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Commit a3e8d27f authored by liucong's avatar liucong
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简化代码

parent 3af6f22a
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Showing with 95 additions and 205 deletions
CMakeLists.txt
View file @ a3e8d27f
......@@ -12,7 +12,6 @@ set(CMAKE_BUILD_TYPE release)
# 添加头文件路径
set(INCLUDE_PATH ${CMAKE_CURRENT_SOURCE_DIR}/Src/
${CMAKE_CURRENT_SOURCE_DIR}/Src/Utility/
${CMAKE_CURRENT_SOURCE_DIR}/Src/Resnet50/
$ENV{DTKROOT}/include/
${CMAKE_CURRENT_SOURCE_DIR}/depend/include/)
include_directories(${INCLUDE_PATH})
......@@ -37,7 +36,7 @@ link_libraries(${LIBRARY})
# 添加源文件
set(SOURCE_FILES ${CMAKE_CURRENT_SOURCE_DIR}/Src/main.cpp
${CMAKE_CURRENT_SOURCE_DIR}/Src/Resnet50/resnet50.cpp
${CMAKE_CURRENT_SOURCE_DIR}/Src/Classifier.cpp
${CMAKE_CURRENT_SOURCE_DIR}/Src/Utility/CommonUtility.cpp
${CMAKE_CURRENT_SOURCE_DIR}/Src/Utility/Filesystem.cpp)
......
Doc/Tutorial_Cpp/ResNet50.md → Doc/Tutorial_Cpp.md
View file @ a3e8d27f
......@@ -58,7 +58,7 @@ ErrorCode Classifier::Classify(const std::vector<cv::Mat> &srcImages,std::vector
// 预处理
// 输入数据
// 创建输入数据
std::unordered_map<std::string, migraphx::argument> inputData;
inputData[inputName]= migraphx::argument{inputShape, (float*)inputBlob.data};
......
Doc/Tutorial_Python/ResNet50.md → Doc/Tutorial_Python.md
View file @ a3e8d27f
......@@ -48,11 +48,11 @@ if __name__ == '__main__':
...
# 预处理
pathOfImage ="../Resource/Images/mnist_9.jpg"
pathOfImage ="../Resource/Images/ImageNet_01.jpg"
image = Preprocessing(pathOfImage)
# 推理
results = model.run({inputName: migraphx.argument(image)}) # 推理结果，list类型
results = model.run({inputName: image}) # 推理结果，list类型
# 获取输出节点属性
result=results[0] # 获取第一个输出节点的数据,migraphx.argument类型
......
README.md
View file @ a3e8d27f
......@@ -8,7 +8,7 @@ ResNet50模型包含了49个卷积层、一个全连接层。
## Python版本推理
下面介绍如何运行python代码示例，具体推理代码解析，在Doc/Tutorial_Python目录中有详细说明。
下面介绍如何运行python代码示例，具体推理代码解析，在Doc/Tutorial_Python.md中有详细说明。
### 构建安装
......@@ -53,7 +53,7 @@ python Classifier.py
## C++版本推理
下面介绍如何运行C++代码示例，具体推理代码解析，在Doc/Tutorial_Cpp目录中有详细说明。
下面介绍如何运行C++代码示例，具体推理代码解析，在Doc/Tutorial_Cpp.md目录中有详细说明。
参考Python版本推理中的构建安装，在光源中拉取推理的docker镜像。
......
Src/Resnet50/resnet50.cpp → Src/Classifier.cpp
View file @ a3e8d27f
#include <resnet50.h>
#include <Classifier.h>
#include <migraphx/onnx.hpp>
#include <migraphx/gpu/target.hpp>
#include <migraphx/quantization.hpp>
#include <opencv2/dnn.hpp>
#include <CommonUtility.h>
#include <Filesystem.h>
#include <SimpleLog.h>
......@@ -22,13 +22,13 @@ Classifier::~Classifier()
ErrorCode Classifier::Initialize(InitializationParameterOfClassifier initializationParameterOfClassifier)
{
// 读取配置文件
std::string configFilePath=CONFIG_FILE;
std::string configFilePath=initializationParameterOfClassifier.configFilePath;
if(Exists(configFilePath)==false)
{
LOG_ERROR(stdout, "no configuration file!\n");
return CONFIG_FILE_NOT_EXIST;
}
if(!configurationFile.open(configFilePath, FileStorage::READ))
if(!configurationFile.open(configFilePath, cv::FileStorage::READ))
{
LOG_ERROR(stdout, "fail to open configuration file\n");
return FAIL_TO_OPEN_CONFIG_FILE;
......@@ -36,7 +36,7 @@ ErrorCode Classifier::Initialize(InitializationParameterOfClassifier initializat
LOG_INFO(stdout, "succeed to open configuration file\n");
// 获取配置文件参数
FileNode netNode = configurationFile["Classifier"];
cv::FileNode netNode = configurationFile["Classifier"];
std::string modelPath=(std::string)netNode["ModelPath"];
scale=(float)netNode["Scale"];
meanValue.val[0]=(float)netNode["MeanValue1"];
......@@ -50,11 +50,11 @@ ErrorCode Classifier::Initialize(InitializationParameterOfClassifier initializat
// 加载模型
if(Exists(modelPath)==false)
{
LOG_ERROR(logFile,"%s not exist!\n",modelPath.c_str());
LOG_ERROR(stdout,"%s not exist!\n",modelPath.c_str());
return MODEL_NOT_EXIST;
}
net = migraphx::parse_onnx(modelPath);
LOG_INFO(logFile,"succeed to load model: %s\n",GetFileName(modelPath).c_str());
LOG_INFO(stdout,"succeed to load model: %s\n",GetFileName(modelPath).c_str());
// 获取模型输入属性
std::unordered_map<std::string, migraphx::shape> inputMap=net.get_parameter_shapes();
......@@ -94,32 +94,33 @@ ErrorCode Classifier::Initialize(InitializationParameterOfClassifier initializat
// INT8量化
migraphx::quantize_int8(net, gpuTarget, calibrationData);
}
if(useFP16)
else if(useFP16)
{
migraphx::quantize_fp16(net);
}
// 编译模型
migraphx::compile_options options;
options.device_id=0; // 设置GPU设备，默认为0号设备
options.offload_copy=true;
options.device_id=0; // 设置GPU设备，默认为0号设备
options.offload_copy=true;
net.compile(gpuTarget,options);
LOG_INFO(logFile,"succeed to compile model: %s\n",GetFileName(modelPath).c_str());
LOG_INFO(stdout,"succeed to compile model: %s\n",GetFileName(modelPath).c_str());
// warm up
std::unordered_map<std::string, migraphx::argument> inputData;
inputData[inputName]=migraphx::argument{inputShape};
net.eval(inputData);
// log
LOG_INFO(logFile,"InputSize:%dx%d\n",inputSize.width,inputSize.height);
LOG_INFO(logFile,"InputName:%s\n",inputName.c_str());
LOG_INFO(logFile,"Scale:%.6f\n",scale);
LOG_INFO(logFile,"Mean:%.2f,%.2f,%.2f\n",meanValue.val[0],meanValue.val[1],meanValue.val[2]);
LOG_INFO(logFile,"SwapRB:%d\n",(int)swapRB);
LOG_INFO(logFile,"Crop:%d\n",(int)crop);
LOG_INFO(logFile,"UseInt8:%d\n",(int)useInt8);
LOG_INFO(logFile,"UseFP16:%d\n",(int)useFP16);
LOG_INFO(stdout,"InputSize:%dx%d\n",inputSize.width,inputSize.height);
LOG_INFO(stdout,"InputName:%s\n",inputName.c_str());
LOG_INFO(stdout,"Scale:%.6f\n",scale);
LOG_INFO(stdout,"Mean:%.2f,%.2f,%.2f\n",meanValue.val[0],meanValue.val[1],meanValue.val[2]);
LOG_INFO(stdout,"SwapRB:%d\n",(int)swapRB);
LOG_INFO(stdout,"Crop:%d\n",(int)crop);
LOG_INFO(stdout,"UseInt8:%d\n",(int)useInt8);
LOG_INFO(stdout,"UseFP16:%d\n",(int)useFP16);
return SUCCESS;
}
......@@ -128,11 +129,11 @@ ErrorCode Classifier::Classify(const std::vector<cv::Mat> &srcImages,std::vector
{
if(srcImages.size()==0||srcImages[0].empty()||srcImages[0].depth()!=CV_8U)
{
LOG_ERROR(logFile, "image error!\n");
LOG_ERROR(stdout, "image error!\n");
return IMAGE_ERROR;
}
// 预处理并转换为NCHW
// 数据预处理并转换为NCHW
cv::Mat inputBlob;
cv::dnn::blobFromImages(srcImages,
inputBlob,
......@@ -142,7 +143,7 @@ ErrorCode Classifier::Classify(const std::vector<cv::Mat> &srcImages,std::vector
swapRB,
false);
// 输入数据
// 创建输入数据
std::unordered_map<std::string, migraphx::argument> inputData;
inputData[inputName]= migraphx::argument{inputShape, (float*)inputBlob.data};
......@@ -150,11 +151,11 @@ ErrorCode Classifier::Classify(const std::vector<cv::Mat> &srcImages,std::vector
std::vector<migraphx::argument> results = net.eval(inputData);
// 获取输出节点的属性
migraphx::argument result = results[0]; // 获取第一个输出节点的数据
migraphx::shape outputShape=result.get_shape(); // 输出节点的shape
std::vector<std::size_t> outputSize=outputShape.lens(); // 每一维大小，维度顺序为(N,C,H,W)
int numberOfOutput=outputShape.elements(); // 输出节点元素的个数
float *logits=(float *)result.data(); // 输出节点数据指针
migraphx::argument result = results[0]; // 获取第一个输出节点的数据
migraphx::shape outputShape=result.get_shape(); // 输出节点的shape
std::vector<std::size_t> outputSize=outputShape.lens();// 每一维大小，维度顺序为(N,C,H,W)
int numberOfOutput=outputShape.elements();// 输出节点元素的个数
float *logits=(float *)result.data();// 输出节点数据指针
// 获取每张图像的预测结果
int numberOfClasses=numberOfOutput/srcImages.size();
......@@ -162,7 +163,6 @@ ErrorCode Classifier::Classify(const std::vector<cv::Mat> &srcImages,std::vector
{
int startIndex=numberOfClasses*i;
// 获取每幅图像对应的输出
std::vector<float> logit;
for(int j=0;j<numberOfClasses;++j)
{
......
Src/Resnet50/resnet50.h → Src/Classifier.h
View file @ a3e8d27f
#ifndef __CLASSIFIER_H__
#define __CLASSIFIER_H__
#include <string>
#include <migraphx/program.hpp>
#include <opencv2/opencv.hpp>
#include <CommonDefinition.h>
namespace migraphxSamples
......@@ -22,7 +21,6 @@ public:
private:
cv::FileStorage configurationFile;
FILE *logFile;
migraphx::program net;
cv::Size inputSize;
......@@ -34,7 +32,8 @@ private:
bool swapRB;
bool crop;
bool useInt8;
bool useFP16;
bool useFP16;
};
......
Src/Utility/CommonDefinition.h
View file @ a3e8d27f
// 常用数据类型和宏定义
// 常用定义
#ifndef __COMMON_DEFINITION_H__
#define __COMMON_DEFINITION_H__
#include <string>
#include <opencv2/opencv.hpp>
using namespace std;
using namespace cv;
namespace migraphxSamples
{
......@@ -21,20 +17,7 @@ namespace migraphxSamples
#define CONFIG_FILE "../Resource/Configuration.xml"
typedef struct __Time
{
string year;
string month;
string day;
string hour;
string minute;
string second;
string millisecond; // ms
string microsecond; // us
string weekDay;
}_Time;
typedef enum _ErrorCode
typedef enum _ErrorCode
{
SUCCESS=0, // 0
MODEL_NOT_EXIST, // 模型不存在
......@@ -44,7 +27,7 @@ typedef enum _ErrorCode
IMAGE_ERROR, // 图像错误
}ErrorCode;
typedef struct _ResultOfPrediction
typedef struct _ResultOfPrediction
{
float confidence;
int label;
......@@ -52,24 +35,22 @@ typedef struct _ResultOfPrediction
}ResultOfPrediction;
typedef struct _ResultOfDetection
typedef struct _ResultOfDetection
{
Rect boundingBox;
cv::Rect boundingBox;
float confidence;
int classID;
string className;
std::string className;
bool exist;
_ResultOfDetection():confidence(0.0f),classID(0),exist(true){}
}ResultOfDetection;
typedef struct _InitializationParameterOfClassifier
typedef struct _InitializationParameterOfClassifier
{
std::string parentPath;
std::string configFilePath;
cv::Size inputSize;
std::string logName;
}InitializationParameterOfClassifier;
}
......
Src/Utility/CommonUtility.cpp
View file @ a3e8d27f
#include <CommonUtility.h>
#include <assert.h>
#include <ctype.h>
#include <time.h>
#include <stdlib.h>
#include <algorithm>
#include <sstream>
#include <vector>
#ifdef _WIN32
#include <io.h>
#include <direct.h>
#include <Windows.h>
#else
#include <unistd.h>
#include <dirent.h>
#include <sys/stat.h>
#include <sys/time.h>
#endif
#include <SimpleLog.h>
namespace migraphxSamples
{
_Time GetCurrentTime3()
{
_Time currentTime;
#if (defined WIN32 || defined _WIN32)
SYSTEMTIME systemTime;
GetLocalTime(&systemTime);
char temp[8] = { 0 };
sprintf(temp, "%04d", systemTime.wYear);
currentTime.year=string(temp);
sprintf(temp, "%02d", systemTime.wMonth);
currentTime.month=string(temp);
sprintf(temp, "%02d", systemTime.wDay);
currentTime.day=string(temp);
sprintf(temp, "%02d", systemTime.wHour);
currentTime.hour=string(temp);
sprintf(temp, "%02d", systemTime.wMinute);
currentTime.minute=string(temp);
sprintf(temp, "%02d", systemTime.wSecond);
currentTime.second=string(temp);
sprintf(temp, "%03d", systemTime.wMilliseconds);
currentTime.millisecond=string(temp);
sprintf(temp, "%d", systemTime.wDayOfWeek);
currentTime.weekDay=string(temp);
#else
struct timeval tv;
struct tm *p;
gettimeofday(&tv, NULL);
p = localtime(&tv.tv_sec);
char temp[8]={0};
sprintf(temp,"%04d",1900+p->tm_year);
currentTime.year=string(temp);
sprintf(temp,"%02d",1+p->tm_mon);
currentTime.month=string(temp);
sprintf(temp,"%02d",p->tm_mday);
currentTime.day=string(temp);
sprintf(temp,"%02d",p->tm_hour);
currentTime.hour=string(temp);
sprintf(temp,"%02d",p->tm_min);
currentTime.minute=string(temp);
sprintf(temp,"%02d",p->tm_sec);
currentTime.second=string(temp);
sprintf(temp,"%03d",tv.tv_usec/1000);
currentTime.millisecond = string(temp);
sprintf(temp, "%03d", tv.tv_usec % 1000);
currentTime.microsecond = string(temp);
sprintf(temp, "%d", p->tm_wday);
currentTime.weekDay = string(temp);
#endif
return currentTime;
}
std::vector<std::string> SplitString(std::string str, std::string separator)
{
std::string::size_type pos;
std::vector<std::string> result;
str+=separator;//扩展字符串以方便操作
int size=str.size();
for(int i=0; i<size; i++)
{
pos=str.find(separator,i);
if(pos<size)
{
std::string s=str.substr(i,pos-i);
result.push_back(s);
i=pos+separator.size()-1;
}
}
return result;
}
bool CompareConfidence(const ResultOfDetection &L,const ResultOfDetection &R)
{
return L.confidence > R.confidence;
......@@ -109,7 +13,7 @@ bool CompareArea(const ResultOfDetection &L,const ResultOfDetection &R)
return L.boundingBox.area() > R.boundingBox.area();
}
void NMS(vector<ResultOfDetection> &detections, float IOUThreshold)
void NMS(std::vector<ResultOfDetection> &detections, float IOUThreshold)
{
// sort
std::sort(detections.begin(), detections.end(), CompareConfidence);
......
Src/Utility/CommonUtility.h
View file @ a3e8d27f
......@@ -3,23 +3,16 @@
#ifndef __COMMON_UTILITY_H__
#define __COMMON_UTILITY_H__
#include <mutex>
#include <string>
#include <vector>
#include <CommonDefinition.h>
using namespace std;
namespace migraphxSamples
{
// 分割字符串
std::vector<std::string> SplitString(std::string str,std::string separator);
// 排序规则: 按照置信度或者按照面积排序
bool CompareConfidence(const ResultOfDetection &L,const ResultOfDetection &R);
bool CompareArea(const ResultOfDetection &L,const ResultOfDetection &R);
// 非极大抑制
void NMS(std::vector<ResultOfDetection> &detections, float IOUThreshold);
}
......
Src/Utility/Filesystem.cpp
View file @ a3e8d27f
......@@ -11,12 +11,7 @@
#include <unistd.h>
#include <dirent.h>
#endif
#include <CommonUtility.h>
#include <opencv2/opencv.hpp>
#include <SimpleLog.h>
using namespace cv;
// 路径分隔符(Linux:‘/’,Windows:’\\’)
#ifdef _WIN32
#define PATH_SEPARATOR '\\'
......@@ -24,9 +19,31 @@ using namespace cv;
#define PATH_SEPARATOR '/'
#endif
using namespace std;
namespace migraphxSamples
{
static std::vector<std::string> SplitString(std::string str, std::string separator)
{
std::string::size_type pos;
std::vector<std::string> result;
str+=separator;//扩展字符串以方便操作
int size=str.size();
for(int i=0; i<size; i++)
{
pos=str.find(separator,i);
if(pos<size)
{
std::string s=str.substr(i,pos-i);
result.push_back(s);
i=pos+separator.size()-1;
}
}
return result;
}
#if defined _WIN32 || defined WINCE
const char dir_separators[] = "/\\";
......@@ -293,7 +310,7 @@ namespace migraphxSamples
}
else
{
LOG_INFO(stdout, "could not open directory: %s", directory.c_str());
printf("could not open directory: %s", directory.c_str());
}
}
......@@ -390,7 +407,7 @@ namespace migraphxSamples
#endif
if (!result)
{
LOG_INFO(stdout, "can't remove directory: %s\n", path.c_str());
printf("can't remove directory: %s\n", path.c_str());
}
}
else
......@@ -402,7 +419,7 @@ namespace migraphxSamples
#endif
if (!result)
{
LOG_INFO(stdout, "can't remove file: %s\n", path.c_str());
printf("can't remove file: %s\n", path.c_str());
}
}
}
......@@ -438,7 +455,7 @@ namespace migraphxSamples
{
RemoveAll(path);
++numberOfFiles;
LOG_INFO(stdout, "%s deleted! number of deleted files:%d\n", path.c_str(), numberOfFiles);
printf("%s deleted! number of deleted files:%d\n", path.c_str(), numberOfFiles);
}
}
......@@ -452,7 +469,7 @@ namespace migraphxSamples
}
else
{
LOG_INFO(stdout, "could not open directory: %s", directory.c_str());
printf("could not open directory: %s", directory.c_str());
}
// ����RemoveAllɾ��Ŀ¼
......@@ -592,17 +609,17 @@ namespace migraphxSamples
if(!srcFile.is_open())
{
LOG_ERROR(stdout,"can not open %s\n",srcPath.c_str());
printf("can not open %s\n",srcPath.c_str());
return false;
}
if(!dstFile.is_open())
{
LOG_ERROR(stdout, "can not open %s\n", dstPath.c_str());
printf("can not open %s\n", dstPath.c_str());
return false;
}
if(srcPath==dstPath)
{
LOG_ERROR(stdout, "src can not be same with dst\n");
printf("src can not be same with dst\n");
return false;
}
char buffer[2048];
......@@ -622,7 +639,7 @@ namespace migraphxSamples
{
if(srcPath==dstPath)
{
LOG_ERROR(stdout, "src can not be same with dst\n");
printf("src can not be same with dst\n");
return false;
}
......@@ -662,9 +679,9 @@ namespace migraphxSamples
// process
double process = (1.0*(i + 1) / fileNameList.size()) * 100;
LOG_INFO(stdout, "%s done! %f% \n", GetFileName(fileNameList[i]).c_str(), process);
printf("%s done! %f% \n", GetFileName(fileNameList[i]).c_str(), process);
}
LOG_INFO(stdout, "all done!(the number of files:%d)\n", fileNameList.size());
printf("all done!(the number of files:%d)\n", fileNameList.size());
return true;
......
Src/Utility/Filesystem.h
View file @ a3e8d27f
......@@ -3,10 +3,8 @@
#ifndef __FILE_SYSTEM_H__
#define __FILE_SYSTEM_H__
#include <vector>
#include <string>
using namespace std;
#include <vector>
namespace migraphxSamples
{
......@@ -21,7 +19,7 @@ bool IsDirectory(const std::string &path);
bool IsPathSeparator(char c);
// 路径拼接
string JoinPath(const std::string &base, const std::string &path);
std::string JoinPath(const std::string &base, const std::string &path);
// 创建多级目录,注意：创建多级目录的时候，目标目录是不能有文件存在的
bool CreateDirectories(const std::string &directoryPath);
......@@ -49,14 +47,13 @@ void Remove(const std::string &directory, const std::string &extension="");
/** 获取路径的文件名和扩展名
*
* 示例：path为D:/1/1.txt,则GetFileName()为1.txt,GetFileName_NoExtension()为1,GetExtension()为.txt,GetParentPath()为D:/1/
*/
string GetFileName(const std::string &path); // 1.txt
string GetFileName_NoExtension(const std::string &path); // 1
string GetExtension(const std::string &path);// .txt
string GetParentPath(const std::string &path);// D:/1/
std::string GetFileName(const std::string &path);
std::string GetFileName_NoExtension(const std::string &path);
std::string GetExtension(const std::string &path);
std::string GetParentPath(const std::string &path);
// 拷贝文件:CopyFile("D:/1.txt","D:/2.txt");将1.txt拷贝为2.txt
// 拷贝文件
bool CopyFile(const std::string srcPath,const std::string dstPath);
/** 拷贝目录
......
Src/Utility/SimpleLog.h
View file @ a3e8d27f
......@@ -19,7 +19,7 @@ using namespace std;
/** 简易日志
*
* 轻量级日志系统，不依赖于其他第三方库，只需要包含一个头文件就可以使用。提供了4种日志级别，包括INFO,DEBUG,WARN和ERROR。
* 不依赖于其他第三方库，只需要包含一个头文件就可以使用。提供了4种日志级别，包括INFO,DEBUG,WARN和ERROR。
*
* 示例1:
// 初始化日志，在./Log/目录下创建两个日志文件log1.log和log2.log(注意：目录./Log/需要存在，否则日志创建失败)
......
Src/main.cpp
View file @ a3e8d27f
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <opencv2/dnn.hpp>
#include <SimpleLog.h>
#include <CommonDefinition.h>
#include <resnet50.h>
#include <Filesystem.h>
#include <Classifier.h>
int main()
{
// 创建分类器
migraphxSamples::Classifier classifier;
migraphxSamples::InitializationParameterOfClassifier initParamOfClassifier;
initParamOfClassifier.configFilePath=CONFIG_FILE;
migraphxSamples::ErrorCode errorCode=classifier.Initialize(initParamOfClassifier);
if(errorCode!=migraphxSamples::SUCCESS)
{
......@@ -32,10 +32,10 @@ int main()
// 推理
std::vector<std::vector<migraphxSamples::ResultOfPrediction>> predictions;
double time1 = getTickCount();
double time1 = cv::getTickCount();
classifier.Classify(srcImages,predictions);
double time2 = getTickCount();
double elapsedTime = (time2 - time1)*1000 / getTickFrequency();
double time2 = cv::getTickCount();
double elapsedTime = (time2 - time1)*1000 / cv::getTickFrequency();
LOG_INFO(stdout, "inference time:%f ms\n", elapsedTime);
// 获取推理结果
......
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