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Commit adcbffb5 authored by liucong's avatar liucong
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重新进行Cpp代码的格式化

parent acfc7adf
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Showing with 890 additions and 848 deletions
Src/Utility/CommonDefinition.h
View file @ adcbffb5
......@@ -19,21 +19,21 @@ namespace migraphxSamples
typedef enum _ErrorCode
{
SUCCESS=0, // 0
SUCCESS = 0, // 0
MODEL_NOT_EXIST, // 模型不存在
CONFIG_FILE_NOT_EXIST, // 配置文件不存在
FAIL_TO_LOAD_MODEL, // 加载模型失败
FAIL_TO_OPEN_CONFIG_FILE, // 加载配置文件失败
IMAGE_ERROR, // 图像错误
}ErrorCode;
} ErrorCode;
typedef struct _ResultOfPrediction
{
float confidence;
int label;
_ResultOfPrediction():confidence(0.0f),label(0){}
_ResultOfPrediction() : confidence(0.0f), label(0) {}
}ResultOfPrediction;
} ResultOfPrediction;
typedef struct _ResultOfDetection
{
......@@ -43,17 +43,16 @@ typedef struct _ResultOfDetection
std::string className;
bool exist;
_ResultOfDetection():confidence(0.0f),classID(0),exist(true){}
_ResultOfDetection() : confidence(0.0f), classID(0), exist(true) {}
}ResultOfDetection;
} ResultOfDetection;
typedef struct _InitializationParameterOfDetector
{
std::string parentPath;
std::string configFilePath;
}InitializationParameterOfDetector;
} InitializationParameterOfDetector;
}
} // namespace migraphxSamples
#endif
Src/Utility/CommonUtility.cpp
View file @ adcbffb5
......@@ -3,34 +3,37 @@
namespace migraphxSamples
{
bool CompareConfidence(const ResultOfDetection &L,const ResultOfDetection &R)
bool CompareConfidence(const ResultOfDetection& L, const ResultOfDetection& R)
{
return L.confidence > R.confidence;
}
bool CompareArea(const ResultOfDetection &L,const ResultOfDetection &R)
bool CompareArea(const ResultOfDetection& L, const ResultOfDetection& R)
{
return L.boundingBox.area() > R.boundingBox.area();
}
void NMS(std::vector<ResultOfDetection> &detections, float IOUThreshold)
void NMS(std::vector<ResultOfDetection>& detections, float IOUThreshold)
{
// sort
std::sort(detections.begin(), detections.end(), CompareConfidence);
for (int i = 0; i<detections.size(); ++i)
for(int i = 0; i < detections.size(); ++i)
{
if (detections[i].exist)
if(detections[i].exist)
{
for (int j = i + 1; j<detections.size(); ++j)
for(int j = i + 1; j < detections.size(); ++j)
{
if (detections[j].exist)
if(detections[j].exist)
{
// compute IOU
float intersectionArea = (detections[i].boundingBox & detections[j].boundingBox).area();
float intersectionRate = intersectionArea / (detections[i].boundingBox.area() + detections[j].boundingBox.area() - intersectionArea);
float intersectionArea =
(detections[i].boundingBox & detections[j].boundingBox).area();
float intersectionRate =
intersectionArea / (detections[i].boundingBox.area() +
detections[j].boundingBox.area() - intersectionArea);
if (intersectionRate>IOUThreshold)
if(intersectionRate > IOUThreshold)
{
detections[j].exist = false;
}
......@@ -38,7 +41,6 @@ void NMS(std::vector<ResultOfDetection> &detections, float IOUThreshold)
}
}
}
}
}
} // namespace migraphxSamples
Src/Utility/CommonUtility.h
View file @ adcbffb5
......@@ -9,12 +9,12 @@ namespace migraphxSamples
{
// 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);
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);
void NMS(std::vector<ResultOfDetection>& detections, float IOUThreshold);
}
} // namespace migraphxSamples
#endif
Src/Utility/Filesystem.cpp
View file @ adcbffb5
This diff is collapsed.
Src/Utility/Filesystem.h
View file @ adcbffb5
......@@ -10,19 +10,19 @@ namespace migraphxSamples
{
// 路径是否存在
bool Exists(const std::string &path);
bool Exists(const std::string& path);
// 路径是否为目录
bool IsDirectory(const std::string &path);
bool IsDirectory(const std::string& path);
// 是否是路径分隔符(Linux:‘/’,Windows:’\\’)
bool IsPathSeparator(char c);
// 路径拼接
std::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);
bool CreateDirectories(const std::string& directoryPath);
/** 生成符合指定模式的文件名列表(支持递归遍历)
*
......@@ -36,25 +36,33 @@ bool CreateDirectories(const std::string &directoryPath);
5. 不能返回子目录名
*
*/
void GetFileNameList(const std::string &directory, const std::string &pattern, std::vector<std::string> &result, bool recursive, bool addPath);
void GetFileNameList(const std::string& directory,
const std::string& pattern,
std::vector<std::string>& result,
bool recursive,
bool addPath);
// 与GetFileNameList的区别在于如果有子目录，在addPath为true的时候会返回子目录路径(目录名最后有"/")
void GetFileNameList2(const std::string &directory, const std::string &pattern, std::vector<std::string> &result, bool recursive, bool addPath);
void GetFileNameList2(const std::string& directory,
const std::string& pattern,
std::vector<std::string>& result,
bool recursive,
bool addPath);
// 删除文件或者目录,支持递归删除
void Remove(const std::string &directory, const std::string &extension="");
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/
*/
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);
*/
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
bool CopyFile(const std::string srcPath,const std::string dstPath);
bool CopyFile(const std::string srcPath, const std::string dstPath);
/** 拷贝目录
*
......@@ -63,8 +71,8 @@ bool CopyFile(const std::string srcPath,const std::string dstPath);
1.第一个参数的最后不能加”/”
2.不能拷贝隐藏文件
*/
bool CopyDirectories(std::string srcPath,const std::string dstPath);
bool CopyDirectories(std::string srcPath, const std::string dstPath);
}
} // namespace migraphxSamples
#endif
Src/Utility/SimpleLog.h
View file @ adcbffb5
......@@ -8,7 +8,7 @@
#include <map>
#include <thread>
#include <mutex>
#if (defined WIN32 || defined _WIN32)
#if(defined WIN32 || defined _WIN32)
#include <Windows.h>
#else
#include <sys/time.h>
......@@ -16,13 +16,13 @@
using namespace std;
/** 简易日志
*
* 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)
//
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)
LogManager::GetInstance()->Initialize("./Log/","log1");
LogManager::GetInstance()->Initialize("./Log/","log2");
......@@ -50,44 +50,43 @@ using namespace std;
class LogManager
{
private:
LogManager(){}
private:
LogManager() {}
public:
~LogManager(){}
inline void Initialize(const string &parentPath,const string &logName)
public:
~LogManager() {}
inline void Initialize(const string& parentPath, const string& logName)
{
// 日志名为空表示输出到控制台
if(logName.size()==0)
if(logName.size() == 0)
return;
// 查找该日志文件，如果没有则创建
std::map<string, FILE*>::const_iterator iter = logMap.find(logName);
if (iter == logMap.end())
if(iter == logMap.end())
{
string pathOfLog = parentPath+ logName + ".log";
FILE *logFile = fopen(pathOfLog.c_str(), "a"); // w:覆盖原有文件,a:追加
if(logFile!=NULL)
string pathOfLog = parentPath + logName + ".log";
FILE* logFile = fopen(pathOfLog.c_str(), "a"); // w:覆盖原有文件,a:追加
if(logFile != NULL)
{
logMap.insert(std::make_pair(logName, logFile));
}
}
}
inline FILE* GetLogFile(const string &logName)
inline FILE* GetLogFile(const string& logName)
{
std::map<string, FILE*>::const_iterator iter=logMap.find(logName);
if(iter==logMap.end())
std::map<string, FILE*>::const_iterator iter = logMap.find(logName);
if(iter == logMap.end())
{
return NULL;
}
return (*iter).second;
}
inline void Close(const string &logName)
inline void Close(const string& logName)
{
std::map<string, FILE*>::const_iterator iter=logMap.find(logName);
if(iter==logMap.end())
std::map<string, FILE*>::const_iterator iter = logMap.find(logName);
if(iter == logMap.end())
{
return;
}
......@@ -95,10 +94,7 @@ public:
fclose((*iter).second);
logMap.erase(iter);
}
inline std::mutex &GetLogMutex()
{
return logMutex;
}
inline std::mutex& GetLogMutex() { return logMutex; }
// Singleton
static LogManager* GetInstance()
......@@ -106,17 +102,18 @@ public:
static LogManager logManager;
return &logManager;
}
private:
private:
std::map<string, FILE*> logMap;
std::mutex logMutex;
};
#ifdef LOG_MUTEX
#define LOCK LogManager::GetInstance()->GetLogMutex().lock()
#define UNLOCK LogManager::GetInstance()->GetLogMutex().unlock()
#define LOCK LogManager::GetInstance()->GetLogMutex().lock()
#define UNLOCK LogManager::GetInstance()->GetLogMutex().unlock()
#else
#define LOCK
#define UNLOCK
#define LOCK
#define UNLOCK
#endif
// log time
......@@ -131,53 +128,53 @@ typedef struct _LogTime
string millisecond; // ms
string microsecond; // us
string weekDay;
}LogTime;
} LogTime;
inline LogTime GetTime()
{
LogTime currentTime;
#if (defined WIN32 || defined _WIN32)
#if(defined WIN32 || defined _WIN32)
SYSTEMTIME systemTime;
GetLocalTime(&systemTime);
char temp[8] = { 0 };
char temp[8] = {0};
sprintf(temp, "%04d", systemTime.wYear);
currentTime.year=string(temp);
currentTime.year = string(temp);
sprintf(temp, "%02d", systemTime.wMonth);
currentTime.month=string(temp);
currentTime.month = string(temp);
sprintf(temp, "%02d", systemTime.wDay);
currentTime.day=string(temp);
currentTime.day = string(temp);
sprintf(temp, "%02d", systemTime.wHour);
currentTime.hour=string(temp);
currentTime.hour = string(temp);
sprintf(temp, "%02d", systemTime.wMinute);
currentTime.minute=string(temp);
currentTime.minute = string(temp);
sprintf(temp, "%02d", systemTime.wSecond);
currentTime.second=string(temp);
currentTime.second = string(temp);
sprintf(temp, "%03d", systemTime.wMilliseconds);
currentTime.millisecond=string(temp);
currentTime.millisecond = string(temp);
sprintf(temp, "%d", systemTime.wDayOfWeek);
currentTime.weekDay=string(temp);
currentTime.weekDay = string(temp);
#else
struct timeval tv;
struct tm *p;
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",(int)(tv.tv_usec/1000));
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", (int)(tv.tv_usec / 1000));
currentTime.millisecond = string(temp);
sprintf(temp, "%03d", (int)(tv.tv_usec % 1000));
currentTime.microsecond = string(temp);
......@@ -188,60 +185,82 @@ inline LogTime GetTime()
}
#define LOG_TIME(logFile) \
do\
{\
LogTime currentTime=GetTime(); \
fprintf(((logFile == NULL) ? stdout : logFile), "%s-%s-%s %s:%s:%s.%s\t",currentTime.year.c_str(),currentTime.month.c_str(),currentTime.day.c_str(),currentTime.hour.c_str(),currentTime.minute.c_str(),currentTime.second.c_str(),currentTime.millisecond.c_str()); \
}while (0)
#define LOG_INFO(logFile,logInfo, ...) \
do\
{\
do \
{ \
LogTime currentTime = GetTime(); \
fprintf(((logFile == NULL) ? stdout : logFile), \
"%s-%s-%s %s:%s:%s.%s\t", \
currentTime.year.c_str(), \
currentTime.month.c_str(), \
currentTime.day.c_str(), \
currentTime.hour.c_str(), \
currentTime.minute.c_str(), \
currentTime.second.c_str(), \
currentTime.millisecond.c_str()); \
} while(0)
#define LOG_INFO(logFile, logInfo, ...) \
do \
{ \
LOCK; \
LOG_TIME(logFile); \
fprintf(((logFile == NULL) ? stdout : logFile), "INFO\t"); \
fprintf(((logFile == NULL) ? stdout : logFile), "[%s:%d (%s) ]: ", __FILE__, __LINE__, __FUNCTION__); \
fprintf(((logFile == NULL) ? stdout : logFile), logInfo, ## __VA_ARGS__); \
fprintf(((logFile == NULL) ? stdout : logFile), \
"[%s:%d (%s) ]: ", \
__FILE__, \
__LINE__, \
__FUNCTION__); \
fprintf(((logFile == NULL) ? stdout : logFile), logInfo, ##__VA_ARGS__); \
fflush(logFile); \
UNLOCK; \
} while (0)
} while(0)
#define LOG_DEBUG(logFile,logInfo, ...) \
do\
{\
#define LOG_DEBUG(logFile, logInfo, ...) \
do \
{ \
LOCK; \
LOG_TIME(logFile);\
fprintf(((logFile==NULL)?stdout:logFile), "DEBUG\t"); \
fprintf(((logFile==NULL)?stdout:logFile), "[%s:%d (%s) ]: ", __FILE__, __LINE__, __FUNCTION__); \
fprintf(((logFile==NULL)?stdout:logFile),logInfo, ## __VA_ARGS__); \
LOG_TIME(logFile); \
fprintf(((logFile == NULL) ? stdout : logFile), "DEBUG\t"); \
fprintf(((logFile == NULL) ? stdout : logFile), \
"[%s:%d (%s) ]: ", \
__FILE__, \
__LINE__, \
__FUNCTION__); \
fprintf(((logFile == NULL) ? stdout : logFile), logInfo, ##__VA_ARGS__); \
fflush(logFile); \
UNLOCK; \
} while (0)
} while(0)
#define LOG_ERROR(logFile,logInfo, ...) \
do\
{\
#define LOG_ERROR(logFile, logInfo, ...) \
do \
{ \
LOCK; \
LOG_TIME(logFile);\
fprintf(((logFile==NULL)?stdout:logFile), "ERROR\t"); \
fprintf(((logFile==NULL)?stdout:logFile), "[%s:%d (%s) ]: ", __FILE__, __LINE__, __FUNCTION__); \
fprintf(((logFile==NULL)?stdout:logFile),logInfo, ## __VA_ARGS__); \
LOG_TIME(logFile); \
fprintf(((logFile == NULL) ? stdout : logFile), "ERROR\t"); \
fprintf(((logFile == NULL) ? stdout : logFile), \
"[%s:%d (%s) ]: ", \
__FILE__, \
__LINE__, \
__FUNCTION__); \
fprintf(((logFile == NULL) ? stdout : logFile), logInfo, ##__VA_ARGS__); \
fflush(logFile); \
UNLOCK; \
} while (0)
} while(0)
#define LOG_WARN(logFile,logInfo, ...) \
do\
{\
#define LOG_WARN(logFile, logInfo, ...) \
do \
{ \
LOCK; \
LOG_TIME(logFile);\
fprintf(((logFile==NULL)?stdout:logFile), "WARN\t"); \
fprintf(((logFile==NULL)?stdout:logFile), "[%s:%d (%s) ]: ", __FILE__, __LINE__, __FUNCTION__); \
fprintf(((logFile==NULL)?stdout:logFile),logInfo, ## __VA_ARGS__); \
LOG_TIME(logFile); \
fprintf(((logFile == NULL) ? stdout : logFile), "WARN\t"); \
fprintf(((logFile == NULL) ? stdout : logFile), \
"[%s:%d (%s) ]: ", \
__FILE__, \
__LINE__, \
__FUNCTION__); \
fprintf(((logFile == NULL) ? stdout : logFile), logInfo, ##__VA_ARGS__); \
fflush(logFile); \
UNLOCK; \
} while (0)
} while(0)
#endif // __SIMPLE_LOG_H__
Src/YOLOV7.cpp
View file @ adcbffb5
......@@ -8,20 +8,15 @@
namespace migraphxSamples
{
DetectorYOLOV7::DetectorYOLOV7()
{
}
DetectorYOLOV7::DetectorYOLOV7() {}
DetectorYOLOV7::~DetectorYOLOV7()
{
configurationFile.release();
}
DetectorYOLOV7::~DetectorYOLOV7() { configurationFile.release(); }
ErrorCode DetectorYOLOV7::Initialize(InitializationParameterOfDetector initializationParameterOfDetector)
ErrorCode
DetectorYOLOV7::Initialize(InitializationParameterOfDetector initializationParameterOfDetector)
{
// 读取配置文件
std::string configFilePath=initializationParameterOfDetector.configFilePath;
std::string configFilePath = initializationParameterOfDetector.configFilePath;
if(!Exists(configFilePath))
{
LOG_ERROR(stdout, "no configuration file!\n");
......@@ -36,33 +31,33 @@ ErrorCode DetectorYOLOV7::Initialize(InitializationParameterOfDetector initializ
// 获取配置文件参数
cv::FileNode netNode = configurationFile["DetectorYOLOV7"];
std::string modelPath=(std::string)netNode["ModelPath"];
std::string pathOfClassNameFile=(std::string)netNode["ClassNameFile"];
std::string modelPath = (std::string)netNode["ModelPath"];
std::string pathOfClassNameFile = (std::string)netNode["ClassNameFile"];
yolov7Parameter.confidenceThreshold = (float)netNode["ConfidenceThreshold"];
yolov7Parameter.nmsThreshold = (float)netNode["NMSThreshold"];
yolov7Parameter.objectThreshold = (float)netNode["ObjectThreshold"];
yolov7Parameter.numberOfClasses=(int)netNode["NumberOfClasses"];
useFP16=(bool)(int)netNode["UseFP16"];
yolov7Parameter.numberOfClasses = (int)netNode["NumberOfClasses"];
useFP16 = (bool)(int)netNode["UseFP16"];
// 加载模型
if(!Exists(modelPath))
{
LOG_ERROR(stdout,"%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(stdout,"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/输出节点信息
std::unordered_map<std::string, migraphx::shape> inputs=net.get_inputs();
std::unordered_map<std::string, migraphx::shape> outputs=net.get_outputs();
inputName=inputs.begin()->first;
inputShape=inputs.begin()->second;
int N=inputShape.lens()[0];
int C=inputShape.lens()[1];
int H=inputShape.lens()[2];
int W=inputShape.lens()[3];
inputSize=cv::Size(W,H);
std::unordered_map<std::string, migraphx::shape> inputs = net.get_inputs();
std::unordered_map<std::string, migraphx::shape> outputs = net.get_outputs();
inputName = inputs.begin()->first;
inputShape = inputs.begin()->second;
int N = inputShape.lens()[0];
int C = inputShape.lens()[1];
int H = inputShape.lens()[2];
int W = inputShape.lens()[3];
inputSize = cv::Size(W, H);
// 设置模型为GPU模式
migraphx::target gpuTarget = migraphx::gpu::target{};
......@@ -75,14 +70,14 @@ ErrorCode DetectorYOLOV7::Initialize(InitializationParameterOfDetector initializ
// 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;
net.compile(gpuTarget,options);
LOG_INFO(stdout,"succeed to compile model: %s\n",GetFileName(modelPath).c_str());
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(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};
inputData[inputName] = migraphx::argument{inputShape};
net.eval(inputData);
// 读取类别名
......@@ -90,7 +85,7 @@ ErrorCode DetectorYOLOV7::Initialize(InitializationParameterOfDetector initializ
{
std::ifstream classNameFile(pathOfClassNameFile);
std::string line;
while (getline(classNameFile, line))
while(getline(classNameFile, line))
{
classNames.push_back(line);
}
......@@ -101,19 +96,20 @@ ErrorCode DetectorYOLOV7::Initialize(InitializationParameterOfDetector initializ
}
// log
LOG_INFO(stdout,"InputSize:%dx%d\n",inputSize.width,inputSize.height);
LOG_INFO(stdout,"InputName:%s\n",inputName.c_str());
LOG_INFO(stdout,"ConfidenceThreshold:%f\n",yolov7Parameter.confidenceThreshold);
LOG_INFO(stdout,"objectThreshold:%f\n",yolov7Parameter.objectThreshold);
LOG_INFO(stdout,"NMSThreshold:%f\n",yolov7Parameter.nmsThreshold);
LOG_INFO(stdout,"NumberOfClasses:%d\n",yolov7Parameter.numberOfClasses);
LOG_INFO(stdout, "InputSize:%dx%d\n", inputSize.width, inputSize.height);
LOG_INFO(stdout, "InputName:%s\n", inputName.c_str());
LOG_INFO(stdout, "ConfidenceThreshold:%f\n", yolov7Parameter.confidenceThreshold);
LOG_INFO(stdout, "objectThreshold:%f\n", yolov7Parameter.objectThreshold);
LOG_INFO(stdout, "NMSThreshold:%f\n", yolov7Parameter.nmsThreshold);
LOG_INFO(stdout, "NumberOfClasses:%d\n", yolov7Parameter.numberOfClasses);
return SUCCESS;
}
ErrorCode DetectorYOLOV7::Detect(const cv::Mat &srcImage, std::vector<ResultOfDetection> &resultsOfDetection)
ErrorCode DetectorYOLOV7::Detect(const cv::Mat& srcImage,
std::vector<ResultOfDetection>& resultsOfDetection)
{
if(srcImage.empty()||srcImage.type()!=CV_8UC3)
if(srcImage.empty() || srcImage.type() != CV_8UC3)
{
LOG_ERROR(stdout, "image error!\n");
return IMAGE_ERROR;
......@@ -121,17 +117,12 @@ ErrorCode DetectorYOLOV7::Detect(const cv::Mat &srcImage, std::vector<ResultOfDe
// 数据预处理并转换为NCHW格式
cv::Mat inputBlob;
cv::dnn::blobFromImage(srcImage,
inputBlob,
1 / 255.0,
inputSize,
cv::Scalar(0, 0, 0),
true,
false);
cv::dnn::blobFromImage(
srcImage, inputBlob, 1 / 255.0, inputSize, cv::Scalar(0, 0, 0), true, false);
// 创建输入数据
std::unordered_map<std::string, migraphx::argument> inputData;
inputData[inputName]= migraphx::argument{inputShape, (float*)inputBlob.data};
inputData[inputName] = migraphx::argument{inputShape, (float*)inputBlob.data};
// 推理
std::vector<migraphx::argument> inferenceResults = net.eval(inputData);
......@@ -142,37 +133,38 @@ ErrorCode DetectorYOLOV7::Detect(const cv::Mat &srcImage, std::vector<ResultOfDe
// 转换为cv::Mat
migraphx::shape outputShape = result.get_shape();
int shape[]={outputShape.lens()[0],outputShape.lens()[1],outputShape.lens()[2]};
cv::Mat out(3,shape,CV_32F);
memcpy(out.data,result.data(),sizeof(float)*outputShape.elements());
int shape[] = {outputShape.lens()[0], outputShape.lens()[1], outputShape.lens()[2]};
cv::Mat out(3, shape, CV_32F);
memcpy(out.data, result.data(), sizeof(float) * outputShape.elements());
outs.push_back(out);
//获取先验框的个数
// 获取先验框的个数
int numProposal = outs[0].size[1];
int numOut = outs[0].size[2];
//变换输出的维度
// 变换输出的维度
outs[0] = outs[0].reshape(0, numProposal);
//生成先验框
// 生成先验框
std::vector<float> confidences;
std::vector<cv::Rect> boxes;
std::vector<int> classIds;
float ratioh = (float)srcImage.rows / inputSize.height, ratiow = (float)srcImage.cols / inputSize.width;
float ratioh = (float)srcImage.rows / inputSize.height,
ratiow = (float)srcImage.cols / inputSize.width;
//计算cx,cy,w,h,box_sore,class_sore
// 计算cx,cy,w,h,box_sore,class_sore
int n = 0, rowInd = 0;
float* pdata = (float*)outs[0].data;
for (n = 0; n < numProposal; n++)
for(n = 0; n < numProposal; n++)
{
float boxScores = pdata[4];
if (boxScores > yolov7Parameter.objectThreshold)
if(boxScores > yolov7Parameter.objectThreshold)
{
cv::Mat scores = outs[0].row(rowInd).colRange(5, numOut);
cv::Point classIdPoint;
double maxClassScore;
cv::minMaxLoc(scores, 0, &maxClassScore, 0, &classIdPoint);
maxClassScore *= boxScores;
if (maxClassScore > yolov7Parameter.confidenceThreshold)
if(maxClassScore > yolov7Parameter.confidenceThreshold)
{
const int classIdx = classIdPoint.x;
float cx = pdata[0] * ratiow;
......@@ -192,26 +184,30 @@ ErrorCode DetectorYOLOV7::Detect(const cv::Mat &srcImage, std::vector<ResultOfDe
pdata += numOut;
}
//执行non maximum suppression消除冗余重叠boxes
// 执行non maximum suppression消除冗余重叠boxes
std::vector<int> indices;
cv::dnn::NMSBoxes(boxes, confidences, yolov7Parameter.confidenceThreshold, yolov7Parameter.nmsThreshold, indices);
for (size_t i = 0; i < indices.size(); ++i)
cv::dnn::NMSBoxes(boxes,
confidences,
yolov7Parameter.confidenceThreshold,
yolov7Parameter.nmsThreshold,
indices);
for(size_t i = 0; i < indices.size(); ++i)
{
int idx = indices[i];
int classID=classIds[idx];
std::string className=classNames[classID];
float confidence=confidences[idx];
int classID = classIds[idx];
std::string className = classNames[classID];
float confidence = confidences[idx];
cv::Rect box = boxes[idx];
ResultOfDetection result;
result.boundingBox=box;
result.confidence=confidence;// confidence
result.classID=classID; // label
result.className=className;
result.boundingBox = box;
result.confidence = confidence; // confidence
result.classID = classID; // label
result.className = className;
resultsOfDetection.push_back(result);
}
return SUCCESS;
}
}
} // namespace migraphxSamples
Src/YOLOV7.h
View file @ adcbffb5
......@@ -14,20 +14,20 @@ typedef struct _YOLOV7Parameter
float nmsThreshold;
float objectThreshold;
}YOLOV7Parameter;
} YOLOV7Parameter;
class DetectorYOLOV7
{
public:
public:
DetectorYOLOV7();
~DetectorYOLOV7();
ErrorCode Initialize(InitializationParameterOfDetector initializationParameterOfDetector);
ErrorCode Detect(const cv::Mat &srcImage, std::vector<ResultOfDetection> &resultsOfDetection);
ErrorCode Detect(const cv::Mat& srcImage, std::vector<ResultOfDetection>& resultsOfDetection);
private:
private:
cv::FileStorage configurationFile;
migraphx::program net;
......@@ -41,6 +41,6 @@ private:
YOLOV7Parameter yolov7Parameter;
};
}
} // namespace migraphxSamples
#endif
Src/main.cpp
View file @ adcbffb5
......@@ -11,8 +11,8 @@ int main()
migraphxSamples::DetectorYOLOV7 detector;
migraphxSamples::InitializationParameterOfDetector initParamOfDetectorYOLOV7;
initParamOfDetectorYOLOV7.configFilePath = CONFIG_FILE;
migraphxSamples::ErrorCode errorCode=detector.Initialize(initParamOfDetectorYOLOV7);
if(errorCode!=migraphxSamples::SUCCESS)
migraphxSamples::ErrorCode errorCode = detector.Initialize(initParamOfDetectorYOLOV7);
if(errorCode != migraphxSamples::SUCCESS)
{
LOG_ERROR(stdout, "fail to initialize detector!\n");
exit(-1);
......@@ -20,18 +20,18 @@ int main()
LOG_INFO(stdout, "succeed to initialize detector\n");
// 读取测试图片
cv::Mat srcImage=cv::imread("../Resource/Images/bus.jpg",1);
cv::Mat srcImage = cv::imread("../Resource/Images/bus.jpg", 1);
// 推理
std::vector<migraphxSamples::ResultOfDetection> predictions;
detector.Detect(srcImage,predictions);
detector.Detect(srcImage, predictions);
// 获取推理结果
LOG_INFO(stdout,"========== Detection Results ==========\n");
for(int i=0;i<predictions.size();++i)
LOG_INFO(stdout, "========== Detection Results ==========\n");
for(int i = 0; i < predictions.size(); ++i)
{
migraphxSamples::ResultOfDetection result=predictions[i];
cv::rectangle(srcImage,result.boundingBox,cv::Scalar(0,255,255),2);
migraphxSamples::ResultOfDetection result = predictions[i];
cv::rectangle(srcImage, result.boundingBox, cv::Scalar(0, 255, 255), 2);
std::string label = cv::format("%.2f", result.confidence);
label = result.className + " " + label;
......@@ -40,13 +40,25 @@ int main()
int baseLine;
cv::Size labelSize = cv::getTextSize(label, cv::FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine);
top = max(top, labelSize.height);
cv::putText(srcImage, label, cv::Point(left, top-10), cv::FONT_HERSHEY_SIMPLEX, 1, cv::Scalar(0, 255, 255), 2);
cv::putText(srcImage,
label,
cv::Point(left, top - 10),
cv::FONT_HERSHEY_SIMPLEX,
1,
cv::Scalar(0, 255, 255),
2);
LOG_INFO(stdout,"box:%d %d %d %d,label:%d,confidence:%f\n",predictions[i].boundingBox.x,
predictions[i].boundingBox.y,predictions[i].boundingBox.width,predictions[i].boundingBox.height,predictions[i].classID,predictions[i].confidence);
LOG_INFO(stdout,
"box:%d %d %d %d,label:%d,confidence:%f\n",
predictions[i].boundingBox.x,
predictions[i].boundingBox.y,
predictions[i].boundingBox.width,
predictions[i].boundingBox.height,
predictions[i].classID,
predictions[i].confidence);
}
cv::imwrite("Result.jpg",srcImage);
LOG_INFO(stdout,"Detection results have been saved to ./Result.jpg\n");
cv::imwrite("Result.jpg", srcImage);
LOG_INFO(stdout, "Detection results have been saved to ./Result.jpg\n");
return 0;
}
\ No newline at end of file
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