Skip to content

P
PaddleX

PaddlePaddle / PaddleX

通知 138
Star 4
Fork 0
P
PaddleX
未验证 提交 a8d497a3 编写于 作者: J Jason 提交者： GitHub
浏览文件
操作

Merge pull request #60 from jiangjiajun/secure_cpp 

Secure cpp
上级 fe0a2f22 5917a0c9
隐藏空白更改
内联 并排
Showing with 101 addition and 28 deletion
deploy/cpp/CMakeLists.txt
浏览文件 @ a8d497a3
......@@ -5,12 +5,29 @@ option(WITH_MKL "Compile demo with MKL/OpenBlas support,defaultuseMKL."
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." OFF)
option(WITH_TENSORRT "Compile demo with TensorRT." OFF)
option(WITH_ENCRYPTION "Compile demo with encryption tool." OFF)
SET(TENSORRT_DIR "" CACHE PATH "Compile demo with TensorRT")
SET(TENSORRT_DIR "" CACHE PATH "Location of libraries")
SET(PADDLE_DIR "" CACHE PATH "Location of libraries")
SET(OPENCV_DIR "" CACHE PATH "Location of libraries")
SET(ENCRYPTION_DIR"" CACHE PATH "Location of libraries")
SET(CUDA_LIB "" CACHE PATH "Location of libraries")
if (NOT WIN32)
set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/demo)
else()
set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/paddlex_inference)
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/paddlex_inference)
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/paddlex_inference)
endif()
if (NOT WIN32)
SET(YAML_BUILD_TYPE ON CACHE BOOL "yaml build shared library.")
else()
SET(YAML_BUILD_TYPE OFF CACHE BOOL "yaml build shared library.")
endif()
include(cmake/yaml-cpp.cmake)
include_directories("${CMAKE_SOURCE_DIR}/")
......@@ -27,6 +44,11 @@ macro(safe_set_static_flag)
endforeach(flag_var)
endmacro()
if (WITH_ENCRYPTION)
add_definitions( -DWITH_ENCRYPTION=${WITH_ENCRYPTION})
endif()
if (WITH_MKL)
ADD_DEFINITIONS(-DUSE_MKL)
endif()
......@@ -183,6 +205,7 @@ else()
set(DEPS ${DEPS}
${MATH_LIB} ${MKLDNN_LIB}
glog gflags_static libprotobuf zlibstatic xxhash libyaml-cppmt)
set(DEPS ${DEPS} libcmt shlwapi)
if (EXISTS "${PADDLE_DIR}/third_party/install/snappy/lib")
set(DEPS ${DEPS} snappy)
......@@ -207,21 +230,35 @@ if(WITH_GPU)
endif()
endif()
if(WITH_ENCRYPTION)
if(NOT WIN32)
include_directories("${ENCRYPTION_DIR}/include")
link_directories("${ENCRYPTION_DIR}/lib")
set(DEPS ${DEPS} ${ENCRYPTION_DIR}/lib/libpmodel-decrypt${CMAKE_SHARED_LIBRARY_SUFFIX})
else()
message(FATAL_ERROR "Encryption Tool don't support WINDOWS")
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})
add_executable(classifier src/classifier.cpp src/transforms.cpp src/paddlex.cpp)
add_library(paddlex_inference SHARED src/visualize src/transforms.cpp src/paddlex.cpp)
ADD_DEPENDENCIES(paddlex_inference ext-yaml-cpp)
target_link_libraries(paddlex_inference ${DEPS})
add_executable(classifier demo/classifier.cpp src/transforms.cpp src/paddlex.cpp)
ADD_DEPENDENCIES(classifier ext-yaml-cpp)
target_link_libraries(classifier ${DEPS})
add_executable(detector src/detector.cpp src/transforms.cpp src/paddlex.cpp src/visualize.cpp)
add_executable(detector demo/detector.cpp src/transforms.cpp src/paddlex.cpp src/visualize.cpp)
ADD_DEPENDENCIES(detector ext-yaml-cpp)
target_link_libraries(detector ${DEPS})
add_executable(segmenter src/segmenter.cpp src/transforms.cpp src/paddlex.cpp src/visualize.cpp)
add_executable(segmenter demo/segmenter.cpp src/transforms.cpp src/paddlex.cpp src/visualize.cpp)
ADD_DEPENDENCIES(segmenter ext-yaml-cpp)
target_link_libraries(segmenter ${DEPS})
......@@ -252,3 +289,14 @@ if (WIN32 AND WITH_MKL)
)
endif()
file(COPY "${CMAKE_SOURCE_DIR}/include/paddlex/visualize.h"
DESTINATION "${CMAKE_BINARY_DIR}/include/" )
file(COPY "${CMAKE_SOURCE_DIR}/include/paddlex/config_parser.h"
DESTINATION "${CMAKE_BINARY_DIR}/include/" )
file(COPY "${CMAKE_SOURCE_DIR}/include/paddlex/transforms.h"
DESTINATION "${CMAKE_BINARY_DIR}/include/" )
file(COPY "${CMAKE_SOURCE_DIR}/include/paddlex/results.h"
DESTINATION "${CMAKE_BINARY_DIR}/include/" )
file(COPY "${CMAKE_SOURCE_DIR}/include/paddlex/paddlex.h"
DESTINATION "${CMAKE_BINARY_DIR}/include/" )
deploy/cpp/cmake/yaml-cpp.cmake
浏览文件 @ a8d497a3
......@@ -14,7 +14,7 @@ ExternalProject_Add(
-DYAML_CPP_INSTALL=OFF
-DYAML_CPP_BUILD_CONTRIB=OFF
-DMSVC_SHARED_RT=OFF
-DBUILD_SHARED_LIBS=OFF
-DBUILD_SHARED_LIBS=${YAML_BUILD_TYPE}
-DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE}
-DCMAKE_CXX_FLAGS=${CMAKE_CXX_FLAGS}
-DCMAKE_CXX_FLAGS_DEBUG=${CMAKE_CXX_FLAGS_DEBUG}
......
deploy/cpp/src/classifier.cpp → deploy/cpp/demo/classifier.cpp
浏览文件 @ a8d497a3
......@@ -25,6 +25,7 @@ DEFINE_string(model_dir, "", "Path of inference model");
DEFINE_bool(use_gpu, false, "Infering with GPU or CPU");
DEFINE_bool(use_trt, false, "Infering with TensorRT");
DEFINE_int32(gpu_id, 0, "GPU card id");
DEFINE_string(key, "", "key of encryption");
DEFINE_string(image, "", "Path of test image file");
DEFINE_string(image_list, "", "Path of test image list file");
......@@ -43,7 +44,7 @@ int main(int argc, char** argv) {
// 加载模型
PaddleX::Model model;
model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id);
model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id, FLAGS_key);
// 进行预测
if (FLAGS_image_list != "") {
......
deploy/cpp/src/detector.cpp → deploy/cpp/demo/detector.cpp
浏览文件 @ a8d497a3
......@@ -26,6 +26,7 @@ DEFINE_string(model_dir, "", "Path of inference model");
DEFINE_bool(use_gpu, false, "Infering with GPU or CPU");
DEFINE_bool(use_trt, false, "Infering with TensorRT");
DEFINE_int32(gpu_id, 0, "GPU card id");
DEFINE_string(key, "", "key of encryption");
DEFINE_string(image, "", "Path of test image file");
DEFINE_string(image_list, "", "Path of test image list file");
DEFINE_string(save_dir, "output", "Path to save visualized image");
......@@ -45,7 +46,7 @@ int main(int argc, char** argv) {
// 加载模型
PaddleX::Model model;
model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id);
model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id, FLAGS_key);
auto colormap = PaddleX::GenerateColorMap(model.labels.size());
std::string save_dir = "output";
......@@ -74,7 +75,7 @@ int main(int argc, char** argv) {
// 可视化
cv::Mat vis_img =
PaddleX::VisualizeDet(im, result, model.labels, colormap, 0.5);
PaddleX::Visualize(im, result, model.labels, colormap, 0.5);
std::string save_path =
PaddleX::generate_save_path(FLAGS_save_dir, image_path);
cv::imwrite(save_path, vis_img);
......@@ -97,7 +98,7 @@ int main(int argc, char** argv) {
// 可视化
cv::Mat vis_img =
PaddleX::VisualizeDet(im, result, model.labels, colormap, 0.5);
PaddleX::Visualize(im, result, model.labels, colormap, 0.5);
std::string save_path =
PaddleX::generate_save_path(FLAGS_save_dir, FLAGS_image);
cv::imwrite(save_path, vis_img);
......
deploy/cpp/src/segmenter.cpp → deploy/cpp/demo/segmenter.cpp
浏览文件 @ a8d497a3
......@@ -26,6 +26,7 @@ DEFINE_string(model_dir, "", "Path of inference model");
DEFINE_bool(use_gpu, false, "Infering with GPU or CPU");
DEFINE_bool(use_trt, false, "Infering with TensorRT");
DEFINE_int32(gpu_id, 0, "GPU card id");
DEFINE_string(key, "", "key of encryption");
DEFINE_string(image, "", "Path of test image file");
DEFINE_string(image_list, "", "Path of test image list file");
DEFINE_string(save_dir, "output", "Path to save visualized image");
......@@ -45,7 +46,7 @@ int main(int argc, char** argv) {
// 加载模型
PaddleX::Model model;
model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id);
model.Init(FLAGS_model_dir, FLAGS_use_gpu, FLAGS_use_trt, FLAGS_gpu_id, FLAGS_key);
auto colormap = PaddleX::GenerateColorMap(model.labels.size());
// 进行预测
......@@ -62,7 +63,7 @@ int main(int argc, char** argv) {
model.predict(im, &result);
// 可视化
cv::Mat vis_img =
PaddleX::VisualizeSeg(im, result, model.labels, colormap);
PaddleX::Visualize(im, result, model.labels, colormap);
std::string save_path =
PaddleX::generate_save_path(FLAGS_save_dir, image_path);
cv::imwrite(save_path, vis_img);
......@@ -74,7 +75,7 @@ int main(int argc, char** argv) {
cv::Mat im = cv::imread(FLAGS_image, 1);
model.predict(im, &result);
// 可视化
cv::Mat vis_img = PaddleX::VisualizeSeg(im, result, model.labels, colormap);
cv::Mat vis_img = PaddleX::Visualize(im, result, model.labels, colormap);
std::string save_path =
PaddleX::generate_save_path(FLAGS_save_dir, FLAGS_image);
cv::imwrite(save_path, vis_img);
......
deploy/cpp/include/paddlex/paddlex.h
浏览文件 @ a8d497a3
......@@ -28,9 +28,14 @@
#include "paddle_inference_api.h" // NOLINT
#include "include/paddlex/config_parser.h"
#include "include/paddlex/results.h"
#include "include/paddlex/transforms.h"
#include "config_parser.h"
#include "results.h"
#include "transforms.h"
#ifdef WITH_ENCRYPTION
#include "paddle_model_decrypt.h"
#include "model_code.h"
#endif
namespace PaddleX {
......@@ -39,14 +44,16 @@ class Model {
void Init(const std::string& model_dir,
bool use_gpu = false,
bool use_trt = false,
int gpu_id = 0) {
create_predictor(model_dir, use_gpu, use_trt, gpu_id);
int gpu_id = 0,
std::string key = "") {
create_predictor(model_dir, use_gpu, use_trt, gpu_id, key);
}
void create_predictor(const std::string& model_dir,
bool use_gpu = false,
bool use_trt = false,
int gpu_id = 0);
int gpu_id = 0,
std::string key = "");
bool load_config(const std::string& model_dir);
......
deploy/cpp/include/paddlex/visualize.h
浏览文件 @ a8d497a3
......@@ -46,13 +46,13 @@ namespace PaddleX {
// Generate visualization colormap for each class
std::vector<int> GenerateColorMap(int num_class);
cv::Mat VisualizeDet(const cv::Mat& img,
cv::Mat Visualize(const cv::Mat& img,
const DetResult& results,
const std::map<int, std::string>& labels,
const std::vector<int>& colormap,
float threshold = 0.5);
cv::Mat VisualizeSeg(const cv::Mat& img,
cv::Mat Visualize(const cv::Mat& img,
const SegResult& result,
const std::map<int, std::string>& labels,
const std::vector<int>& colormap);
......
deploy/cpp/scripts/build.sh
浏览文件 @ a8d497a3
......@@ -16,6 +16,11 @@ CUDA_LIB=/path/to/cuda/lib/
# CUDNN 的 lib 路径
CUDNN_LIB=/path/to/cudnn/lib/
# 是否加载加密后的模型
WITH_ENCRYPTION=OFF
# 加密工具的路径
ENCRYPTION_DIR=/path/to/encryption_tool/
# OPENCV 路径, 如果使用自带预编译版本可不修改
OPENCV_DIR=$(pwd)/deps/opencv3gcc4.8/
sh $(pwd)/scripts/bootstrap.sh
......@@ -28,10 +33,12 @@ cmake .. \
-DWITH_GPU=${WITH_GPU} \
-DWITH_MKL=${WITH_MKL} \
-DWITH_TENSORRT=${WITH_TENSORRT} \
-DWITH_ENCRYPTION=${WITH_ENCRYPTION} \
-DTENSORRT_DIR=${TENSORRT_DIR} \
-DPADDLE_DIR=${PADDLE_DIR} \
-DWITH_STATIC_LIB=${WITH_STATIC_LIB} \
-DCUDA_LIB=${CUDA_LIB} \
-DCUDNN_LIB=${CUDNN_LIB} \
-DENCRYPTION_DIR=${ENCRYPTION_DIR} \
-DOPENCV_DIR=${OPENCV_DIR}
make
deploy/cpp/src/paddlex.cpp
浏览文件 @ a8d497a3
......@@ -19,7 +19,8 @@ namespace PaddleX {
void Model::create_predictor(const std::string& model_dir,
bool use_gpu,
bool use_trt,
int gpu_id) {
int gpu_id,
std::string key) {
// 读取配置文件
if (!load_config(model_dir)) {
std::cerr << "Parse file 'model.yml' failed!" << std::endl;
......@@ -28,7 +29,14 @@ void Model::create_predictor(const std::string& model_dir,
paddle::AnalysisConfig config;
std::string model_file = model_dir + OS_PATH_SEP + "__model__";
std::string params_file = model_dir + OS_PATH_SEP + "__params__";
config.SetModel(model_file, params_file);
#ifdef WITH_ENCRYPTION
if (key != ""){
paddle_security_load_model(&config, key.c_str(), model_file.c_str(), params_file.c_str());
}
#endif
if (key == ""){
config.SetModel(model_file, params_file);
}
if (use_gpu) {
config.EnableUseGpu(100, gpu_id);
} else {
......
deploy/cpp/src/visualize.cpp
浏览文件 @ a8d497a3
......@@ -31,7 +31,7 @@ std::vector<int> GenerateColorMap(int num_class) {
return colormap;
}
cv::Mat VisualizeDet(const cv::Mat& img,
cv::Mat Visualize(const cv::Mat& img,
const DetResult& result,
const std::map<int, std::string>& labels,
const std::vector<int>& colormap,
......@@ -105,7 +105,7 @@ cv::Mat VisualizeDet(const cv::Mat& img,
return vis_img;
}
cv::Mat VisualizeSeg(const cv::Mat& img,
cv::Mat Visualize(const cv::Mat& img,
const SegResult& result,
const std::map<int, std::string>& labels,
const std::vector<int>& colormap) {
......
docs/tutorials/deploy/deploy_cpp_linux.md
浏览文件 @ a8d497a3
......@@ -95,7 +95,7 @@ make
```
### Step5: 预测及可视化
编译成功后，预测demo的可执行程序分别为`build/detector`，`build/classifer`，`build/segmenter`，用户可根据自己的模型类型选择，其主要命令参数说明如下：
编译成功后，预测demo的可执行程序分别为`build/demo/detector`，`build/demo/classifer`，`build/demo/segmenter`，用户可根据自己的模型类型选择，其主要命令参数说明如下：
| 参数 | 说明 |
| ---- | ---- |
......@@ -116,7 +116,7 @@ make
不使用`GPU`测试图片 `/path/to/xiaoduxiong.jpeg`
```shell
./build/detector --model_dir=/path/to/inference_model --image=/path/to/xiaoduxiong.jpeg --save_dir=output
./build/demo/detector --model_dir=/path/to/inference_model --image=/path/to/xiaoduxiong.jpeg --save_dir=output
```
图片文件`可视化预测结果`会保存在`save_dir`参数设置的目录下。
......@@ -131,6 +131,6 @@ make
/path/to/images/xiaoduxiongn.jpeg
```
```shell
./build/detector --model_dir=/path/to/models/inference_model --image_list=/root/projects/images_list.txt --use_gpu=1 --save_dir=output
./build/demo/detector --model_dir=/path/to/models/inference_model --image_list=/root/projects/images_list.txt --use_gpu=1 --save_dir=output
```
图片文件`可视化预测结果`会保存在`save_dir`参数设置的目录下。
docs/tutorials/deploy/deploy_cpp_win_vs2019.md
浏览文件 @ a8d497a3
......@@ -106,7 +106,7 @@ d:
cd D:\projects\PaddleX\deploy\cpp\out\build\x64-Release
```
编译成功后，预测demo的入口程序为`detector`，`classifer`，`segmenter`，用户可根据自己的模型类型选择，其主要命令参数说明如下：
编译成功后，预测demo的入口程序为`demo\detector`，`demo\classifer`，`demo\segmenter`，用户可根据自己的模型类型选择，其主要命令参数说明如下：
| 参数 | 说明 |
| ---- | ---- |
......
Markdown is supported
0% 或 .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑！
想要评论请 注册 或