Hi3559AV100 NNIE开发（6）RFCN中NNIE实现关键线程函数->SAMPLE_SVP_NNIE_Rfcn_ViToVo()进行数据流分析
前面随笔给出了NNIE开发的基本知识，下面几篇随笔将着重于Mobilefacenet NNIE开发，实现mobilefacenet.wk的chip版本，并在Hi3559AV100上实现mobilefacenet网络功能，外接USB摄像头通过MPP平台输出至VO HDMI显示结果。下文是Hi3559AV100 NNIE开发（6）RFCN中实现关键线程函数->SAMPLE_SVP_NNIE_Rfcn_ViToVo()进行数据流分析，通过对线程函数分析，详细了解如何对.wk模型数据进行处理并弄清楚检测框绘制这些后处理的实现。
1、SAMPLE_SVP_NNIE_Rfcn_ViToVo()函数调用
首先给出SAMPLE_SVP_NNIE_Rfcn_ViToVo()函数的调用，为后续分析提供参照：
1 static pthread_t s_hNnieThread = 0; //全局定义
2
3 HI_CHAR acThreadName[16] = {0};//局部定义
4
5
6 /******************************************
7 Create work thread
8 ******************************************/
9 snprintf(acThreadName, 16, "NNIE_ViToVo");
10 prctl(PR_SET_NAME, (unsigned long)acThreadName, 0,0,0);
11 pthread_create(&s_hNnieThread, 0, SAMPLE_SVP_NNIE_Rfcn_ViToVo, NULL);
其中prctl函数的定义如下，其中PR_SET_NAME表示使用(char *) arg2所指向的位置中的值设置调用线程的名称。
1 int prctl(int option, unsigned long arg2, unsigned long arg3,
2 unsigned long arg4, unsigned long arg5);
2、SAMPLE_SVP_NNIE_Rfcn_ViToVo()函数实现具体分析
下面讲分析SAMPLE_SVP_NNIE_Rfcn_ViToVo(HI_VOID* pArgs)函数的内部实现，具体设计到5个函数，实现的功能已经注释出来，具体如下：
1 static HI_VOID* SAMPLE_SVP_NNIE_Rfcn_ViToVo(HI_VOID* pArgs)
2 {
3
4 .... //参数定义
5
6 while (HI_FALSE == s_bNnieStopSignal)
7 {
8 //用户从通道获取一帧处理完成的图像 通道1-输出stExtFrmInfo
9 s32Ret = HI_MPI_VPSS_GetChnFrame(s32VpssGrp,
10 as32VpssChn[1],
11 &stExtFrmInfo,
12 s32MilliSec);
13 ......
14
15 //用户从通道获取一帧处理完成的图像 通道0-输出stBaseFrmInfo
16 s32Ret = HI_MPI_VPSS_GetChnFrame(s32VpssGrp,
17 as32VpssChn[0],
18 &stBaseFrmInfo,
19 s32MilliSec);
20 ......
21
22 //关键处理函数
23 s32Ret = SAMPLE_SVP_NNIE_Rfcn_Proc(
24 pstParam,
25 pstSwParam,
26 &stExtFrmInfo,
27 stBaseFrmInfo.stVFrame.u32Width,
28 stBaseFrmInfo.stVFrame.u32Height);
29 ......
30
31 //Draw rect
32 s32Ret = SAMPLE_COMM_SVP_NNIE_FillRect(
33 &stBaseFrmInfo,
34 &(pstSwParam->stRect),
35 0x0000FF00); //绿色
36 ......
37
38 //将视频图像送入指定输出通道显示。
39 s32Ret = HI_MPI_VO_SendFrame(voLayer,
40 voChn,
41 &stBaseFrmInfo,
42 s32MilliSec);
43 ......
44
45 BASE_RELEASE:
46 s32Ret = HI_MPI_VPSS_ReleaseChnFrame(s32VpssGrp,as32VpssChn[0], &stBaseFrmInfo);
47 ......
48
49 EXT_RELEASE:
50 s32Ret = HI_MPI_VPSS_ReleaseChnFrame(s32VpssGrp,as32VpssChn[1], &stExtFrmInfo);
51 .......
52
53 }
54
55 return HI_NULL;
56 }
2.1、HI_MPI_VPSS_GetChnFrame的实现
下面给出HI_MPI_VPSS_GetChnFrame函数的参数调用与实现过程（其中VPSS双通道输出），具体功能为从通道获取一帧处理完成的图像：
1 HI_S32 s32VpssGrp = 0;
2 HI_S32 as32VpssChn[] = {VPSS_CHN0, VPSS_CHN1};
3 VIDEO_FRAME_INFO_S stBaseFrmInfo;
4 VIDEO_FRAME_INFO_S stExtFrmInfo;
5 HI_S32 s32MilliSec = 20000;
6
7 //用户从通道获取一帧处理完成的图像 通道1-输出stExtFrmInfo
8 s32Ret = HI_MPI_VPSS_GetChnFrame(s32VpssGrp,
9 as32VpssChn[1],
10 &stExtFrmInfo,
11 s32MilliSec);
12
13 //用户从通道获取一帧处理完成的图像 通道0-输出stBaseFrmInfo
14 s32Ret = HI_MPI_VPSS_GetChnFrame(s32VpssGrp,
15 as32VpssChn[0],
16 &stBaseFrmInfo,
17 s32MilliSec);
18
19 //函数定义
20 HI_S32 HI_MPI_VPSS_GetChnFrame(VPSS_GRP VpssGrp, VPSS_CHN VpssChn,
21 VIDEO_FRAME_INFO_S *pstVideoFrame, HI_S32 s32MilliSec);
2.2、SAMPLE_SVP_NNIE_Rfcn_Proc的实现-NNIE数据处理
SAMPLE_SVP_NNIE_Rfcn_Proc函数实现是整个RFCN NNIE数据处理过程的Key Point，检测加框等信息来源处，现给出函数参数及实现分析:
1 SAMPLE_SVP_NNIE_PARAM_S *pstParam;
2 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S *pstSwParam;
3
4 pstParam = &s_stRfcnNnieParam;
5 pstSwParam = &s_stRfcnSoftwareParam;
6 /*
7 s_stRfcnNnieParam及s_stRfcnSoftwareParam参数涉及前述操作
8
9 s_stRfcnNnieParam.pstModel = &s_stRfcnModel.stModel;
10 s_stRfcnSoftwareParam.apcRpnDataLayerName[0] = "rpn_cls_score";
11 s_stRfcnSoftwareParam.apcRpnDataLayerName[1] = "rpn_bbox_pred";
12 s32Ret = SAMPLE_SVP_NNIE_Rfcn_ParamInit(&stNnieCfg,
13 &s_stRfcnNnieParam,
14 &s_stRfcnSoftwareParam);
15 */
16
17
18 VIDEO_FRAME_INFO_S stBaseFrmInfo;
19 VIDEO_FRAME_INFO_S stExtFrmInfo;
20
21 //其中stBaseFrmInfo参数与stExtFrmInfo参数是经过下述函数输出得到
22 /*
23 s32Ret = HI_MPI_VPSS_GetChnFrame(s32VpssGrp,
24 as32VpssChn[1],
25 &stExtFrmInfo,
26 s32MilliSec);
27 s32Ret = HI_MPI_VPSS_GetChnFrame(s32VpssGrp,
28 as32VpssChn[0],
29 &stBaseFrmInfo,
30 s32MilliSec);
31 */
32
33
34 s32Ret = SAMPLE_SVP_NNIE_Rfcn_Proc(
35 pstParam,
36 pstSwParam,
37 &stExtFrmInfo,
38 stBaseFrmInfo.stVFrame.u32Width,
39 stBaseFrmInfo.stVFrame.u32Height);
随之给出SAMPLE_SVP_NNIE_Rfcn_Proc函数的定义及内部实现过程：
1 static HI_S32 SAMPLE_SVP_NNIE_Rfcn_Proc(
2 SAMPLE_SVP_NNIE_PARAM_S *pstParam,
3 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S *pstSwParam,
4 VIDEO_FRAME_INFO_S* pstExtFrmInfo,
5 HI_U32 u32BaseWidth,HI_U32 u32BaseHeight)
6 {
7
8 ......参数定义
9
10 s32Ret = SAMPLE_SVP_NNIE_Forward(pstParam,
11 &stInputDataIdx,
12 &stProcSegIdx,
13 HI_TRUE);
14
15 ......
16
17 /*RPN*/
18 s32Ret = SAMPLE_SVP_NNIE_Rfcn_Rpn(pstParam,
19 pstSwParam);
20
21
22 if(0 != pstSwParam->stRpnBbox.unShape.stWhc.u32Height)
23 {
24
25 s32Ret = SAMPLE_SVP_NNIE_ForwardWithBbox(
26 pstParam,
27 &stInputDataIdx,
28 &pstSwParam->stRpnBbox,
29 &stProcSegIdx,
30 HI_TRUE);
31 ......
32
33 s32Ret = SAMPLE_SVP_NNIE_ForwardWithBbox(
34 pstParam,
35 &stInputDataIdx,
36 &pstSwParam->stRpnBbox,
37 &stProcSegIdx,
38 HI_TRUE);
39 ......
40
41 s32Ret = SAMPLE_SVP_NNIE_Rfcn_GetResult(pstParam,
42 pstSwParam);
43
44 }
45 else
46 { ...... }
47 s32Ret = SAMPLE_SVP_NNIE_RoiToRect(
48 &(pstSwParam->stDstScore),
49 &(pstSwParam->stDstRoi),
50 &(pstSwParam->stClassRoiNum),
51 pstSwParam->af32ScoreThr,
52 HI_TRUE,
53 &(pstSwParam->stRect),
54 pstExtFrmInfo->stVFrame.u32Width,
55 pstExtFrmInfo->stVFrame.u32Height,
56 u32BaseWidth,
57 u32BaseHeight);
58
59 ......
60
61 return s32Ret;
62
63 }
2.2.1、SAMPLE_SVP_NNIE_Forward子函数分析
首先给出函数的调用及参数细节，便于分析函数功能：
1 其中在SAMPLE_SVP_NNIE_Rfcn_ViToVo函数中：
2 SAMPLE_SVP_NNIE_PARAM_S *pstParam;
3 pstParam = &s_stRfcnNnieParam; //此值传给SAMPLE_SVP_NNIE_Rfcn_Proc
4
5
6
7 static HI_S32 SAMPLE_SVP_NNIE_Rfcn_Proc(
8 SAMPLE_SVP_NNIE_PARAM_S *pstParam, /*这个参数传进来之后经过了SP420赋值然后送入
9 SAMPLE_SVP_NNIE_Forward*/
10 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S *pstSwParam,
11 VIDEO_FRAME_INFO_S* pstExtFrmInfo,
12 HI_U32 u32BaseWidth,HI_U32 u32BaseHeight)
13
14 ......
15
16 SAMPLE_SVP_NNIE_INPUT_DATA_INDEX_S stInputDataIdx = {0};
17 SAMPLE_SVP_NNIE_PROCESS_SEG_INDEX_S stProcSegIdx = {0};
18
19 stInputDataIdx.u32SegIdx = 0;
20 stInputDataIdx.u32NodeIdx = 0;
21
22 /*SP420*/
23 pstParam->astSegData[stInputDataIdx.u32SegIdx].astSrc[stInputDataIdx.u32NodeIdx].u64VirAddr = pstExtFrmInfo->stVFrame.u64VirAddr[0];
24 pstParam->astSegData[stInputDataIdx.u32SegIdx].astSrc[stInputDataIdx.u32NodeIdx].u64PhyAddr = pstExtFrmInfo->stVFrame.u64PhyAddr[0];
25 pstParam->astSegData[stInputDataIdx.u32SegIdx].astSrc[stInputDataIdx.u32NodeIdx].u32Stride = pstExtFrmInfo->stVFrame.u32Stride[0];
26
27 /*NNIE process 0-th seg*/
28 stProcSegIdx.u32SegIdx = 0;
29
30 /*NNIE process 0-th seg*/
31 stProcSegIdx.u32SegIdx = 0;
32 s32Ret = SAMPLE_SVP_NNIE_Forward(pstParam,
33 &stInputDataIdx,
34 &stProcSegIdx,
35 HI_TRUE);
36
37 ......
38
39 //函数定义
40 static HI_S32 SAMPLE_SVP_NNIE_Forward(
41 SAMPLE_SVP_NNIE_PARAM_S *pstNnieParam,
42 SAMPLE_SVP_NNIE_INPUT_DATA_INDEX_S* pstInputDataIdx,
43 SAMPLE_SVP_NNIE_PROCESS_SEG_INDEX_S* pstProcSegIdx,
44 HI_BOOL bInstant)
此函数如其名，主要实现了NNIE forward功能，下面给出调用具体函数：
1 /******************************************************************************
2 * function : NNIE Forward
3 ******************************************************************************/
4 static HI_S32 SAMPLE_SVP_NNIE_Forward(SAMPLE_SVP_NNIE_PARAM_S *pstNnieParam,
5 SAMPLE_SVP_NNIE_INPUT_DATA_INDEX_S* pstInputDataIdx,
6 SAMPLE_SVP_NNIE_PROCESS_SEG_INDEX_S* pstProcSegIdx,HI_BOOL bInstant)
7 {
8 ......
9
10 SAMPLE_COMM_SVP_FlushCache(
11 pstNnieParam->astForwardCtrl[pstProcSegIdx->u32SegIdx].stTskBuf.u64PhyAddr,
12 (HI_VOID *) pstNnieParam->astForwardCtrl[pstProcSegIdx->u32SegIdx].stTskBuf.u64VirAddr,
13 pstNnieParam->astForwardCtrl[pstProcSegIdx->u32SegIdx].stTskBuf.u32Size);
14
15 /*set input blob according to node name*/
16 if(pstInputDataIdx->u32SegIdx != pstProcSegIdx->u32SegIdx)
17 {
18 for(i = 0; i < pstNnieParam->pstModel->astSeg[pstProcSegIdx->u32SegIdx].u16SrcNum; i++)
19 {
20 ......
21 }
22 }
23
24 /*NNIE_Forward 多节点输入输出的 CNN 类型网络预测。
25 对输入样本(s)进行CNN预测，对对应样本(s)进行输出响应*/
26 s32Ret = HI_MPI_SVP_NNIE_Forward(
27 &hSvpNnieHandle,
28 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astSrc,
29 pstNnieParam->pstModel,
30 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst,
31 &pstNnieParam->astForwardCtrl[pstProcSegIdx->u32SegIdx],
32 bInstant);
33
34
35 if(bInstant)
36 {
37 /*Wait NNIE finish,,,,enNnieId 执行网络段的 NNIE 引擎 ID。 */
38 while(HI_ERR_SVP_NNIE_QUERY_TIMEOUT == (s32Ret = HI_MPI_SVP_NNIE_Query(pstNnieParam->astForwardCtrl[pstProcSegIdx->u32SegIdx].enNnieId,
39 hSvpNnieHandle, &bFinish, HI_TRUE)))
40 {
41 ......
42 }
43 }
44
45 bFinish = HI_FALSE;
46 for(i = 0; i < pstNnieParam->astForwardCtrl[pstProcSegIdx->u32SegIdx].u32DstNum; i++)
47 {
48 if(SVP_BLOB_TYPE_SEQ_S32 == pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].enType)
49 {
50 ......
51
52 SAMPLE_COMM_SVP_FlushCache(
53 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u64PhyAddr,
54 (HI_VOID *) pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u64VirAddr,
55 u32TotalStepNum*pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u32Stride);
56
57 }
58 else
59 {
60
61 SAMPLE_COMM_SVP_FlushCache(pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u64PhyAddr,
62 (HI_VOID *) pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u64VirAddr,
63 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u32Num*
64 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].unShape.stWhc.u32Chn*
65 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].unShape.stWhc.u32Height*
66 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u32Stride);
67 }
68 }
69
70 return s32Ret;
71 }
2.2.2、SAMPLE_SVP_NNIE_Rfcn_Rpn子函数分析
下面给出sample_svp_NNIE_Rfcn_Rpn子函数分析，此函数主要是用于rpn相关，下面给出参数调用及函数分析：
1 其中在SAMPLE_SVP_NNIE_Rfcn_ViToVo函数中：
2 SAMPLE_SVP_NNIE_PARAM_S *pstParam; //此值传给SAMPLE_SVP_NNIE_Rfcn_Proc
3 pstParam = &s_stRfcnNnieParam; //此值传给SAMPLE_SVP_NNIE_Rfcn_Proc
4
5 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S *pstSwParam;
6 pstSwParam = &s_stRfcnSoftwareParam;
7
8 static HI_S32 SAMPLE_SVP_NNIE_Rfcn_Proc(
9 SAMPLE_SVP_NNIE_PARAM_S *pstParam, /*这个参数传进来之后经过了SP420赋值然后送入
10 SAMPLE_SVP_NNIE_Forward*/
11 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S *pstSwParam, //直接传给SAMPLE_SVP_NNIE_Rfcn_Rpn函数
12 VIDEO_FRAME_INFO_S* pstExtFrmInfo,
13 HI_U32 u32BaseWidth,HI_U32 u32BaseHeight)
14
15 /*SP420*/
16 pstParam->astSegData[stInputDataIdx.u32SegIdx].astSrc[stInputDataIdx.u32NodeIdx].u64VirAddr = pstExtFrmInfo->stVFrame.u64VirAddr[0];
17 pstParam->astSegData[stInputDataIdx.u32SegIdx].astSrc[stInputDataIdx.u32NodeIdx].u64PhyAddr = pstExtFrmInfo->stVFrame.u64PhyAddr[0];
18 pstParam->astSegData[stInputDataIdx.u32SegIdx].astSrc[stInputDataIdx.u32NodeIdx].u32Stride = pstExtFrmInfo->stVFrame.u32Stride[0];
19
20 此后，pstParam参数先传入SAMPLE_SVP_NNIE_Forward函数进行处理，随后传入SAMPLE_SVP_NNIE_Rfcn_Rpn函数
21
22 /*RPN*/
23 s32Ret = SAMPLE_SVP_NNIE_Rfcn_Rpn(pstParam,
24 pstSwParam);
25
26 // 函数调用 ，用于used to do rpn
27 HI_S32 SAMPLE_SVP_NNIE_Rfcn_Rpn(
28 SAMPLE_SVP_NNIE_PARAM_S*pstNnieParam,
29 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S* pstSoftwareParam)
下面给出sample_svp_NNIE_Rfcn_Rpn子函数内部实现，此函数虽然传入两个参数，但是没有对pstNnieParam参数进行任何处理，完成的pstSoftwareParam结构体内大量参数的的处理 ，主要是调用了SVP_NNIE_Rpn函数与SAMPLE_COMM_SVP_FlushCache函数：
1 HI_S32 SAMPLE_SVP_NNIE_Rfcn_Rpn(SAMPLE_SVP_NNIE_PARAM_S*pstNnieParam,
2 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S* pstSoftwareParam)
3 {
4 HI_S32 s32Ret = HI_SUCCESS;
5 s32Ret = SVP_NNIE_Rpn(pstSoftwareParam->aps32Conv,pstSoftwareParam->u32NumRatioAnchors,
6 pstSoftwareParam->u32NumScaleAnchors,pstSoftwareParam->au32Scales,
7 pstSoftwareParam->au32Ratios,pstSoftwareParam->u32OriImHeight,
8 pstSoftwareParam->u32OriImWidth,pstSoftwareParam->au32ConvHeight,
9 pstSoftwareParam->au32ConvWidth,pstSoftwareParam->au32ConvChannel,
10 pstSoftwareParam->u32ConvStride,pstSoftwareParam->u32MaxRoiNum,
11 pstSoftwareParam->u32MinSize,pstSoftwareParam->u32SpatialScale,
12 pstSoftwareParam->u32NmsThresh,pstSoftwareParam->u32FilterThresh,
13 pstSoftwareParam->u32NumBeforeNms,(HI_U32*)pstSoftwareParam->stRpnTmpBuf.u64VirAddr,
14 (HI_S32*)pstSoftwareParam->stRpnBbox.u64VirAddr,
15 &pstSoftwareParam->stRpnBbox.unShape.stWhc.u32Height);
16 SAMPLE_COMM_SVP_FlushCache(pstSoftwareParam->stRpnBbox.u64PhyAddr,
17 (HI_VOID *) pstSoftwareParam->stRpnBbox.u64VirAddr,
18 pstSoftwareParam->stRpnBbox.u32Num*
19 pstSoftwareParam->stRpnBbox.unShape.stWhc.u32Chn*
20 pstSoftwareParam->stRpnBbox.unShape.stWhc.u32Height*
21 pstSoftwareParam->stRpnBbox.u32Stride);
22 SAMPLE_SVP_CHECK_EXPR_RET(HI_SUCCESS != s32Ret,s32Ret,SAMPLE_SVP_ERR_LEVEL_ERROR,
23 "Error,SVP_NNIE_Rpn failed!\n");
24 return s32Ret;
25 }
2.2.3、SAMPLE_SVP_NNIE_ForwardWithBbox子函数分析
完成前面几个函数后，通过if判断，当满足条件后执行SAMPLE_SVP_NNIE_ForwardWithBbox函数：
1 if(0 != pstSwParam->stRpnBbox.unShape.stWhc.u32Height)
否则不满足if条件的时候，将执行下面赋值语句：
1 for (i = 0; i < pstSwParam->stClassRoiNum.unShape.stWhc.u32Width; i++)
2 {
3 *(((HI_U32*)(HI_UL)pstSwParam->stClassRoiNum.u64VirAddr)+i) = 0;
4 }
而SAMPLE_SVP_NNIE_ForwardWithBbox执行了有两次，分别是对不同NNIE process x-th seg进行处理，具体如下：
1 其中在SAMPLE_SVP_NNIE_Rfcn_ViToVo函数中：
2 SAMPLE_SVP_NNIE_PARAM_S *pstParam; //此值传给SAMPLE_SVP_NNIE_Rfcn_Proc
3 pstParam = &s_stRfcnNnieParam; //此值传给SAMPLE_SVP_NNIE_Rfcn_Proc
4
5 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S *pstSwParam;
6 pstSwParam = &s_stRfcnSoftwareParam;
7
8 static HI_S32 SAMPLE_SVP_NNIE_Rfcn_Proc(
9 SAMPLE_SVP_NNIE_PARAM_S *pstParam, /*这个参数传进来之后经过了SP420赋值然后送入
10 SAMPLE_SVP_NNIE_Forward*/
11 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S *pstSwParam, /*直接传给SAMPLE_SVP_NNIE_Rfcn_Rpn函数
12 随后传给SAMPLE_SVP_NNIE_ForwardWithBbox函数*/
13 VIDEO_FRAME_INFO_S* pstExtFrmInfo,
14 HI_U32 u32BaseWidth,HI_U32 u32BaseHeight)
15
16 /*RPN*/
17 s32Ret = SAMPLE_SVP_NNIE_Rfcn_Rpn(pstParam,
18 pstSwParam); /*此函数完成pstSwParam的相关赋值，并
19 传给SAMPLE_SVP_NNIE_ForwardWithBbox函数*/
20
21
22 /*在SAMPLE_SVP_NNIE_ForwardWithBbox函数前面，已经有了下面参数的赋值，
23 并且传入至SAMPLE_SVP_NNIE_Forward函数*/
24 stInputDataIdx.u32SegIdx = 0;
25 stInputDataIdx.u32NodeIdx = 0;
26
27 s32Ret = SAMPLE_SVP_NNIE_Forward(pstParam,
28 &stInputDataIdx, //stInputDataIdx参数已经用于此函数中
29 &stProcSegIdx,
30 HI_TRUE);
31
32
33 //函数调用
34 /*NNIE process 1-th seg, the input data comes from 3-rd report node of 0-th seg,
35 the input roi comes from RPN results*/
36 stInputDataIdx.u32SegIdx = 0;
37 stInputDataIdx.u32NodeIdx = 3;
38
39 stProcSegIdx.u32SegIdx = 1;
40
41 s32Ret = SAMPLE_SVP_NNIE_ForwardWithBbox(
42 pstParam,
43 &stInputDataIdx,
44 &pstSwParam->stRpnBbox,
45 &stProcSegIdx,
46 HI_TRUE);
47
48
49 /*NNIE process 2-nd seg, the input data comes from 4-th report node of 0-th seg
50 the input roi comes from RPN results*/
51 stInputDataIdx.u32SegIdx = 0;
52 stInputDataIdx.u32NodeIdx = 4;
53
54 stProcSegIdx.u32SegIdx = 2;
55
56 s32Ret = SAMPLE_SVP_NNIE_ForwardWithBbox(
57 pstParam,
58 &stInputDataIdx,
59 &pstSwParam->stRpnBbox,
60 &stProcSegIdx,
61 HI_TRUE);
下面给出函数具体实现：
1 /******************************************************************************
2 * function : NNIE ForwardWithBbox
3 ******************************************************************************/
4 static HI_S32 SAMPLE_SVP_NNIE_ForwardWithBbox(
5 SAMPLE_SVP_NNIE_PARAM_S *pstNnieParam,
6 SAMPLE_SVP_NNIE_INPUT_DATA_INDEX_S* pstInputDataIdx,
7 SVP_SRC_BLOB_S astBbox[],
8 SAMPLE_SVP_NNIE_PROCESS_SEG_INDEX_S* pstProcSegIdx,
9 HI_BOOL bInstant)
10 {
11 ......
12
13 SAMPLE_COMM_SVP_FlushCache(pstNnieParam->astForwardWithBboxCtrl[pstProcSegIdx->u32SegIdx].stTskBuf.u64PhyAddr,
14 (HI_VOID *) pstNnieParam->astForwardWithBboxCtrl[pstProcSegIdx->u32SegIdx].stTskBuf.u64VirAddr,
15 pstNnieParam->astForwardWithBboxCtrl[pstProcSegIdx->u32SegIdx].stTskBuf.u32Size);
16
17 /*set input blob according to node name*/
18 if(pstInputDataIdx->u32SegIdx != pstProcSegIdx->u32SegIdx)
19 {
20 for(i = 0; i < pstNnieParam->pstModel->astSeg[pstProcSegIdx->u32SegIdx].u16SrcNum; i++)
21 {
22 for(j = 0; j < pstNnieParam->pstModel->astSeg[pstInputDataIdx->u32SegIdx].u16DstNum; j++)
23 {
24 ......
25 }
26 ......
27 }
28 }
29 /*NNIE_ForwardWithBbox*/
30 s32Ret = HI_MPI_SVP_NNIE_ForwardWithBbox(
31 &hSvpNnieHandle,
32 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astSrc,
33 astBbox,
34 pstNnieParam->pstModel, //网络类型只支持ROI/PSROI
35 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst,
36 &pstNnieParam->astForwardWithBboxCtrl[pstProcSegIdx->u32SegIdx],
37 bInstant);
38
39 ......
40
41 if(bInstant)
42 {
43 /*Wait NNIE finish*/
44 while(HI_ERR_SVP_NNIE_QUERY_TIMEOUT == (s32Ret = HI_MPI_SVP_NNIE_Query(pstNnieParam->astForwardWithBboxCtrl[pstProcSegIdx->u32SegIdx].enNnieId,
45 hSvpNnieHandle, &bFinish, HI_TRUE)))
46 {
47 ......
48 }
49 }
50
51 bFinish = HI_FALSE;
52
53
54 for(i = 0; i < pstNnieParam->astForwardWithBboxCtrl[pstProcSegIdx->u32SegIdx].u32DstNum; i++)
55 {
56 if(SVP_BLOB_TYPE_SEQ_S32 == pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].enType)
57 {
58 ......
59
60 SAMPLE_COMM_SVP_FlushCache(pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u64PhyAddr,
61 (HI_VOID *) pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u64VirAddr,
62 u32TotalStepNum*pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u32Stride);
63 }
64 else
65 {
66 SAMPLE_COMM_SVP_FlushCache(pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u64PhyAddr,
67 (HI_VOID *) pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u64VirAddr,
68 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u32Num*
69 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].unShape.stWhc.u32Chn*
70 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].unShape.stWhc.u32Height*
71 pstNnieParam->astSegData[pstProcSegIdx->u32SegIdx].astDst[i].u32Stride);
72 }
73 }
74
75 return s32Ret;
76 }
2.2.4、SAMPLE_SVP_NNIE_Rfcn_GetResult子函数分析
下一个子函数是获得NNIE Rfcn的结果，前提需要保证网络结构和输入数据保持一致，函数调用如下：
1 其中在SAMPLE_SVP_NNIE_Rfcn_ViToVo函数中：
2 SAMPLE_SVP_NNIE_PARAM_S *pstParam; //此值传给SAMPLE_SVP_NNIE_Rfcn_Proc
3 pstParam = &s_stRfcnNnieParam; //此值传给SAMPLE_SVP_NNIE_Rfcn_Proc
4
5 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S *pstSwParam;
6 pstSwParam = &s_stRfcnSoftwareParam;
7
8 static HI_S32 SAMPLE_SVP_NNIE_Rfcn_Proc(
9 SAMPLE_SVP_NNIE_PARAM_S *pstParam, /*这个参数传进来之后经过了SP420赋值然后送入
10 SAMPLE_SVP_NNIE_Forward*/
11 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S *pstSwParam, /*直接传给SAMPLE_SVP_NNIE_Rfcn_Rpn函数
12 随后传给SAMPLE_SVP_NNIE_ForwardWithBbox函数*/
13 VIDEO_FRAME_INFO_S* pstExtFrmInfo,
14 HI_U32 u32BaseWidth,HI_U32 u32BaseHeight)
15
16 pstParam->astSegData[stInputDataIdx.u32SegIdx].astSrc[stInputDataIdx.u32NodeIdx].u64VirAddr = pstExtFrmInfo->stVFrame.u64VirAddr[0];
17 pstParam->astSegData[stInputDataIdx.u32SegIdx].astSrc[stInputDataIdx.u32NodeIdx].u64PhyAddr = pstExtFrmInfo->stVFrame.u64PhyAddr[0];
18 pstParam->astSegData[stInputDataIdx.u32SegIdx].astSrc[stInputDataIdx.u32NodeIdx].u32Stride = pstExtFrmInfo->stVFrame.u32Stride[0];
19
20
21 s32Ret = SAMPLE_SVP_NNIE_Forward(pstParam, //参数调用
22 &stInputDataIdx,
23 &stProcSegIdx,
24 HI_TRUE);
25
26 /*RPN*/
27 s32Ret = SAMPLE_SVP_NNIE_Rfcn_Rpn(pstParam, //参数调用
28 pstSwParam); //参数调用
29
30
31 s32Ret = SAMPLE_SVP_NNIE_ForwardWithBbox(
32 pstParam, //参数调用
33 &stInputDataIdx,
34 &pstSwParam->stRpnBbox,
35 &stProcSegIdx,
36 HI_TRUE);
37
38
39
40 //函数调用
41
42 /*GetResult*/
43 /*if user has changed net struct, please make sure SAMPLE_SVP_NNIE_Rfcn_GetResult
44 function's input datas are correct*/
45 s32Ret = SAMPLE_SVP_NNIE_Rfcn_GetResult(pstParam,
46 pstSwParam);
47
48 //函数调用
49 HI_S32 SAMPLE_SVP_NNIE_Rfcn_GetResult(SAMPLE_SVP_NNIE_PARAM_S*pstNnieParam,
50 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S* pstSoftwareParam)
此函数作用是为了获取NNIE RFCN的结果，其核心是实现了SVP_NNIE_Rfcn_GetResult函数，具体如下：
1 HI_S32 SAMPLE_SVP_NNIE_Rfcn_GetResult(SAMPLE_SVP_NNIE_PARAM_S*pstNnieParam,
2 SAMPLE_SVP_NNIE_RFCN_SOFTWARE_PARAM_S* pstSoftwareParam)
3 {
4 HI_S32 s32Ret = HI_SUCCESS;
5 HI_U32 i = 0;
6 HI_S32* ps32Proposal = (HI_S32*)pstSoftwareParam->stRpnBbox.u64VirAddr;
7
8 ......
9
10 for(i = 0; i < pstSoftwareParam->stRpnBbox.unShape.stWhc.u32Height; i++)
11 {
12 *(ps32Proposal+SAMPLE_SVP_NNIE_COORDI_NUM*i) /= SAMPLE_SVP_NNIE_QUANT_BASE;
13 *(ps32Proposal+SAMPLE_SVP_NNIE_COORDI_NUM*i+1) /= SAMPLE_SVP_NNIE_QUANT_BASE;
14 *(ps32Proposal+SAMPLE_SVP_NNIE_COORDI_NUM*i+2) /= SAMPLE_SVP_NNIE_QUANT_BASE;
15 *(ps32Proposal+SAMPLE_SVP_NNIE_COORDI_NUM*i+3) /= SAMPLE_SVP_NNIE_QUANT_BASE;
16 }
17 //this function is used to get RFCN result
18 s32Ret = SVP_NNIE_Rfcn_GetResult(
19 (HI_S32*)pstNnieParam->astSegData[1].astDst[0].u64VirAddr,
20 pstNnieParam->astSegData[1].astDst[0].u32Stride,
21 (HI_S32*)pstNnieParam->astSegData[2].astDst[0].u64VirAddr,
22 pstNnieParam->astSegData[2].astDst[0].u32Stride,
23 (HI_S32*)pstSoftwareParam->stRpnBbox.u64VirAddr,
24 pstSoftwareParam->stRpnBbox.unShape.stWhc.u32Height,
25 pstSoftwareParam->au32ConfThresh,pstSoftwareParam->u32MaxRoiNum,
26 pstSoftwareParam->u32ClassNum,pstSoftwareParam->u32OriImWidth,
27 pstSoftwareParam->u32OriImHeight,pstSoftwareParam->u32ValidNmsThresh,
28 (HI_U32*)pstSoftwareParam->stGetResultTmpBuf.u64VirAddr,
29 (HI_S32*)pstSoftwareParam->stDstScore.u64VirAddr,
30 (HI_S32*)pstSoftwareParam->stDstRoi.u64VirAddr,
31 (HI_S32*)pstSoftwareParam->stClassRoiNum.u64VirAddr);
32 ......
33 return s32Ret;
34 }
2.2.5、SAMPLE_SVP_NNIE_RoiToRect子函数分析
SAMPLE_SVP_NNIE_Rfcn_Proc函数最后一个子函数为对ROI（感兴趣区域画框），RFNC对21类物体进行目标识别，具体调用及实现如下：
1 /*draw result, this sample has 21 classes:
2 class 0:background class 1:plane class 2:bicycle
3 class 3:bird class 4:boat class 5:bottle
4 class 6:bus class 7:car class 8:cat
5 class 9:chair class10:cow class11:diningtable
6 class 12:dog class13:horse class14:motorbike
7 class 15:person class16:pottedplant class17:sheep
8 class 18:sofa class19:train class20:tvmonitor*/
9 s32Ret = SAMPLE_SVP_NNIE_RoiToRect(
10 &(pstSwParam->stDstScore),
11 &(pstSwParam->stDstRoi),
12 &(pstSwParam->stClassRoiNum),
13 pstSwParam->af32ScoreThr,
14 HI_TRUE,
15 &(pstSwParam->stRect),
16 pstExtFrmInfo->stVFrame.u32Width,
17 pstExtFrmInfo->stVFrame.u32Height,
18 u32BaseWidth,
19 u32BaseHeight);
20
21 /******************************************************************************
22 * function : roi to rect
23 ******************************************************************************/
24 HI_S32 SAMPLE_SVP_NNIE_RoiToRect(SVP_BLOB_S *pstDstScore,
25 SVP_BLOB_S *pstDstRoi, SVP_BLOB_S *pstClassRoiNum, HI_FLOAT *paf32ScoreThr,
26 HI_BOOL bRmBg,SAMPLE_SVP_NNIE_RECT_ARRAY_S *pstRect,
27 HI_U32 u32SrcWidth, HI_U32 u32SrcHeight,HI_U32 u32DstWidth,HI_U32 u32DstHeight)
28 {
29 HI_U32 i = 0, j = 0;
30 HI_U32 u32RoiNumBias = 0;
31 HI_U32 u32ScoreBias = 0;
32 HI_U32 u32BboxBias = 0;
33 HI_FLOAT f32Score = 0.0f;
34 HI_S32* ps32Score = (HI_S32*)pstDstScore->u64VirAddr;
35 HI_S32* ps32Roi = (HI_S32*)pstDstRoi->u64VirAddr;
36 HI_S32* ps32ClassRoiNum = (HI_S32*)pstClassRoiNum->u64VirAddr;
37 HI_U32 u32ClassNum = pstClassRoiNum->unShape.stWhc.u32Width;
38 HI_U32 u32RoiNumTmp = 0;
39
40 .......
41
42 pstRect->u32TotalNum = 0;
43 pstRect->u32ClsNum = u32ClassNum;
44 if (bRmBg)
45 {
46 pstRect->au32RoiNum[0] = 0;
47 u32RoiNumBias += ps32ClassRoiNum[0];
48 for (i = 1; i < u32ClassNum; i++)
49 {
50 u32ScoreBias = u32RoiNumBias;
51 u32BboxBias = u32RoiNumBias * SAMPLE_SVP_NNIE_COORDI_NUM;
52 u32RoiNumTmp = 0;
53 /*if the confidence score greater than result thresh, the result will be drawed*/
54 if(((HI_FLOAT)ps32Score[u32ScoreBias] / SAMPLE_SVP_NNIE_QUANT_BASE >=
55 paf32ScoreThr[i]) && (ps32ClassRoiNum[i] != 0))
56 {
57 for (j = 0; j < (HI_U32)ps32ClassRoiNum[i]; j++)
58 {
59 /*Score is descend order*/
60 f32Score = (HI_FLOAT)ps32Score[u32ScoreBias + j] / SAMPLE_SVP_NNIE_QUANT_BASE;
61 if ((f32Score < paf32ScoreThr[i]) || (u32RoiNumTmp >= SAMPLE_SVP_NNIE_MAX_ROI_NUM_OF_CLASS))
62 {
63 break;
64 }
65
66 pstRect->astRect[i][u32RoiNumTmp].astPoint[0].s32X = (HI_U32)((HI_FLOAT)ps32Roi[u32BboxBias + j*SAMPLE_SVP_NNIE_COORDI_NUM] / (HI_FLOAT)u32SrcWidth * (HI_FLOAT)u32DstWidth) & (~1) ;
67 pstRect->astRect[i][u32RoiNumTmp].astPoint[0].s32Y = (HI_U32)((HI_FLOAT)ps32Roi[u32BboxBias + j*SAMPLE_SVP_NNIE_COORDI_NUM + 1] / (HI_FLOAT)u32SrcHeight * (HI_FLOAT)u32DstHeight) & (~1);
68
69 pstRect->astRect[i][u32RoiNumTmp].astPoint[1].s32X = (HI_U32)((HI_FLOAT)ps32Roi[u32BboxBias + j*SAMPLE_SVP_NNIE_COORDI_NUM + 2]/ (HI_FLOAT)u32SrcWidth * (HI_FLOAT)u32DstWidth) & (~1);
70 pstRect->astRect[i][u32RoiNumTmp].astPoint[1].s32Y = pstRect->astRect[i][u32RoiNumTmp].astPoint[0].s32Y;
71
72 pstRect->astRect[i][u32RoiNumTmp].astPoint[2].s32X = pstRect->astRect[i][u32RoiNumTmp].astPoint[1].s32X;
73 pstRect->astRect[i][u32RoiNumTmp].astPoint[2].s32Y = (HI_U32)((HI_FLOAT)ps32Roi[u32BboxBias + j*SAMPLE_SVP_NNIE_COORDI_NUM + 3] / (HI_FLOAT)u32SrcHeight * (HI_FLOAT)u32DstHeight) & (~1);
74
75 pstRect->astRect[i][u32RoiNumTmp].astPoint[3].s32X = pstRect->astRect[i][u32RoiNumTmp].astPoint[0].s32X;
76 pstRect->astRect[i][u32RoiNumTmp].astPoint[3].s32Y = pstRect->astRect[i][u32RoiNumTmp].astPoint[2].s32Y;
77
78 u32RoiNumTmp++;
79 }
80
81 }
82
83 pstRect->au32RoiNum[i] = u32RoiNumTmp;
84 pstRect->u32TotalNum += u32RoiNumTmp;
85 u32RoiNumBias += ps32ClassRoiNum[i];
86 }
87
88 }
89 return HI_SUCCESS;
90 }
3、SAMPLE_COMM_SVP_NNIE_FillRect函数分析
SAMPLE_COMM_SVP_NNIE_FillRect主要是配合VGS实现画框功能，具体调用和实现如下，函数功能已由注释给出：
1 //Draw rect
2 s32Ret = SAMPLE_COMM_SVP_NNIE_FillRect(
3 &stBaseFrmInfo,
4 &(pstSwParam->stRect),
5 0x0000FF00); //绿色
6
7 HI_S32 SAMPLE_COMM_SVP_NNIE_FillRect(
8 VIDEO_FRAME_INFO_S *pstFrmInfo,
9 SAMPLE_SVP_NNIE_RECT_ARRAY_S* pstRect,
10 HI_U32 u32Color)
11 {
12 VGS_HANDLE VgsHandle = -1;
13 HI_S32 s32Ret = HI_SUCCESS;
14 HI_U32 i,j;
15 VGS_TASK_ATTR_S stVgsTask;//定义 VGS task 的属性
16 VGS_ADD_COVER_S stVgsAddCover;//定义 VGS 上 COVER 的配置
17 static HI_U32 u32Frm = 0;
18 u32Frm++;
19 if (0 == pstRect->u32TotalNum)
20 {
21 return s32Ret;
22 }
23 s32Ret = HI_MPI_VGS_BeginJob(&VgsHandle); //启动一个 job。
24 if (s32Ret != HI_SUCCESS)
25 {
26 ......
27 return s32Ret;
28 }
29
30 memcpy(&stVgsTask.stImgIn, pstFrmInfo, sizeof(VIDEO_FRAME_INFO_S));
31 memcpy(&stVgsTask.stImgOut, pstFrmInfo, sizeof(VIDEO_FRAME_INFO_S));
32
33 stVgsAddCover.enCoverType = COVER_QUAD_RANGLE;//任意四边形COVER
34 stVgsAddCover.u32Color = u32Color; //RGB888
35 stVgsAddCover.stQuadRangle.bSolid = HI_FALSE; //空心 COVER
36 stVgsAddCover.stQuadRangle.u32Thick = 2; //2 像素对齐
37
38 for (i = 0; i < pstRect->u32ClsNum; i++)
39 {
40 for (j = 0; j < pstRect->au32RoiNum[i]; j++)
41 {
42 memcpy(stVgsAddCover.stQuadRangle.stPoint, pstRect->astRect[i][j].astPoint, sizeof(pstRect->astRect[i][j].astPoint));
43
44 //做 COVER 任务时，输入输出图像为同一块 buffer
45 //往一个已经启动的 job 里添加打 COVER task。 task属性必须满足VGS的能力。
46 s32Ret = HI_MPI_VGS_AddCoverTask(VgsHandle, &stVgsTask, &stVgsAddCover);
47 if (s32Ret != HI_SUCCESS)
48 {
49 SAMPLE_PRT("HI_MPI_VGS_AddCoverTask fail,Error(%#x)\n", s32Ret);
50 HI_MPI_VGS_CancelJob(VgsHandle);
51 return s32Ret;
52 }
53
54 }
55
56 }
57 //提交一个 job。
58 s32Ret = HI_MPI_VGS_EndJob(VgsHandle);
59 if (s32Ret != HI_SUCCESS)
60 {
61 SAMPLE_PRT("HI_MPI_VGS_EndJob fail,Error(%#x)\n", s32Ret);
62 HI_MPI_VGS_CancelJob(VgsHandle);
63 return s32Ret;
64 }
65
66 return s32Ret;
4、HI_MPI_VO_SendFrame函数分析
SAMPLE_SVP_NNIE_Rfcn_ViToVo线程函数执行的最后一个函数HI_MPI_VO_SendFrame，函数作用是将视频图像送入指定输出通道显示，具体调用如下：
1 s32Ret = HI_MPI_VO_SendFrame(voLayer,
2 voChn,
3 &stBaseFrmInfo,
4 s32MilliSec);
Hi3559AV100 NNIE开发（6）RFCN中NNIE实现关键线程函数->SAMPLE_SVP_NNIE_Rfcn_ViToVo()进行数据流分析的更多相关文章
- 基于Hi3559AV100的SVP(NNIE)开发整体流程
在之后的hi3559AV100板载开发中,除了走通V4L2->VDEC->VPSS->VO(HDMI)输出,还有需要进行神经网络的开发学习,进行如face detection的开发等 ...
- Hi3559AV100 NNIE开发（2）-RFCN(.wk)LoadModel及NNIE Init函数运行过程分析
之后随笔将更多笔墨着重于NNIE开发系列,下文是关于Hi3559AV100 NNIE开发(2)-RFCN(.wk)LoadModel及NNIE Init函数运行过程分析,通过对LoadModel函数及 ...
- Hi3559AV100 NNIE开发（4）mobilefacenet.cfg参数配置挖坑解决与SVP_NNIE_Cnn实现分析
前面随笔给出了NNIE开发的基本知识,下面几篇随笔将着重于Mobilefacenet NNIE开发,实现mobilefacenet.wk的chip版本,并在Hi3559AV100上实现mobilefa ...
- Hi3359AV100 NNIE开发（1）-RFCN demo LoadModel函数与参数解析
之后随笔将更多笔墨着重于NNIE开发系列,下文是关于Hi3359AV100 NNIE开发(1)-RFCN demo LoadModel函数与参数解析,通过对LoadModel函数的解析,能够很好理解. ...
- Hi3559AV100 NNIE开发（3）RuyiStudio软件 .wk文件生成过程-mobilefacenet.cfg的参数配置
之后随笔将更多笔墨着重于NNIE开发系列,下文是关于Hi3559AV100 NNIE开发(3)RuyiStudio软件 .wk文件生成过程-mobilefacenet.cfg的参数配置,目前项目需要对 ...
- Hi3559AV100 NNIE开发（5）mobilefacenet.wk仿真成功量化及与CNN_convert_bin_and_print_featuremap.py输出中间层数据对比过程
前面随笔给出了NNIE开发的基本知识,下面几篇随笔将着重于Mobilefacenet NNIE开发,实现mobilefacenet.wk的chip版本,并在Hi3559AV100上实现mobilefa ...
- Hi3559AV100 NNIE开发（7） Ruyistudio 输出mobileface_func.wk与板载运行mobileface_chip.wk输出中间层数据对比
前面随笔讲了关于NNIE的整个开发流程,并给出了Hi3559AV100 NNIE开发(5)mobilefacenet.wk仿真成功量化及与CNN_convert_bin_and_print_featu ...
- 前端开发：Javascript中的数组，常用方法解析
前端开发:Javascript中的数组,常用方法解析 前言 Array是Javascript构成的一个重要的部分,它可以用来存储字符串.对象.函数.Number,它是非常强大的.因此深入了解Array ...
- 分享 Ionic 开发 Hybrid App 中遇到的问题以及后期发布 iOS/Android 的方方面面
此篇文章主要整理了最近在使用 Ionic 开发 Hybrid App 过程中遇到的一些疑难点以及后期发布生成 iOS 和 Android 版本过程中的种种问题. 文章目录 Ionic 简介和项目需求介 ...
随机推荐
- Linux Bash Script loop
Linux Bash Script loop shell 编程之流程控制 for 循环.while 循环和 until 循环 for var in item1 item2 ... itemN do c ...
- input composition event All In One
input composition event All In One input event compositionStart & compositionEnd & compositi ...
- WebAR in Action
WebAR in Action WebAR (Web + AR) 增强现实 https://developer.mozilla.org/en-US/docs/Web/API/WebAR_API Web ...
- 如何用 js 实现一个 sleep 函数
如何用 js 实现一个 sleep 函数 原理 实现方式 总结 refs js sleep xgqfrms 2012-2020 www.cnblogs.com 发布文章使用:只允许注册用户才可以访问!
- switchable css dark theme in js & html custom element
switchable css dark theme in js & html custom element dark theme / dark mode https://codepen.io/ ...
- css & auto height & overflow: hidden;
css & auto height & overflow: hidden; {overflow: hidden; height: 100%;} is the panacea! {溢出: ...
- HTML5 stream video player
HTML5 stream video player Aliplayer https://player.alicdn.com/aliplayer/index.html https://help.aliy ...
- wxPython 创建基本窗口
$ pip install wxPython import wx class MyFrame(wx.Frame): def __init__(self, parent, title): super(M ...
- 「NGK每日快讯」2021.2.2日NGK公链第91期官方快讯!
- BGV再掀DeFi投资热潮，NGK全球启动大会圆满落幕
此次全球启动大会的主题为"BGV再掀DeFi投资热潮,后市发展如何". 首先发言的是NGK灵石团队首席技术官STEPHEN先生,他先是对出席此次大会的嘉宾.到场的媒体记者以及NGK ...