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/*
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* @Author: turboLIU
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* @Date: 2022-11-02 15:04:08
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* @LastEditTime: 2024-10-25 09:17:48
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* @Description: Do not edit
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* @FilePath: /Algo_ACL_Common/API/AI_API.h
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*/
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#ifndef AI_API
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#define AI_API
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#include <string>
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#include "detection_type_api.h"
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using namespace AIGO;
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#ifdef __cplusplus
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extern "C"{
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#endif
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/**
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* @brief 算法启动前，最先年调用该函数，用于设置NPU硬件环境
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*
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* @return int 非0表示环境异常
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*/
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int Init_ACL();
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/**
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* @brief Set the deque size object
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*
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* @param irdetin
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* @param visdetin
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* @param irsegin
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* @param vissegin
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* @param irdetout
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* @param visdetout
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* @param irsegout
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* @param vissegout
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* @param irdetres
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* @param visdetres
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* @param irsegres
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* @param vissegres
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* @return int
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*/
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int set_deque_size(int irdetin=3, int visdetin=3, int irsegin=3, int vissegin=3, int irdetout=5, int visdetout = 5, int irsegout = 5, int vissegout = 5,
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int irdetres = 10, int visdetres = 10, int irsegres = 10, int vissegres = 10);
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int get_deque_size(int &irdetin, int &visdetin, int &irsegin, int &vissegin, int &irdetout, int &visdetout, int &irsegout, int &vissegout,
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int &irdetres, int &visdetres, int &irsegres, int &vissegres);
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int reset_dequeu_size(int irdetin=30, int visdetin=30, int irsegin=30, int vissegin=30, int irdetout=50, int visdetout = 50, int irsegout = 50, int vissegout = 50,
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int irdetres = 100, int visdetres = 100, int irsegres = 100, int vissegres = 100);
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/**
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* @brief Set the stream size object
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* init 函数调用之前，设置模型宽高；默认 1280， 1024
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*
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* @param width 模型宽 默认1280
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* @param height 模型高 默认1024
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* @return int
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*/
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int set_stream_size(int width, int height, MODE mode);
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int get_stream_size(int &width, int &height, MODE mode);
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int reset_stream_size(int width, int height, MODE mode);
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/**
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* @brief 同时初始化检测和分割模型
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*
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* @param irdetmodel 红外检测模型
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* @param visdetmodel 可见光检测模型
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* @param irsegmodel 红外分割模型
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* @param vissegmodel 可见光分割模型
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* @return int
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*/
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int Init_AI(const char* irdetmodel, const char* visdetmodel, const char* irsegmodel, const char* vissegmodel);
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int Det_VL(ImgMat frame, std::vector<objinfo> &outputs);
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int Det_IR(ImgMat frame, std::vector<objinfo> &outputs);
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int Seg_VL(ImgMat frame, TenMat* output);
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int Seg_IR(ImgMat frame, TenMat* output);
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/**
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* @brief 运行检测分割算法，异步接口，调用get_result函数获取结果
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*
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* @param img
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* @param GoDet 是否执行检测算法
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* @param GoSeg 是否执行分割算法
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* @param cropFlag 是否中心裁减，裁减大小通过 set_ROIArea 设置
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* @return int
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*/
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int runAsync(ImgMat img, bool GoDet=true, bool GoSeg=true, bool cropFlag=false);
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/**
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* @brief Get the result object，获取已异步结果
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*
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* @param timestamp
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* @param dets
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* @param maskImg
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* @param front: true: 先进先出， false: 后进先出
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* @param single true：仅获取当前光源的算法结果， false：获取双光结果
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* @return int -1:队列被释放； 1: 队列为空; 0: 成功从队列获取结果；
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*/
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int get_result(long long ×tamp, std::vector<objinfo> &dets, TenMat * maskImg, bool front=true, MODE mode=VIS); // async
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/**
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* @brief 由可见光为主光源，切换至红外为主光源
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*
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* @return int
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*/
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int switch_vis_to_ir();
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/**
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* @brief 由红外为主光源，切换至可见光为主光源
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*
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* @return int
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*/
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int switch_ir_to_vis();
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/**
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* @brief Set the dropout param
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*
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* @param drop true: drop deque front data, false: not drop data, 默认: false
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* @return int
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*/
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int set_dropout_param(bool drop);
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/**
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* @brief Get the dropout param
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*
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* @param drop
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* @return int
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*/
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int get_dropout_param(bool &drop);
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/**
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* @brief 设置分割类型，可时时生效
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*
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* @param mode IR or VIS
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* @param road segment road or not
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* @param bridge segment bridge or not
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* @param water segment water or not
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* @param building segment building or not
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* @return int
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*/
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int set_seg_classes(MODE mode, bool road, bool bridge, bool water, bool building);
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/**
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* @brief Set the nms threshold object
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*
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* @param nms
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* @return int
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*/
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int set_nms_threshold(float nms);
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/**
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* @brief Get the nms threshold object
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*
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* @param nms
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* @return int
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*/
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int get_nms_threshold(float& nms);
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/**
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* @brief Set the det threshold object
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*
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* @param threshold 置信度
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* @param idx 1～15，设置哪一个种类的置信度，种类编号参见CLASSTYPE
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* @return int
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*/
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int set_det_threshold(float threshold, int idx);
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/**
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* @brief Get the det threshold object
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*
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* @param threshold 置信度
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* @param idx 1～15，设置哪一个种类的置信度，种类编号参见CLASSTYPE
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* @return int
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*/
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int get_det_threshold(float &threshold, int idx);
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/**
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* @brief Set the seg threshold object
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*
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* @param thr
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* @return int
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*/
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int set_seg_threshold(float thr);
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/**
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* @brief Get the seg threshold object
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*
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* @return float
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*/
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float get_seg_threshold();
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/**
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* @brief 设置数据流模式，仅支持: BGR，RGB，NV12， NV21； 默认RGB
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*
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* @param m
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* @return int
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*/
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int set_StreamMode(INPUT_LAYOUT m);
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/**
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* @brief Get the StreamMode object
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*
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* @return INPUT_LAYOUT
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*/
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INPUT_LAYOUT get_StreamMode();
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/**
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* @brief 算法关闭时调用，释放算法内部资源
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*
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* @return int
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*/
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int Uninit_AI();
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/**
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* @brief only deinit hardware
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*
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* @return int
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*/
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int Uninit_ACL();
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/**
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* @brief Set the ROIArea object
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*
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* @param x1 lefttop
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* @param y1 lefttop
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* @param x2 botright
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* @param y2 botright
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* @return int
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*/
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int set_ROIArea(int x1, int y1, int x2, int y2);
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int setLabelMap(uint32_t A[], uint32_t B[], uint32_t len);
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class DETECTION_API
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{
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private:
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/* data */
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public:
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DETECTION_API(/* args */);
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~DETECTION_API();
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public:
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int netWidth=0;
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int netHeight = 0;
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int clsnum = 0;
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std::vector<std::vector<float>> anchors;// = {{7,11, 9,21, 21,15},{16,39, 31,24, 57,27},{43,59, 90,59, 131,116}};
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void* AIGOhandle=NULL;
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int AIGOinit(const char* modename, int deviceID=0);
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int AIGOpreprocess(ImgMat img, bool doCopy=true);
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int AIGOinfer();
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int AIGOpostprocess(std::vector<objinfo> &results);
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int AIGOdeinit();
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};
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class SEGMENTION_API
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{
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private:
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/* data */
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public:
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SEGMENTION_API(/* args */);
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~SEGMENTION_API();
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int netWidth = 0;
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int netHeight = 0;
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int clsnum = 0;
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void* AIGOhandle = NULL;
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int AIGOinit(const char* modename, int deviceID=0);
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int AIGOpreprocess(ImgMat img, bool doCopy=true);
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int AIGOinfer();
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int AIGOpostprocess();
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int AIGOdeinit();
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};
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#ifdef __cplusplus
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}
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#endif
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#endif |
