv_tegra_release
 
 ### Step2: 下载PaddlePaddle C++ 预测库 fluid_inference
 
-解压下载的[nv_jetson_cuda10_cudnn7.6_trt6(jetpack4.3)](https://paddle-inference-lib.bj.bcebos.com/2.0.0-nv-jetson-jetpack4.3-all/paddle_inference.tgz) 。
+解压下载的[nv_jetson_cuda10_cudnn7.6_trt6(jetpack4.3)](https://paddle-inference-lib.bj.bcebos.com/2.0.1-nv-jetson-jetpack4.3-all/paddle_inference.tgz) 。
 
 下载并解压后`/root/projects/fluid_inference`目录包含内容为：
 ```
@@ -74,6 +74,9 @@ TENSORRT_LIB_DIR=/usr/lib/aarch64-linux-gnu
 # Paddle 预测库路径
 PADDLE_DIR=/path/to/fluid_inference/
 
+# Paddle 预测库名称
+PADDLE_LIB_NAME=paddle_inference
+
 # Paddle 的预测库是否使用静态库来编译
 # 使用TensorRT时，Paddle的预测库通常为动态库
 WITH_STATIC_LIB=OFF
@@ -101,7 +104,8 @@ cmake .. \
     -DWITH_STATIC_LIB=${WITH_STATIC_LIB} \
     -DCUDA_LIB=${CUDA_LIB} \
     -DCUDNN_LIB=${CUDNN_LIB} \
-    -DOPENCV_DIR=${OPENCV_DIR}
+    -DOPENCV_DIR=${OPENCV_DIR} \
+    -DPADDLE_LIB_NAME={PADDLE_LIB_NAME}
 make
 ```
 
diff --git a/static/deploy/cpp/docs/linux_build.md b/static/deploy/cpp/docs/linux_build.md
index ab95dc786ba766e88d3ec069ef79124b506e9900..60c609663002c05e75f811ae1431e58cf4a333da 100644
--- a/static/deploy/cpp/docs/linux_build.md
+++ b/static/deploy/cpp/docs/linux_build.md
@@ -1,10 +1,10 @@
 # Linux平台编译指南
 
 ## 说明
-本文档在 `Linux`平台使用`GCC 4.8.5` 和 `GCC 4.9.4`测试过，如果需要使用更高G++版本编译使用，则需要重新编译Paddle预测库，请参考: [从源码编译Paddle预测库](https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/05_inference_deployment/inference/build_and_install_lib_cn.html#zhijiexiazaianzhuang) 。本文档使用的预置的opencv库是在ubuntu 16.04上用gcc4.8编译的，如果需要在ubuntu 16.04以外的系统环境编译，那么需自行编译opencv库。
+本文档在 `Linux`平台使用`GCC 8.2`测试过，如果需要使用其他G++版本编译使用，则需要重新编译Paddle预测库，请参考: [从源码编译Paddle预测库](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/advanced_guide/inference_deployment/inference/build_and_install_lib_cn.html)。本文档使用的预置的opencv库是在ubuntu 16.04上用gcc4.8编译的，如果需要在ubuntu 16.04以外的系统环境编译，那么需自行编译opencv库。
 
 ## 前置条件
-* G++ 4.8.2 ~ 4.9.4
+* G++ 8.2
 * CUDA 9.0 / CUDA 10.0, cudnn 7+ （仅在使用GPU版本的预测库时需要）
 * CMake 3.0+
 
@@ -19,7 +19,7 @@
 
 ### Step2: 下载PaddlePaddle C++ 预测库 fluid_inference
 
-PaddlePaddle C++ 预测库针对不同的`CPU`和`CUDA`版本提供了不同的预编译版本，请根据实际情况下载:  [C++预测库下载列表](https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/05_inference_deployment/inference/build_and_install_lib_cn.html#linux)
+PaddlePaddle C++ 预测库针对不同的`CPU`和`CUDA`版本提供了不同的预编译版本，请根据实际情况下载:  [C++预测库下载列表](https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/05_inference_deployment/inference/build_and_install_lib_cn.html)
 
 
 下载并解压后`/root/projects/fluid_inference`目录包含内容为：
@@ -58,9 +58,8 @@ TENSORRT_LIB_DIR=/path/to/TensorRT/lib
 # Paddle 预测库路径
 PADDLE_DIR=/path/to/fluid_inference
 
-# Paddle 的预测库是否使用静态库来编译
-# 使用TensorRT时，Paddle的预测库通常为动态库
-WITH_STATIC_LIB=OFF
+# Paddle 预测库名称
+PADDLE_LIB_NAME=paddle_inference
 
 # CUDA 的 lib 路径
 CUDA_LIB=/path/to/cuda/lib
@@ -68,10 +67,6 @@ CUDA_LIB=/path/to/cuda/lib
 # CUDNN 的 lib 路径
 CUDNN_LIB=/path/to/cudnn/lib
 
-# 修改脚本设置好主要参数后，执行`build`脚本：
-sh ./scripts/build.sh
-
-
 # 请检查以上各个路径是否正确
 
 # 以下无需改动
@@ -82,10 +77,10 @@ cmake .. \
     -DTENSORRT_LIB_DIR=${TENSORRT_LIB_DIR} \
     -DTENSORRT_INC_DIR=${TENSORRT_INC_DIR} \
     -DPADDLE_DIR=${PADDLE_DIR} \
-    -DWITH_STATIC_LIB=${WITH_STATIC_LIB} \
     -DCUDA_LIB=${CUDA_LIB} \
     -DCUDNN_LIB=${CUDNN_LIB} \
-    -DOPENCV_DIR=${OPENCV_DIR}
+    -DOPENCV_DIR=${OPENCV_DIR} \
+    -DPADDLE_LIB_NAME={PADDLE_LIB_NAME}
 make
 
 ```
@@ -94,6 +89,7 @@ make
  ```shell
  sh ./scripts/build.sh
  ```
+
 **注意**: OPENCV依赖OPENBLAS，Ubuntu用户需确认系统是否已存在`libopenblas.so`。如未安装，可执行apt-get install libopenblas-dev进行安装。
 
 ### Step5: 预测及可视化
diff --git a/static/deploy/cpp/docs/windows_vs2019_build.md b/static/deploy/cpp/docs/windows_vs2019_build.md
index 7b8dcff078281d39773d862c48df2f88d645105b..aca5d3ab970cb4aa9aac9a6ea26b2a7c621acac2 100644
--- a/static/deploy/cpp/docs/windows_vs2019_build.md
+++ b/static/deploy/cpp/docs/windows_vs2019_build.md
@@ -24,7 +24,7 @@ git clone https://github.com/PaddlePaddle/PaddleDetection.git
 
 ### Step2: 下载PaddlePaddle C++ 预测库 fluid_inference
 
-PaddlePaddle C++ 预测库针对不同的`CPU`和`CUDA`版本提供了不同的预编译版本，请根据实际情况下载:  [C++预测库下载列表](https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/05_inference_deployment/inference/windows_cpp_inference.html#windows)
+PaddlePaddle C++ 预测库针对不同的`CPU`和`CUDA`版本提供了不同的预编译版本，请根据实际情况下载:  [C++预测库下载列表](https://www.paddlepaddle.org.cn/documentation/docs/zh/guides/05_inference_deployment/inference/windows_cpp_inference.html)
 
 解压后`D:\projects\fluid_inference`目录包含内容为：
 ```
@@ -62,18 +62,23 @@ cd D:\projects\PaddleDetection\deploy\cpp
 | *CUDNN_LIB | CUDNN的库路径 |
 | OPENCV_DIR  | OpenCV的安装路径， |
 | PADDLE_DIR | Paddle预测库的路径 |
+| PADDLE_LIB_NAME | Paddle 预测库名称 |
 
+**注意：** 1. 使用`CPU`版预测库，请把`WITH_GPU`的勾去掉 2. 如果使用的是`openblas`版本，请把`WITH_MKL`勾去掉
+
+执行如下命令项目文件：
 ```
-cmake . -G "Visual Studio 16 2019" -A x64 -T host=x64 -DWITH_GPU=ON -DWITH_MKL=ON -DCMAKE_BUILD_TYPE=Release -DCUDA_LIB=path_to_cuda_lib -DCUDNN_LIB=path_to_cudnn_lib -DPADDLE_DIR=path_to_paddle_lib -DOPENCV_DIR=path_to_opencv
+cmake . -G "Visual Studio 16 2019" -A x64 -T host=x64 -DWITH_GPU=ON -DWITH_MKL=ON -DCMAKE_BUILD_TYPE=Release -DCUDA_LIB=path_to_cuda_lib -DCUDNN_LIB=path_to_cudnn_lib -DPADDLE_DIR=path_to_paddle_lib -DPADDLE_LIB_NAME=paddle_inference -DOPENCV_DIR=path_to_opencv
 ```
 
 例如：
 ```
-cmake . -G "Visual Studio 16 2019" -A x64 -T host=x64 -DWITH_GPU=ON -DWITH_MKL=ON -DCMAKE_BUILD_TYPE=Release -DCUDA_LIB=D:\projects\packages\cuda10_0\lib\x64 -DCUDNN_LIB=D:\projects\packages\cuda10_0\lib\x64 -DPADDLE_DIR=D:\projects\packages\fluid_inference -DOPENCV_DIR=D:\projects\packages\opencv3_4_6
+cmake . -G "Visual Studio 16 2019" -A x64 -T host=x64 -DWITH_GPU=ON -DWITH_MKL=ON -DCMAKE_BUILD_TYPE=Release -DCUDA_LIB=D:\projects\packages\cuda10_0\lib\x64 -DCUDNN_LIB=D:\projects\packages\cuda10_0\lib\x64 -DPADDLE_DIR=D:\projects\packages\fluid_inference -DPADDLE_LIB_NAME=paddle_inference -DOPENCV_DIR=D:\projects\packages\opencv3_4_6
 ```
 
 3. 编译
-用`Visual Studio 16 2019`打开`cpp`文件夹下的`PaddleObjectDetector.sln`，点击`生成`->`全部生成`
+用`Visual Studio 16 2019`打开`cpp`文件夹下的`PaddleObjectDetector.sln`，将编译模式设置为`Release`，点击`生成`->`全部生成
+
 
 ### Step5: 预测及可视化
 
diff --git a/static/deploy/cpp/scripts/build.sh b/static/deploy/cpp/scripts/build.sh
index fb6ca625e9bcc1a84dbf6728e809b08e6432d075..803fbab7d7fe7cfbc7ce1bcc7543692a24d27cb4 100644
--- a/static/deploy/cpp/scripts/build.sh
+++ b/static/deploy/cpp/scripts/build.sh
@@ -7,21 +7,17 @@ WITH_MKL=ON
 # 是否集成 TensorRT(仅WITH_GPU=ON 有效)
 WITH_TENSORRT=OFF
 
-# 是否使用2.0rc1预测库
-USE_PADDLE_20RC1=OFF
+# paddle 预测库lib名称，由于不同平台不同版本预测库lib名称不同，请查看所下载的预测库中`paddle_inference/lib/`文件夹下`lib`的名称
+PADDLE_LIB_NAME=libpaddle_inference
 
 # TensorRT 的include路径
-TENSORRT_INC_DIR=/path/to/tensorrt/lib
+TENSORRT_INC_DIR=/path/to/tensorrt/include
 
 # TensorRT 的lib路径
-TENSORRT_LIB_DIR=/path/to/tensorrt/include
+TENSORRT_LIB_DIR=/path/to/tensorrt/lib
 
 # Paddle 预测库路径
-PADDLE_DIR=/path/to/fluid_inference/
-
-# Paddle 的预测库是否使用静态库来编译
-# 使用TensorRT时，Paddle的预测库通常为动态库
-WITH_STATIC_LIB=OFF
+PADDLE_DIR=/paddle/to/paddle_inference
 
 # CUDA 的 lib 路径
 CUDA_LIB=/path/to/cuda/lib
@@ -39,11 +35,11 @@ then
   echo "set OPENCV_DIR for x86_64"
   # linux系统通过以下命令下载预编译的opencv
   mkdir -p $(pwd)/deps && cd $(pwd)/deps
-  wget -c https://bj.bcebos.com/paddleseg/deploy/opencv3.4.6gcc4.8ffmpeg.tar.gz2
-  tar xvfj opencv3.4.6gcc4.8ffmpeg.tar.gz2 && cd ..
+  wget -c https://paddledet.bj.bcebos.com/data/opencv3.4.6gcc8.2ffmpeg.zip
+  unzip opencv3.4.6gcc8.2ffmpeg.zip && cd ..
 
   # set OPENCV_DIR
-  OPENCV_DIR=$(pwd)/deps/opencv3.4.6gcc4.8ffmpeg/
+  OPENCV_DIR=$(pwd)/deps/opencv3.4.6gcc8.2ffmpeg
 
 elif [ "$MACHINE_TYPE" = "aarch64" ]
 then
@@ -76,7 +72,8 @@ cmake .. \
     -DWITH_STATIC_LIB=${WITH_STATIC_LIB} \
     -DCUDA_LIB=${CUDA_LIB} \
     -DCUDNN_LIB=${CUDNN_LIB} \
-    -DOPENCV_DIR=${OPENCV_DIR}
+    -DOPENCV_DIR=${OPENCV_DIR} \
+    -DPADDLE_LIB_NAME=${PADDLE_LIB_NAME}
 
 make
 echo "make finished!"
diff --git a/static/ppdet/utils/export_utils.py b/static/ppdet/utils/export_utils.py
index 1904e7cfd9ba7497c2aa86139f2cdbc599c70799..3579ddb495f8e6055a512f9d8fe32897ca7abe22 100644
--- a/static/ppdet/utils/export_utils.py
+++ b/static/ppdet/utils/export_utils.py
@@ -37,7 +37,7 @@ TRT_MIN_SUBGRAPH = {
     'EfficientDet': 40,
     'Face': 3,
     'TTFNet': 3,
-    'FCOS': 3,
+    'FCOS': 33,
     'SOLOv2': 60,
 }
 RESIZE_SCALE_SET = {