xfcvDataMovers

xfcvDataMovers class object takes input some simple parameters from users and provides a simple data transaction API where user does not have to bother about the complexity. Moreover it provides a template parameter using which application can switch from PL based data movement to GMIO based (and vice versa) seamlessly. For more details please refer xfcvDataMovers.

Class Definition

template <DataMoverKind KIND,
          typename DATA_TYPE,
          int TILE_HEIGHT_MAX,
          int TILE_WIDTH_MAX,
          int AIE_VECTORIZATION_FACTOR,
          int CORES = 1,
          int PL_AXI_BITWIDTH = 32,
          bool USE_GMIO = false>
class xfcvDataMovers {
    //Tiler  constructor
    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == TILER)>::type* = nullptr>
    xfcvDataMovers(uint16_t overlapH, uint16_t overlapV);

    //Stitcher constructor
    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == STITCHER)>::type* = nullptr>
    xfcvDataMovers();

    //Meta data computation
    void compute_metadata(const cv::Size& img_size);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == TILER)>::type* = nullptr>
    std::array<uint16_t, 2> host2aie_nb(cv::Mat& img, xrtBufferHandle imgHndl = nullptr);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == TILER)>::type* = nullptr>
    std::array<uint16_t, 2> host2aie_nb(xrtBufferHandle imgHndl, const cv::Size& size);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == STITCHER)>::type* = nullptr>
    void aie2host_nb(cv::Mat& img, std::array<uint16_t, 2> tiles, xrtBufferHandle imgHndl = nullptr);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == STITCHER)>::type* = nullptr>
    void aie2host_nb(xrtBufferHandle imgHndl, const cv::Size& size, std::array<uint16_t, 2> tiles);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == TILER)>::type* = nullptr>
    void wait();

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == STITCHER)>::type* = nullptr>
    void wait();;
};

//GMIO class specialization
template <DataMoverKind KIND,
          typename DATA_TYPE,
          int TILE_HEIGHT_MAX,
          int TILE_WIDTH_MAX,
          int AIE_VECTORIZATION_FACTOR,
          int CORES>
class xfcvDataMovers<KIND, DATA_TYPE, TILE_HEIGHT_MAX, TILE_WIDTH_MAX, AIE_VECTORIZATION_FACTOR, CORES, 0, true> {
    //Tiler  constructor
    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == TILER)>::type* = nullptr>
    xfcvDataMovers(uint16_t overlapH, uint16_t overlapV);

    //Stitcher constructor
    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == STITCHER)>::type* = nullptr>
    xfcvDataMovers();

    //Compute meta data
    void compute_metadata(const cv::Size& img_size);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == TILER)>::type* = nullptr>
    std::array<uint16_t, 2> host2aie_nb(DATA_TYPE* img_data, const cv::Size& img_size, std::array<std::string, CORES> portNames);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == TILER)>::type* = nullptr>
    std::array<uint16_t, 2> host2aie_nb(cv::Mat& img, std::array<std::string, CORES> portNames);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == STITCHER)>::type* = nullptr>
    void aie2host_nb(DATA_TYPE* img_data, const cv::Size& img_size, std::array<uint16_t, 2> tiles, std::array<std::string, CORES> portNames);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == STITCHER)>::type* = nullptr>
    void aie2host_nb(cv::Mat& img, std::array<uint16_t, 2> tiles, std::array<std::string, CORES> portNames);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == TILER)>::type* = nullptr>
    std::array<uint16_t, 2> host2aie(cv::Mat& img, std::array<std::string, CORES> portNames);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == TILER)>::type* = nullptr>
    std::array<uint16_t, 2> host2aie(DATA_TYPE* img_data, const cv::Size& img_size, std::array<std::string, CORES> portNames);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == STITCHER)>::type* = nullptr>
    void aie2host(cv::Mat& img, std::array<uint16_t, 2> tiles, std::array<std::string, CORES> portNames);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == STITCHER)>::type* = nullptr>
    void aie2host(DATA_TYPE* img_data, const cv::Size& img_size, std::array<uint16_t, 2> tiles, std::array<std::string, CORES> portNames);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == TILER)>::type* = nullptr>
    void wait(std::array<std::string, CORES> portNames);

    template <DataMoverKind _t = KIND, typename std::enable_if<(_t == STITCHER)>::type* = nullptr>
    void wait(std::array<std::string, CORES> portNames);
};

Table xF::xfcvDataMovers Member Function Descriptions

Member Functions	Description
xfcvDataMovers(uint16_t overlapH, uint16_t overlapV)	Tiler constructor using horizontal and vertical overlap sizes
xfcvDataMovers()	Stitcher constructor
host2aie_nb(cv::Mat& img, xrtBufferHandle imgHndl = nullptr)	Host to AIE non blocking transaction using input image.
host2aie_nb(xrtBufferHandle imgHndl, const cv::Size& size)	Host to AIE non blocking transaction using XRT allocated buffer handle and image size
aie2host_nb(cv::Mat& img, std::array<uint16_t, 2> tiles, xrtBufferHandle imgHndl = nullptr)	AIE to Host non blocking transaction using input image and {tile rows, tile cols} array
aie2host_nb(xrtBufferHandle imgHndl, const cv::Size& size, std::array<uint16_t, 2> tiles)	AIE to Host non blocking transaction using XRT allocated buffer handle and image size
wait()	Wait for transaction to complete

Note

If XRT mapped buffer handle is associated with image it can also be passed to imgHndl argument avoid copy

Note

Parameter tiles can be obtained from tiler data transfer API host2aie_nb

Table xF::xfcvDataMovers Member Function Descriptions (GMIO specialization)

Member Functions	Description
xfcvDataMovers(uint16_t overlapH, uint16_t overlapV)	Tiler constructor using horizontal and vertical overlap sizes
xfcvDataMovers()	Stitcher constructor
host2aie_nb(cv::Mat& img, std::array<std::string, CORES> portNames)	Host to AIE non blocking transaction using input image.
host2aie_nb(DATA_TYPE* img_data, const cv::Size& size, std::array<std::string, CORES> portNames)	Host to AIE non blocking transaction using image data pointer and image size
aie2host_nb(cv::Mat& img, std::array<std::string, CORES> portNames)	AIE to Host non blocking transaction using input image.
aie2host_nb(DATA_TYPE* img_data, const cv::Size& size, std::array<std::string, CORES> portNames)	AIE to Host non blocking transaction using image data pointer and image size
host2aie(cv::Mat& img, std::array<std::string, CORES> portNames)	Host to AIE blocking transaction using input image.
host2aie(DATA_TYPE* img_data, const cv::Size& size, std::array<std::string, CORES> portNames)	Host to AIE blocking transaction using image data pointer and image size
aie2host(cv::Mat& img, std::array<std::string, CORES> portNames)	AIE to Host blocking transaction using input image.
aie2host(DATA_TYPE* img_data, const cv::Size& size, std::array<std::string, CORES> portNames)	AIE to Host blocking transaction using image data pointer and image size
wait()	Wait for transaction to complete

Note

Argument portNames correspond GMIO port declared as part of platform specification

Vitis Vision AIE Library Functions API list with performance estimates

Frames per second (FPS) measured from host-code and includes data-transfer latencies and AIEngine™ kernel latencies. Measurements done on VCK190 evaluation boards and use only one AIE core.

Table AIE Library Functions API list with performance estimates

Function(xf::cv::aie)	Performance (FPS) with PL Data-movers(Full HD)	Performance (FPS) with PL Data-movers (4K)	Performance (FPS) with GMIO Data-movers(Full HD)	Performance (FPS) with GMIO Data-movers (4K)
absolutedifference	284	80	128	50
accumulate	280	79	137	48
accumulateweighted	281	75	111	40
addweighted	358	100	129	38
convertScaleAbs	406	106	214	57
erode	250	65	131	41
filter2D	250	67	157	47
gainControl	405	103	192	60
gaussian	249	66	179	52
laplacian	250	66	150	46
pixel_wise_mul	362	102	170	51
threshold	403	105	251	68
zero function	405	103	204	66