SSD仿真代码

SvpSampleCnnDetSSD

memory needed by post-process of get detection result

4.解析完的结果：stBox :  vTaggedBoxes

输入：1.netType

重要的步骤

draw detection rect boxes to src Image

输入：1.stSSDParam

#define SVP_NNIE_LAYER_CONF_CNT (4)//6#define SVP_NNIE_LAYER_PRIORBOX_CNT (4)//6#define SVP_NNIE_LAYER_SOFTMAX_CNT (4)//6#define SVP_NNIE_LAYER_DETECT_CNT (4)//6#define SVP_NNIE_LAYER_INCNT (8)//12#define SVP_NNIE_LAYER_OUTCNT (8)//12#define SVP_NNIE_AR_NUM (2)#define SVP_NNIE_PRIORBOX_NUM (4)#define SVP_NNIE_MINSIZE_NUM (3)#define SVP_SAMPLE_SSD_REPORT_NUM (8)//12/**********************************parameter struct*************************************/typedef struct hiSVP_NNIE_SSD_S{    //------ parameters for PriorBox ------    HI_S32 priorbox_layer_width[SVP_NNIE_LAYER_PRIORBOX_CNT];    HI_S32 priorbox_layer_height[SVP_NNIE_LAYER_PRIORBOX_CNT];    HI_S32 img_width;    HI_S32 img_height;    HI_FLOAT priorbox_min_size[SVP_NNIE_LAYER_PRIORBOX_CNT][SVP_NNIE_MINSIZE_NUM]; //    HI_S32 min_size_num;    HI_FLOAT priorbox_max_size[SVP_NNIE_LAYER_PRIORBOX_CNT];    HI_S32 max_size_num;    HI_S32 flip;    HI_S32 clip;    HI_S32 input_ar_num[SVP_NNIE_LAYER_PRIORBOX_CNT];    HI_FLOAT priorbox_aspect_ratio[SVP_NNIE_LAYER_PRIORBOX_CNT][SVP_NNIE_AR_NUM];    HI_FLOAT priorbox_step_w[SVP_NNIE_LAYER_PRIORBOX_CNT];    HI_FLOAT priorbox_step_h[SVP_NNIE_LAYER_PRIORBOX_CNT];    HI_FLOAT offset;    HI_S32 priorbox_var[SVP_NNIE_PRIORBOX_NUM];    HI_S32* priorbox_output_data[SVP_NNIE_LAYER_PRIORBOX_CNT + 1];    // ------ parameters for Softmax ------    HI_S32 softmax_in_height;    HI_U32 softmax_in_channel[SVP_NNIE_LAYER_SOFTMAX_CNT];    HI_S32 concat_num;    HI_S32 softmax_out_width;    HI_S32 softmax_out_height;    HI_S32 softmax_out_channel;    HI_S32 softmax_input_width[SVP_NNIE_LAYER_SOFTMAX_CNT];    HI_S32* softmax_input_data[SVP_NNIE_LAYER_SOFTMAX_CNT];    HI_S32* softmax_output_data;    //------ parameters for concat conv bias ------    HI_S32* conv_data[SVP_NNIE_LAYER_INCNT];    HI_S32 conv_width[SVP_NNIE_LAYER_INCNT];    HI_S32 conv_height[SVP_NNIE_LAYER_INCNT];    HI_S32 conv_channel[SVP_NNIE_LAYER_INCNT];    HI_S32 conv_stride[SVP_NNIE_LAYER_INCNT];    // ------ parameters for Permute ------    HI_S32* permute_output_data[SVP_NNIE_LAYER_OUTCNT];    HI_S32 permute_output_width[SVP_NNIE_LAYER_OUTCNT];    HI_S32 permute_output_height[SVP_NNIE_LAYER_OUTCNT];    HI_S32 permute_output_channel[SVP_NNIE_LAYER_OUTCNT];    // ------ parameters for detectionOut ------    HI_S32* detection_out_loc_data[SVP_NNIE_LAYER_DETECT_CNT];    HI_S32* detection_out_assist_mem;    HI_U32 detect_input_channel[SVP_NNIE_LAYER_DETECT_CNT];    HI_S32 num_classes;    HI_S32 top_k;    HI_S32 keep_top_k;    HI_S32 nms_thresh;    HI_S32 conf_thresh;} SVP_NNIE_SSD_S;

ssd_inerface.cpp

输出的输出

输入：2.stSSDParam

数据结构

cv_draw_rect.cpp

1. check input para

输入：3.&stBoxesInfo

输入：3.netType

输入：2.stDetParam

stDetCfgtypedef struct hiSVP_NNIE_CFG_S{    const HI_CHAR *pszModelName;    const HI_CHAR *paszPicList[SVP_NNIE_MAX_INPUT_NUM];    const HI_CHAR *paszLabel[SVP_NNIE_MAX_OUTPUT_NUM];    HI_U32 u32MaxInputNum;    HI_U32 u32MaxBboxNum;    HI_U32 u32TopN;    HI_BOOL bNeedLabel;}SVP_NNIE_CFG_S; 

HI_S32 SvpDetSsdGetDetectInputNum(const SVP_NNIE_SSD_S *para){ HI_S32 s32PriorSum = 0; for (HI_S32 i = 0; i < para->concat_num; i++) { s32PriorSum += para->detect_input_channel[i] / 4; } return s32PriorSum;}HI_S32 SvpDetSsdGetDetectOutSize(const SVP_NNIE_SSD_S *para){ HI_S32 s32PriorNum = SvpDetSsdGetDetectInputNum(para); return s32PriorNum*(4 + 6 + 6)*sizeof(HI_S32) + MAX_STACK_DEPTH * sizeof(SVP_SAMPLE_STACK_S);}

SvpSampleDetectionOneSeg.cpp

输入：1.pstDetParam

stDetParamstDetCfg

pszModelNamepaszPicList

HI_MPI_SVP_NNIE_Query

输入：6.imgNameRecoder

dst_score_sizedst_bbox_sizedst_roicnt_sizeu32PriorSizeu32SoftmaxSizeu32DetectionOutSizeu32ResultMemSize = 以上相加

SVP_SAMPLE_MIN

SvpSampleCom.cpp

SvpSampleOneSegDetCnnDeinit(&stDetParam);

step7 set ctrl param

输入：1.pstSSDParam

hi_comm_svp.h

2. declare definitions

 5.j为共输入几张照片

4. run forward and detection

3. init resources

输入：4.p32BoxNum

typedef struct tagSVPUtils_Rect_S{ HI_U32 x; HI_U32 y; HI_U32 w; HI_U32 h;} SVPUtils_Rect_S;typedef struct tagSVPUtil_TaggedBox_S{ SVPUtils_Rect_S stRect; HI_U32 u32Class; HI_FLOAT fScore;} SVPUtils_TaggedBox_S; 

1.pstDetParam->astSrc=====pstSrcBlob

SvpSampleSsd.cpp

重要的函数

所在的文件名字

dst_score

HI_MPI_SVP_NNIE_Forward

cv_draw_rect.h

u32DetectionOutSize = SvpDetSsdGetDetectOutSize(pstSSDParam);

ssd_interface.h

stDetParamtypedef struct hiSVP_NNIE_ONE_SEG_DET_S{    HI_U32 u32TotalImgNum;    FILE *fpSrc[SVP_NNIE_MAX_INPUT_NUM];    FILE *fpLabel[SVP_NNIE_MAX_OUTPUT_NUM];    HI_U32 u32ModelBufSize;    HI_U32 u32TmpBufSize;    SVP_NNIE_MODEL_S    stModel;    SVP_MEM_INFO_S      stModelBuf;    SVP_MEM_INFO_S      stTmpBuf;    SVP_MEM_INFO_S      stTskBuf;    HI_U32 u32TaskBufSize;    SVP_SRC_BLOB_S astSrc[SVP_NNIE_MAX_INPUT_NUM];    SVP_DST_BLOB_S astDst[SVP_NNIE_MAX_OUTPUT_NUM];    SVP_NNIE_FORWARD_CTRL_S stCtrl;    //memory needed by post-process of getting detection result    HI_S32 *ps32ResultMem;}SVP_NNIE_ONE_SEG_DET_S;

typedef struct hiSVP_SAMPLE_BOX_S{ HI_FLOAT f32Xmin; HI_FLOAT f32Xmax; HI_FLOAT f32Ymin; HI_FLOAT f32Ymax; HI_FLOAT f32ClsScore; HI_U32 u32MaxScoreIndex; HI_U32 u32Mask;}SVP_SAMPLE_BOX_S;typedef struct hiSVP_SAMPLE_BOX_RESULT_INFO_S{ HI_U32 u32OriImHeight; HI_U32 u32OriImWidth; SVP_SAMPLE_BOX_S* pstBbox;}SVP_SAMPLE_BOX_RESULT_INFO_S;

重要的参数

2.输入的数据：pstSSDParam->conv_data

use resultMem

SvpSampleMkdir

3.画好的图片保存在哪里？

SvpSampleWk.h

SvpSampleCnnDetectionOneSeg

calc batch loop count

输入：1.stDetCfg

SvpSampleNetCom.cpp

输入：1.g_paszModelName_d2.g_paszPicList_d3.netType（非）4：s32Cnt，最大为16，一般为1

2.图片类型：RGBPLANAR

5. deinit resources

输入：2.pstSSDParam