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Add C++ Classify inference example (#6868)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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DennisJ 2023-12-10 23:41:24 +08:00 • committed by GitHub
parent 1b37a13131
commit b62b20d517
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4 changed files with 380 additions and 223 deletions
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64
examples/YOLOv8-ONNXRuntime-CPP/inference.h
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@ -19,53 +19,59 @@
#endif
enum MODEL_TYPE {
enum MODEL_TYPE
{
//FLOAT32 MODEL
YOLO_ORIGIN_V5 = 0,
YOLO_ORIGIN_V8 = 1,//only support v8 detector currently
YOLO_POSE_V8 = 2,
YOLO_CLS_V8 = 3,
YOLO_ORIGIN_V8_HALF = 4,
YOLO_DETECT_V8 = 1,
YOLO_POSE = 2,
YOLO_CLS = 3,
//FLOAT16 MODEL
YOLO_DETECT_V8_HALF = 4,
YOLO_POSE_V8_HALF = 5,
YOLO_CLS_V8_HALF = 6
};
typedef struct _DCSP_INIT_PARAM {
std::string ModelPath;
MODEL_TYPE ModelType = YOLO_ORIGIN_V8;
std::vector<int> imgSize = {640, 640};
float RectConfidenceThreshold = 0.6;
typedef struct _DL_INIT_PARAM
{
std::string modelPath;
MODEL_TYPE modelType = YOLO_DETECT_V8;
std::vector<int> imgSize = { 640, 640 };
float rectConfidenceThreshold = 0.6;
float iouThreshold = 0.5;
bool CudaEnable = false;
int LogSeverityLevel = 3;
int IntraOpNumThreads = 1;
} DCSP_INIT_PARAM;
int keyPointsNum = 2;//Note:kpt number for pose
bool cudaEnable = false;
int logSeverityLevel = 3;
int intraOpNumThreads = 1;
} DL_INIT_PARAM;
typedef struct _DCSP_RESULT {
typedef struct _DL_RESULT
{
int classId;
float confidence;
cv::Rect box;
} DCSP_RESULT;
std::vector<cv::Point2f> keyPoints;
} DL_RESULT;
class DCSP_CORE {
class YOLO_V8
{
public:
DCSP_CORE();
YOLO_V8();
~DCSP_CORE();
~YOLO_V8();
public:
char *CreateSession(DCSP_INIT_PARAM &iParams);
char* CreateSession(DL_INIT_PARAM& iParams);
char *RunSession(cv::Mat &iImg, std::vector<DCSP_RESULT> &oResult);
char* RunSession(cv::Mat& iImg, std::vector<DL_RESULT>& oResult);
char *WarmUpSession();
char* WarmUpSession();
template<typename N>
char *TensorProcess(clock_t &starttime_1, cv::Mat &iImg, N &blob, std::vector<int64_t> &inputNodeDims,
std::vector<DCSP_RESULT> &oResult);
char* TensorProcess(clock_t& starttime_1, cv::Mat& iImg, N& blob, std::vector<int64_t>& inputNodeDims,
std::vector<DL_RESULT>& oResult);
char* PreProcess(cv::Mat& iImg, std::vector<int> iImgSize, cv::Mat& oImg);
@ -73,11 +79,11 @@ public:
private:
Ort::Env env;
Ort::Session *session;
Ort::Session* session;
bool cudaEnable;
Ort::RunOptions options;
std::vector<const char *> inputNodeNames;
std::vector<const char *> outputNodeNames;
std::vector<const char*> inputNodeNames;
std::vector<const char*> outputNodeNames;
MODEL_TYPE modelType;
std::vector<int> imgSize;