infer_cpp_docu (#5469)

* infer_cpp_docu * fix:change the path

infer_cpp_docu (#5469)
* infer_cpp_docu * fix:change the path
052fcbfe · feng_shuai · GitHub · 004e4c4d · 052fcbfe · 052fcbfe
14 changed file
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/CMakeLists.txt
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/CMakeLists.txt
+project(clas_system CXX C)
+
+option(WITH_MKL        "Compile demo with MKL/OpenBlas support, default use MKL."       ON)
+option(WITH_GPU        "Compile demo with GPU/CPU, default use CPU."                    OFF)
+option(WITH_STATIC_LIB "Compile demo with static/shared library, default use static."   ON)
+option(WITH_TENSORRT "Compile demo with TensorRT."   OFF)
+
+SET(PADDLE_LIB "" CACHE PATH "Location of libraries")
+SET(OPENCV_DIR "" CACHE PATH "Location of libraries")
+SET(CUDA_LIB "" CACHE PATH "Location of libraries")
+SET(CUDNN_LIB "" CACHE PATH "Location of libraries")
+SET(TENSORRT_DIR "" CACHE PATH "Compile demo with TensorRT")
+
+set(DEMO_NAME "clas_system")
+
+
+macro(safe_set_static_flag)
+    foreach(flag_var
+        CMAKE_CXX_FLAGS CMAKE_CXX_FLAGS_DEBUG CMAKE_CXX_FLAGS_RELEASE
+        CMAKE_CXX_FLAGS_MINSIZEREL CMAKE_CXX_FLAGS_RELWITHDEBINFO)
+      if(${flag_var} MATCHES "/MD")
+        string(REGEX REPLACE "/MD" "/MT" ${flag_var} "${${flag_var}}")
+      endif(${flag_var} MATCHES "/MD")
+    endforeach(flag_var)
+endmacro()
+
+if (WITH_MKL)
+    ADD_DEFINITIONS(-DUSE_MKL)
+endif()
+
+if(NOT DEFINED PADDLE_LIB)
+  message(FATAL_ERROR "please set PADDLE_LIB with -DPADDLE_LIB=/path/paddle/lib")
+endif()
+
+if(NOT DEFINED OPENCV_DIR)
+    message(FATAL_ERROR "please set OPENCV_DIR with -DOPENCV_DIR=/path/opencv")
+endif()
+
+
+if (WIN32)
+  include_directories("${PADDLE_LIB}/paddle/fluid/inference")
+  include_directories("${PADDLE_LIB}/paddle/include")
+  link_directories("${PADDLE_LIB}/paddle/fluid/inference")
+  find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/build/ NO_DEFAULT_PATH)
+
+else ()
+  find_package(OpenCV REQUIRED PATHS ${OPENCV_DIR}/share/OpenCV NO_DEFAULT_PATH)
+  include_directories("${PADDLE_LIB}/paddle/include")
+  link_directories("${PADDLE_LIB}/paddle/lib")
+endif ()
+include_directories(${OpenCV_INCLUDE_DIRS})
+
+if (WIN32)
+    add_definitions("/DGOOGLE_GLOG_DLL_DECL=")
+    set(CMAKE_C_FLAGS_DEBUG   "${CMAKE_C_FLAGS_DEBUG} /bigobj /MTd")
+    set(CMAKE_C_FLAGS_RELEASE  "${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 -o3 -std=c++11")
+    set(CMAKE_STATIC_LIBRARY_PREFIX "")
+endif()
+message("flags" ${CMAKE_CXX_FLAGS})
+
+
+if (WITH_GPU)
+    if (NOT DEFINED CUDA_LIB OR ${CUDA_LIB} STREQUAL "")
+        message(FATAL_ERROR "please set CUDA_LIB with -DCUDA_LIB=/path/cuda-8.0/lib64")
+    endif()
+    if (NOT WIN32)
+        if (NOT DEFINED CUDNN_LIB)
+            message(FATAL_ERROR "please set CUDNN_LIB with -DCUDNN_LIB=/path/cudnn_v7.4/cuda/lib64")
+        endif()
+    endif(NOT WIN32)
+endif()
+
+include_directories("${PADDLE_LIB}/third_party/install/protobuf/include")
+include_directories("${PADDLE_LIB}/third_party/install/glog/include")
+include_directories("${PADDLE_LIB}/third_party/install/gflags/include")
+include_directories("${PADDLE_LIB}/third_party/install/xxhash/include")
+include_directories("${PADDLE_LIB}/third_party/install/zlib/include")
+include_directories("${PADDLE_LIB}/third_party/boost")
+include_directories("${PADDLE_LIB}/third_party/eigen3")
+
+include_directories("${CMAKE_SOURCE_DIR}/")
+
+if (NOT WIN32)
+  if (WITH_TENSORRT AND WITH_GPU)
+     include_directories("${TENSORRT_DIR}/include")
+     link_directories("${TENSORRT_DIR}/lib")
+  endif()
+endif(NOT WIN32)
+
+link_directories("${PADDLE_LIB}/third_party/install/zlib/lib")
+
+link_directories("${PADDLE_LIB}/third_party/install/protobuf/lib")
+link_directories("${PADDLE_LIB}/third_party/install/glog/lib")
+link_directories("${PADDLE_LIB}/third_party/install/gflags/lib")
+link_directories("${PADDLE_LIB}/third_party/install/xxhash/lib")
+link_directories("${PADDLE_LIB}/paddle/lib")
+
+
+if(WITH_MKL)
+  include_directories("${PADDLE_LIB}/third_party/install/mklml/include")
+  if (WIN32)
+    set(MATH_LIB ${PADDLE_LIB}/third_party/install/mklml/lib/mklml.lib
+            ${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5md.lib)
+  else ()
+    set(MATH_LIB ${PADDLE_LIB}/third_party/install/mklml/lib/libmklml_intel${CMAKE_SHARED_LIBRARY_SUFFIX}
+            ${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5${CMAKE_SHARED_LIBRARY_SUFFIX})
+    execute_process(COMMAND cp -r ${PADDLE_LIB}/third_party/install/mklml/lib/libmklml_intel${CMAKE_SHARED_LIBRARY_SUFFIX} /usr/lib)
+  endif ()
+  set(MKLDNN_PATH "${PADDLE_LIB}/third_party/install/mkldnn")
+  if(EXISTS ${MKLDNN_PATH})
+    include_directories("${MKLDNN_PATH}/include")
+    if (WIN32)
+      set(MKLDNN_LIB ${MKLDNN_PATH}/lib/mkldnn.lib)
+    else ()
+      set(MKLDNN_LIB ${MKLDNN_PATH}/lib/libmkldnn.so.0)
+    endif ()
+  endif()
+else()
+  if (WIN32)
+    set(MATH_LIB ${PADDLE_LIB}/third_party/install/openblas/lib/openblas${CMAKE_STATIC_LIBRARY_SUFFIX})
+  else ()
+    set(MATH_LIB ${PADDLE_LIB}/third_party/install/openblas/lib/libopenblas${CMAKE_STATIC_LIBRARY_SUFFIX})
+  endif ()
+endif()
+
+# Note: libpaddle_inference_api.so/a must put before libpaddle_fluid.so/a
+if(WITH_STATIC_LIB)
+  if(WIN32)
+    set(DEPS
+        ${PADDLE_LIB}/paddle/lib/paddle_inference${CMAKE_STATIC_LIBRARY_SUFFIX})
+  else()
+    set(DEPS
+        ${PADDLE_LIB}/paddle/lib/libpaddle_inference${CMAKE_STATIC_LIBRARY_SUFFIX})
+  endif()
+else()
+  if(WIN32)
+    set(DEPS
+        ${PADDLE_LIB}/paddle/lib/paddle_inference${CMAKE_SHARED_LIBRARY_SUFFIX})
+  else()
+    set(DEPS
+        ${PADDLE_LIB}/paddle/lib/libpaddle_inference${CMAKE_SHARED_LIBRARY_SUFFIX})
+  endif()
+endif(WITH_STATIC_LIB)
+
+if (NOT WIN32)
+    set(DEPS ${DEPS}
+        ${MATH_LIB} ${MKLDNN_LIB}
+        glog gflags protobuf z xxhash
+        )
+    if(EXISTS "${PADDLE_LIB}/third_party/install/snappystream/lib")
+        set(DEPS ${DEPS} snappystream)
+    endif()
+    if (EXISTS "${PADDLE_LIB}/third_party/install/snappy/lib")
+        set(DEPS ${DEPS} snappy)
+    endif()
+else()
+    set(DEPS ${DEPS}
+        ${MATH_LIB} ${MKLDNN_LIB}
+        glog gflags_static libprotobuf xxhash)
+    set(DEPS ${DEPS} libcmt shlwapi)
+    if (EXISTS "${PADDLE_LIB}/third_party/install/snappy/lib")
+        set(DEPS ${DEPS} snappy)
+    endif()
+    if(EXISTS "${PADDLE_LIB}/third_party/install/snappystream/lib")
+        set(DEPS ${DEPS} snappystream)
+    endif()
+endif(NOT WIN32)
+
+
+if(WITH_GPU)
+  if(NOT WIN32)
+    if (WITH_TENSORRT)
+      set(DEPS ${DEPS} ${TENSORRT_DIR}/lib/libnvinfer${CMAKE_SHARED_LIBRARY_SUFFIX})
+      set(DEPS ${DEPS} ${TENSORRT_DIR}/lib/libnvinfer_plugin${CMAKE_SHARED_LIBRARY_SUFFIX})
+    endif()
+    set(DEPS ${DEPS} ${CUDA_LIB}/libcudart${CMAKE_SHARED_LIBRARY_SUFFIX})
+    set(DEPS ${DEPS} ${CUDNN_LIB}/libcudnn${CMAKE_SHARED_LIBRARY_SUFFIX})
+  else()
+    set(DEPS ${DEPS} ${CUDA_LIB}/cudart${CMAKE_STATIC_LIBRARY_SUFFIX} )
+    set(DEPS ${DEPS} ${CUDA_LIB}/cublas${CMAKE_STATIC_LIBRARY_SUFFIX} )
+    set(DEPS ${DEPS} ${CUDNN_LIB}/cudnn${CMAKE_STATIC_LIBRARY_SUFFIX})
+  endif()
+endif()
+
+
+if (NOT WIN32)
+    set(EXTERNAL_LIB "-ldl -lrt -lgomp -lz -lm -lpthread")
+    set(DEPS ${DEPS} ${EXTERNAL_LIB})
+endif()
+
+set(DEPS ${DEPS} ${OpenCV_LIBS})
+
+AUX_SOURCE_DIRECTORY(./src SRCS)
+add_executable(${DEMO_NAME} ${SRCS})
+
+target_link_libraries(${DEMO_NAME} ${DEPS})
+
+if (WIN32 AND WITH_MKL)
+    add_custom_command(TARGET ${DEMO_NAME} POST_BUILD
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mklml/lib/mklml.dll ./mklml.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5md.dll ./libiomp5md.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mkldnn/lib/mkldnn.dll ./mkldnn.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mklml/lib/mklml.dll ./release/mklml.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mklml/lib/libiomp5md.dll ./release/libiomp5md.dll
+        COMMAND ${CMAKE_COMMAND} -E copy_if_different ${PADDLE_LIB}/third_party/install/mkldnn/lib/mkldnn.dll ./release/mkldnn.dll
+    )
+endif()
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/README.md
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/README.md
+# 服务器端C++预测
+
+本教程将介绍在服务器端部署mobilenet_v3_small模型的详细步骤。
+
+
+## 1. 准备环境
+
+### 运行准备
+- Linux环境，推荐使用docker[安装说明](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/docker/linux-docker.html)。
+
+### 1.1 编译opencv库
+
+* 首先需要从opencv官网上下载Linux环境下的源码，以3.4.7版本为例，下载及解压缩命令如下：
+
+```
+cd deploy/inference_cpp
+wget https://github.com/opencv/opencv/archive/3.4.7.tar.gz
+tar -xvf 3.4.7.tar.gz
+```
+
+最终可以在当前目录下看到`opencv-3.4.7/`的文件夹。
+
+* 编译opencv，首先设置opencv源码路径(`root_path`)以及安装路径(`install_path`)，`root_path`为下载的opencv源码路径，`install_path`为opencv的安装路径。在本例中，源码路径即为当前目录下的`opencv-3.4.7/`。
+
+```shell
+cd ./opencv-3.4.7
+export root_path=$PWD
+export install_path=${root_path}/opencv3
+```
+
+* 然后在opencv源码路径下，按照下面的命令进行编译。
+
+```shell
+rm -rf build
+mkdir build
+cd build
+
+cmake .. \
+    -DCMAKE_INSTALL_PREFIX=${install_path} \
+    -DCMAKE_BUILD_TYPE=Release \
+    -DBUILD_SHARED_LIBS=OFF \
+    -DWITH_IPP=OFF \
+    -DBUILD_IPP_IW=OFF \
+    -DWITH_LAPACK=OFF \
+    -DWITH_EIGEN=OFF \
+    -DCMAKE_INSTALL_LIBDIR=lib64 \
+    -DWITH_ZLIB=ON \
+    -DBUILD_ZLIB=ON \
+    -DWITH_JPEG=ON \
+    -DBUILD_JPEG=ON \
+    -DWITH_PNG=ON \
+    -DBUILD_PNG=ON \
+    -DWITH_TIFF=ON \
+    -DBUILD_TIFF=ON
+
+make -j
+make install
+```
+
+* `make install`完成之后，会在该文件夹下生成opencv头文件和库文件，用于后面的代码编译。
+
+以opencv3.4.7版本为例，最终在安装路径下的文件结构如下所示。**注意**：不同的opencv版本，下述的文件结构可能不同。
+
+```
+opencv3/
+|-- bin     :可执行文件
+|-- include :头文件
+|-- lib64   :库文件
+|-- share   :部分第三方库
+```
+
+### 1.2 下载或者编译Paddle预测库
+
+* 有2种方式获取Paddle预测库，下面进行详细介绍。
+
+#### 1.2.1 预测库源码编译
+* 如果希望获取最新预测库特性，可以从Paddle github上克隆最新代码，源码编译预测库。
+* 可以参考[Paddle预测库官网](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/guides/05_inference_deployment/inference/build_and_install_lib_cn.html#id16)的说明，从github上获取Paddle代码，然后进行编译，生成最新的预测库。使用git获取代码方法如下。
+
+```shell
+git clone https://github.com/PaddlePaddle/Paddle.git
+```
+
+* 进入Paddle目录后，使用如下命令编译。
+
+```shell
+rm -rf build
+mkdir build
+cd build
+
+cmake  .. \
+    -DWITH_CONTRIB=OFF \
+    -DWITH_MKL=ON \
+    -DWITH_MKLDNN=ON  \
+    -DWITH_TESTING=OFF \
+    -DCMAKE_BUILD_TYPE=Release \
+    -DWITH_INFERENCE_API_TEST=OFF \
+    -DON_INFER=ON \
+    -DWITH_PYTHON=ON
+make -j
+make inference_lib_dist
+```
+
+更多编译参数选项可以参考Paddle C++预测库官网：[https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/guides/05_inference_deployment/inference/build_and_install_lib_cn.html#id16](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/guides/05_inference_deployment/inference/build_and_install_lib_cn.html#id16)。
+
+
+* 编译完成之后，可以在`build/paddle_inference_install_dir/`文件下看到生成了以下文件及文件夹。
+
+```
+build/paddle_inference_install_dir/
+|-- CMakeCache.txt
+|-- paddle
+|-- third_party
+|-- version.txt
+```
+
+其中`paddle`就是之后进行C++预测时所需的Paddle库，`version.txt`中包含当前预测库的版本信息。
+
+#### 1.2.2 直接下载安装
+
+* [Paddle预测库官网](https://paddleinference.paddlepaddle.org.cn/user_guides/download_lib.html)上提供了不同cuda版本的Linux预测库，可以在官网查看并选择合适的预测库版本。
+
+  以`manylinux_cuda11.1_cudnn8.1_avx_mkl_trt7_gcc8.2`版本为例，使用下述命令下载并解压：
+
+
+```shell
+wget https://paddle-inference-lib.bj.bcebos.com/2.2.2/cxx_c/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda11.1_cudnn8.1.1_trt7.2.3.4/paddle_inference.tgz
+
+tar -xvf paddle_inference.tgz
+```
+
+
+最终会在当前的文件夹中生成`paddle_inference/`的子文件夹,文件内容和上述的paddle_inference_install_dir一样。
+
+
+## 2 开始运行
+
+### 2.1 将模型导出为inference model
+
+* 可以参考[模型导出](../../tools/export_model.py)，导出`inference model`，用于模型预测。得到预测模型后，假设模型文件放在`inference`目录下，则目录结构如下。
+
+```
+mobilenet_v3_small_infer/
+|--inference.pdmodel
+|--inference.pdiparams
+|--inference.pdiparams.info
+```
+**注意**：上述文件中，`inference.pdmodel`文件存储了模型结构信息，`inference.pdiparams`文件存储了模型参数信息。注意两个文件的路径需要与配置文件`tools/config.txt`中的`cls_model_path`和`cls_params_path`参数对应一致。
+
+### 2.2 编译 C++预测demo
+
+* 编译命令如下，其中Paddle C++预测库、opencv等其他依赖库的地址需要换成自己机器上的实际地址。
+
+
+```shell
+sh tools/build.sh
+```
+
+具体地，`tools/build.sh`中内容如下。
+
+```shell
+OPENCV_DIR=your_opencv_dir
+LIB_DIR=your_paddle_inference_dir
+CUDA_LIB_DIR=your_cuda_lib_dir
+CUDNN_LIB_DIR=your_cudnn_lib_dir
+TENSORRT_DIR=your_tensorrt_lib_dir
+
+BUILD_DIR=build
+rm -rf ${BUILD_DIR}
+mkdir ${BUILD_DIR}
+cd ${BUILD_DIR}
+cmake .. \
+    -DPADDLE_LIB=${LIB_DIR} \
+    -DWITH_MKL=ON \
+    -DDEMO_NAME=clas_system \
+    -DWITH_GPU=OFF \
+    -DWITH_STATIC_LIB=OFF \
+    -DWITH_TENSORRT=OFF \
+    -DTENSORRT_DIR=${TENSORRT_DIR} \
+    -DOPENCV_DIR=${OPENCV_DIR} \
+    -DCUDNN_LIB=${CUDNN_LIB_DIR} \
+    -DCUDA_LIB=${CUDA_LIB_DIR} \
+
+make -j
+```
+
+上述命令中，
+
+* `OPENCV_DIR`为opencv编译安装的地址（本例中为`opencv-3.4.7/opencv3`文件夹的路径）；
+
+* `LIB_DIR`为下载的Paddle预测库（`paddle_inference`文件夹），或编译生成的Paddle预测库（`build/paddle_inference_install_dir`文件夹）的路径；
+
+* `CUDA_LIB_DIR`为cuda库文件地址，在docker中为`/usr/local/cuda/lib64`；
+
+* `CUDNN_LIB_DIR`为cudnn库文件地址，在docker中为`/usr/lib64`。
+
+* `TENSORRT_DIR`是tensorrt库文件地址，在dokcer中为`/usr/local/TensorRT-7.2.3.4/`，TensorRT需要结合GPU使用。
+
+在执行上述命令，编译完成之后，会在当前路径下生成`build`文件夹，其中生成一个名为`clas_system`的可执行文件。
+
+
+### 运行demo
+* 首先修改`tools/config.txt`中对应字段：
+  * use_gpu：是否使用GPU；
+  * gpu_id：使用的GPU卡号；
+  * gpu_mem：显存；
+  * cpu_math_library_num_threads：底层科学计算库所用线程的数量；
+  * use_mkldnn：是否使用MKLDNN加速；
+  * use_tensorrt: 是否使用tensorRT进行加速；
+  * use_fp16：是否使用半精度浮点数进行计算，该选项仅在use_tensorrt为true时有效；
+  * cls_model_path：预测模型结构文件路径；
+  * cls_params_path：预测模型参数文件路径；
+  * resize_short_size：预处理时图像缩放大小；
+  * crop_size：预处理时图像裁剪后的大小。
+
+* 然后修改`tools/run.sh`：
+  * `./build/clas_system ./tools/config.txt ../../images/demo.jpg`
+  * 上述命令中分别为：编译得到的可执行文件`clas_system`；运行时的配置文件`config.txt`；待预测的图像。
+
+* 最后执行以下命令，完成对一幅图像的分类。
+
+```shell
+sh tools/run.sh
+```
+对于下面的图像进行预测
+
+<div align="center">
+    <img src="../../images/demo.jpg" width=300">
+</div>
+
+* 最终屏幕上会输出结果，如下所示
+```
+class id: 8
+
+score: 0.9014717937
+
+Current image path: ../../images/demo.jpg
+
+Current time cost: 0.0473620000 s, average time cost in all: 0.0473620000 s.
+
+```
+
+表示预测的类别ID是`8`，置信度为`0.901`，该结果与基于训练引擎的结果完全一致。
+其中`class id`表示置信度最高的类别对应的id，score表示图片属于该类别的概率。
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/include/cls.h
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/include/cls.h
+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include "opencv2/core.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/imgproc.hpp"
+#include "paddle_inference_api.h"
+#include <chrono>
+#include <iomanip>
+#include <iostream>
+#include <ostream>
+#include <vector>
+
+#include <cstring>
+#include <fstream>
+#include <numeric>
+
+#include <include/preprocess_op.h>
+
+using namespace paddle_infer;
+
+namespace MobileNetV3 {
+
+class Classifier {
+public:
+  explicit Classifier(const std::string &model_path,
+                      const std::string &params_path, const bool &use_gpu,
+                      const int &gpu_id, const int &gpu_mem,
+                      const int &cpu_math_library_num_threads,
+                      const bool &use_mkldnn, const bool &use_tensorrt,
+                      const bool &use_fp16, const int &resize_short_size,
+                      const int &crop_size) {
+    this->use_gpu_ = use_gpu;
+    this->gpu_id_ = gpu_id;
+    this->gpu_mem_ = gpu_mem;
+    this->cpu_math_library_num_threads_ = cpu_math_library_num_threads;
+    this->use_mkldnn_ = use_mkldnn;
+    this->use_tensorrt_ = use_tensorrt;
+    this->use_fp16_ = use_fp16;
+
+    this->resize_short_size_ = resize_short_size;
+    this->crop_size_ = crop_size;
+
+    LoadModel(model_path, params_path);
+  }
+
+  // Load Paddle inference model
+  void LoadModel(const std::string &model_path, const std::string &params_path);
+
+  // Run predictor
+  double Run(cv::Mat &img);
+
+private:
+  std::shared_ptr<Predictor> predictor_;
+
+  bool use_gpu_ = false;
+  int gpu_id_ = 0;
+  int gpu_mem_ = 4000;
+  int cpu_math_library_num_threads_ = 4;
+  bool use_mkldnn_ = false;
+  bool use_tensorrt_ = false;
+  bool use_fp16_ = false;
+
+  std::vector<float> mean_ = {0.485f, 0.456f, 0.406f};
+  std::vector<float> scale_ = {1 / 0.229f, 1 / 0.224f, 1 / 0.225f};
+  bool is_scale_ = true;
+
+  int resize_short_size_ = 256;
+  int crop_size_ = 224;
+
+  // pre-process
+  ResizeImg resize_op_;
+  Normalize normalize_op_;
+  Permute permute_op_;
+  CenterCropImg crop_op_;
+};
+
+} // namespace MobileNetV3
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/include/cls_config.h
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/include/cls_config.h
+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include <iomanip>
+#include <iostream>
+#include <map>
+#include <ostream>
+#include <string>
+#include <vector>
+
+#include "include/utility.h"
+
+namespace MobileNetV3 {
+
+class ClsConfig {
+public:
+  explicit ClsConfig(const std::string &config_file) {
+    config_map_ = LoadConfig(config_file);
+
+    this->use_gpu = bool(stoi(config_map_["use_gpu"]));
+
+    this->gpu_id = stoi(config_map_["gpu_id"]);
+
+    this->gpu_mem = stoi(config_map_["gpu_mem"]);
+
+    this->cpu_math_library_num_threads =
+        stoi(config_map_["cpu_math_library_num_threads"]);
+
+    this->use_mkldnn = bool(stoi(config_map_["use_mkldnn"]));
+
+    this->use_tensorrt = bool(stoi(config_map_["use_tensorrt"]));
+    this->use_fp16 = bool(stoi(config_map_["use_fp16"]));
+
+    this->cls_model_path.assign(config_map_["cls_model_path"]);
+
+    this->cls_params_path.assign(config_map_["cls_params_path"]);
+
+    this->resize_short_size = stoi(config_map_["resize_short_size"]);
+
+    this->crop_size = stoi(config_map_["crop_size"]);
+  }
+
+  bool use_gpu = false;
+
+  int gpu_id = 0;
+
+  int gpu_mem = 4000;
+
+  int cpu_math_library_num_threads = 1;
+
+  bool use_mkldnn = false;
+
+  bool use_tensorrt = false;
+  bool use_fp16 = false;
+
+  std::string cls_model_path;
+
+  std::string cls_params_path;
+
+  int resize_short_size = 256;
+  int crop_size = 224;
+
+  void PrintConfigInfo();
+
+private:
+  // Load configuration
+  std::map<std::string, std::string> LoadConfig(const std::string &config_file);
+
+  std::vector<std::string> split(const std::string &str,
+                                 const std::string &delim);
+
+  std::map<std::string, std::string> config_map_;
+};
+
+} // namespace MobileNetV3
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/include/preprocess_op.h
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/include/preprocess_op.h
+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include "opencv2/core.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/imgproc.hpp"
+#include <chrono>
+#include <iomanip>
+#include <iostream>
+#include <ostream>
+#include <vector>
+
+#include <cstring>
+#include <fstream>
+#include <numeric>
+
+using namespace std;
+
+namespace MobileNetV3 {
+
+class Normalize {
+public:
+  virtual void Run(cv::Mat *im, const std::vector<float> &mean,
+                   const std::vector<float> &scale, const bool is_scale = true);
+};
+
+// RGB -> CHW
+class Permute {
+public:
+  virtual void Run(const cv::Mat *im, float *data);
+};
+
+class CenterCropImg {
+public:
+  virtual void Run(cv::Mat &im, const int crop_size = 224);
+};
+
+class ResizeImg {
+public:
+  virtual void Run(const cv::Mat &img, cv::Mat &resize_img, int max_size_len);
+};
+
+} // namespace MobileNetV3
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/include/utility.h
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/include/utility.h
+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+#include <chrono>
+#include <iomanip>
+#include <iostream>
+#include <ostream>
+#include <stdlib.h>
+#include <vector>
+
+#include <algorithm>
+#include <cstring>
+#include <fstream>
+#include <numeric>
+
+#include "opencv2/core.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/imgproc.hpp"
+
+namespace MobileNetV3 {
+
+class Utility {
+public:
+  static std::vector<std::string> ReadDict(const std::string &path);
+
+  //   template <class ForwardIterator>
+  //   inline static size_t argmax(ForwardIterator first, ForwardIterator last)
+  //   {
+  //     return std::distance(first, std::max_element(first, last));
+  //   }
+};
+
+} // namespace MobileNetV3
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/src/cls.cpp
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/src/cls.cpp
+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <chrono>
+#include <include/cls.h>
+
+namespace MobileNetV3 {
+
+void Classifier::LoadModel(const std::string &model_path,
+                           const std::string &params_path) {
+  paddle_infer::Config config;
+  config.SetModel(model_path, params_path);
+
+  if (this->use_gpu_) {
+    config.EnableUseGpu(this->gpu_mem_, this->gpu_id_);
+    if (this->use_tensorrt_) {
+      config.EnableTensorRtEngine(
+          1 << 20, 1, 3,
+          this->use_fp16_ ? paddle_infer::Config::Precision::kHalf
+                          : paddle_infer::Config::Precision::kFloat32,
+          false, false);
+    }
+  } else {
+    config.DisableGpu();
+    if (this->use_mkldnn_) {
+      config.EnableMKLDNN();
+      // cache 10 different shapes for mkldnn to avoid memory leak
+      config.SetMkldnnCacheCapacity(10);
+    }
+    config.SetCpuMathLibraryNumThreads(this->cpu_math_library_num_threads_);
+  }
+
+  config.SwitchUseFeedFetchOps(false);
+  // true for multiple input
+  config.SwitchSpecifyInputNames(true);
+
+  config.SwitchIrOptim(true);
+
+  config.EnableMemoryOptim();
+  config.DisableGlogInfo();
+
+  this->predictor_ = CreatePredictor(config);
+}
+
+double Classifier::Run(cv::Mat &img) {
+  cv::Mat srcimg;
+  cv::Mat resize_img;
+  img.copyTo(srcimg);
+
+  this->resize_op_.Run(img, resize_img, this->resize_short_size_);
+
+  this->crop_op_.Run(resize_img, this->crop_size_);
+
+  this->normalize_op_.Run(&resize_img, this->mean_, this->scale_,
+                          this->is_scale_);
+  std::vector<float> input(1 * 3 * resize_img.rows * resize_img.cols, 0.0f);
+  this->permute_op_.Run(&resize_img, input.data());
+
+  auto input_names = this->predictor_->GetInputNames();
+  auto input_t = this->predictor_->GetInputHandle(input_names[0]);
+  input_t->Reshape({1, 3, resize_img.rows, resize_img.cols});
+  auto start = std::chrono::system_clock::now();
+  input_t->CopyFromCpu(input.data());
+  this->predictor_->Run();
+
+  std::vector<float> out_data;
+  auto output_names = this->predictor_->GetOutputNames();
+  auto output_t = this->predictor_->GetOutputHandle(output_names[0]);
+  std::vector<int> output_shape = output_t->shape();
+  int out_num = std::accumulate(output_shape.begin(), output_shape.end(), 1,
+                                std::multiplies<int>());
+
+  out_data.resize(out_num);
+  output_t->CopyToCpu(out_data.data());
+  auto end = std::chrono::system_clock::now();
+  auto duration =
+      std::chrono::duration_cast<std::chrono::microseconds>(end - start);
+  double cost_time = double(duration.count()) *
+                     std::chrono::microseconds::period::num /
+                     std::chrono::microseconds::period::den;
+
+  int maxPosition =
+      max_element(out_data.begin(), out_data.end()) - out_data.begin();
+  std::cout << "result: " << std::endl;
+  std::cout << "\tclass id: " << maxPosition << std::endl;
+  std::cout << std::fixed << std::setprecision(10)
+            << "\tscore: " << double(out_data[maxPosition]) << std::endl;
+
+  return cost_time;
+}
+
+} // namespace MobileNetV3
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/src/cls_config.cpp
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/src/cls_config.cpp
+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <include/cls_config.h>
+
+namespace MobileNetV3 {
+
+std::vector<std::string> ClsConfig::split(const std::string &str,
+                                          const std::string &delim) {
+  std::vector<std::string> res;
+  if ("" == str)
+    return res;
+  char *strs = new char[str.length() + 1];
+  std::strcpy(strs, str.c_str());
+
+  char *d = new char[delim.length() + 1];
+  std::strcpy(d, delim.c_str());
+
+  char *p = std::strtok(strs, d);
+  while (p) {
+    std::string s = p;
+    res.push_back(s);
+    p = std::strtok(NULL, d);
+  }
+
+  return res;
+}
+
+std::map<std::string, std::string>
+ClsConfig::LoadConfig(const std::string &config_path) {
+  auto config = Utility::ReadDict(config_path);
+
+  std::map<std::string, std::string> dict;
+  for (int i = 0; i < config.size(); i++) {
+    // pass for empty line or comment
+    if (config[i].size() <= 1 || config[i][0] == '#') {
+      continue;
+    }
+    std::vector<std::string> res = split(config[i], " ");
+    dict[res[0]] = res[1];
+  }
+  return dict;
+}
+
+void ClsConfig::PrintConfigInfo() {
+  std::cout << "=======Paddle Class inference config======" << std::endl;
+  for (auto iter = config_map_.begin(); iter != config_map_.end(); iter++) {
+    std::cout << iter->first << " : " << iter->second << std::endl;
+  }
+  std::cout << "=======End of Paddle Class inference config======" << std::endl;
+}
+
+} // namespace MobileNetV3
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/src/main.cpp
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/src/main.cpp
+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "opencv2/core.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/imgproc.hpp"
+#include <chrono>
+#include <iomanip>
+#include <iostream>
+#include <opencv2/core/utils/filesystem.hpp>
+#include <ostream>
+#include <vector>
+
+#include <cstring>
+#include <fstream>
+#include <numeric>
+
+#include <include/cls.h>
+#include <include/cls_config.h>
+
+using namespace std;
+using namespace cv;
+using namespace MobileNetV3;
+
+int main(int argc, char **argv) {
+  if (argc < 3) {
+    std::cerr << "[ERROR] usage: " << argv[0]
+              << " configure_filepath image_path\n";
+    exit(1);
+  }
+
+  ClsConfig config(argv[1]);
+
+  config.PrintConfigInfo();
+
+  std::string path(argv[2]);
+
+  std::vector<std::string> img_files_list;
+  if (cv::utils::fs::isDirectory(path)) {
+    std::vector<cv::String> filenames;
+    cv::glob(path, filenames);
+    for (auto f : filenames) {
+      img_files_list.push_back(f);
+    }
+  } else {
+    img_files_list.push_back(path);
+  }
+
+  std::cout << "img_file_list length: " << img_files_list.size() << std::endl;
+
+  Classifier classifier(config.cls_model_path, config.cls_params_path,
+                        config.use_gpu, config.gpu_id, config.gpu_mem,
+                        config.cpu_math_library_num_threads, config.use_mkldnn,
+                        config.use_tensorrt, config.use_fp16,
+                        config.resize_short_size, config.crop_size);
+
+  double elapsed_time = 0.0;
+  int warmup_iter = img_files_list.size() > 5 ? 5 : 0;
+  for (int idx = 0; idx < img_files_list.size(); ++idx) {
+    std::string img_path = img_files_list[idx];
+    cv::Mat srcimg = cv::imread(img_path, cv::IMREAD_COLOR);
+    if (!srcimg.data) {
+      std::cerr << "[ERROR] image read failed! image path: " << img_path
+                << "\n";
+      exit(-1);
+    }
+
+    cv::cvtColor(srcimg, srcimg, cv::COLOR_BGR2RGB);
+
+    double run_time = classifier.Run(srcimg);
+    if (idx >= warmup_iter) {
+      elapsed_time += run_time;
+      std::cout << "Current image path: " << img_path << std::endl;
+      std::cout << "Current time cost: " << run_time << " s, "
+                << "average time cost in all: "
+                << elapsed_time / (idx + 1 - warmup_iter) << " s." << std::endl;
+    } else {
+      std::cout << "Current time cost: " << run_time << " s." << std::endl;
+    }
+  }
+
+  return 0;
+}
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/src/preprocess_op.cpp
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/src/preprocess_op.cpp
+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "opencv2/core.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/imgproc.hpp"
+#include "paddle_api.h"
+#include "paddle_inference_api.h"
+#include <chrono>
+#include <iomanip>
+#include <iostream>
+#include <ostream>
+#include <vector>
+
+#include <cstring>
+#include <fstream>
+#include <math.h>
+#include <numeric>
+
+#include <include/preprocess_op.h>
+
+namespace MobileNetV3 {
+
+void Permute::Run(const cv::Mat *im, float *data) {
+  int rh = im->rows;
+  int rw = im->cols;
+  int rc = im->channels();
+  for (int i = 0; i < rc; ++i) {
+    cv::extractChannel(*im, cv::Mat(rh, rw, CV_32FC1, data + i * rh * rw), i);
+  }
+}
+
+void Normalize::Run(cv::Mat *im, const std::vector<float> &mean,
+                    const std::vector<float> &scale, const bool is_scale) {
+  double e = 1.0;
+  if (is_scale) {
+    e /= 255.0;
+  }
+  (*im).convertTo(*im, CV_32FC3, e);
+  for (int h = 0; h < im->rows; h++) {
+    for (int w = 0; w < im->cols; w++) {
+      im->at<cv::Vec3f>(h, w)[0] =
+          (im->at<cv::Vec3f>(h, w)[0] - mean[0]) * scale[0];
+      im->at<cv::Vec3f>(h, w)[1] =
+          (im->at<cv::Vec3f>(h, w)[1] - mean[1]) * scale[1];
+      im->at<cv::Vec3f>(h, w)[2] =
+          (im->at<cv::Vec3f>(h, w)[2] - mean[2]) * scale[2];
+    }
+  }
+}
+
+void CenterCropImg::Run(cv::Mat &img, const int crop_size) {
+  int resize_w = img.cols;
+  int resize_h = img.rows;
+  int w_start = int((resize_w - crop_size) / 2);
+  int h_start = int((resize_h - crop_size) / 2);
+  cv::Rect rect(w_start, h_start, crop_size, crop_size);
+  img = img(rect);
+}
+
+void ResizeImg::Run(const cv::Mat &img, cv::Mat &resize_img,
+                    int resize_short_size) {
+  int w = img.cols;
+  int h = img.rows;
+
+  float ratio = 1.f;
+  if (h < w) {
+    ratio = float(resize_short_size) / float(h);
+  } else {
+    ratio = float(resize_short_size) / float(w);
+  }
+
+  int resize_h = round(float(h) * ratio);
+  int resize_w = round(float(w) * ratio);
+
+  cv::resize(img, resize_img, cv::Size(resize_w, resize_h));
+}
+
+} // namespace MobileNetV3
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/src/utility.cpp
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/src/utility.cpp
+// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <iostream>
+#include <ostream>
+#include <vector>
+
+#include <include/utility.h>
+
+namespace MobileNetV3 {
+
+std::vector<std::string> Utility::ReadDict(const std::string &path) {
+  std::ifstream in(path);
+  std::string line;
+  std::vector<std::string> m_vec;
+  if (in) {
+    while (getline(in, line)) {
+      m_vec.push_back(line);
+    }
+  } else {
+    std::cout << "no such label file: " << path << ", exit the program..."
+              << std::endl;
+    exit(1);
+  }
+  return m_vec;
+}
+
+} // namespace MobileNetV3
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/tools/build.sh
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/tools/build.sh
+OPENCV_DIR=../opencv-3.4.7/opencv3/
+LIB_DIR=../paddle_inference/
+CUDA_LIB_DIR=/usr/local/cuda/lib64
+CUDNN_LIB_DIR=/usr/lib64
+TENSORRT_DIR=/usr/local/TensorRT-7.2.3.4
+
+BUILD_DIR=build
+rm -rf ${BUILD_DIR}
+mkdir ${BUILD_DIR}
+cd ${BUILD_DIR}
+cmake .. \
+    -DPADDLE_LIB=${LIB_DIR} \
+    -DWITH_MKL=ON \
+    -DWITH_GPU=OFF \
+    -DWITH_STATIC_LIB=OFF \
+    -DUSE_TENSORRT=OFF \
+    -DOPENCV_DIR=${OPENCV_DIR} \
+    -DCUDNN_LIB=${CUDNN_LIB_DIR} \
+    -DCUDA_LIB=${CUDA_LIB_DIR} \
+
+make -j
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/tools/config.txt
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/tools/config.txt
+# model load config
+use_gpu  0
+gpu_id  0
+gpu_mem  4000
+cpu_math_library_num_threads  10
+use_mkldnn 1
+use_tensorrt 0
+use_fp16 0
+
+# cls config
+cls_model_path  ./mobilenet_v3_small_infer/inference.pdmodel
+cls_params_path ./mobilenet_v3_small_infer/inference.pdiparams
+resize_short_size 256
+crop_size 224
--- a/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/tools/run.sh
+++ b/tutorials/mobilenetv3_prod/Step6/deploy/inference_cpp/tools/run.sh
+./build/clas_system ./tools/config.txt ../../images/demo.jpg