实验平台：Zedboard(XC7Z020-CLG484-1)
开发工具：Vivado2019.2开发套件
（由于jpg、png等图片格式涉及图像压缩算法，因此在zynq平台读取此类图片较为困难，故目前仅支持bmp图片的读取）
BMP(全称Bitmap)是Window操作系统中的标准图像文件格式，可以分成两类：设备相关位图(DDB)和设备无关位图(DIB)，使用非常广。它采用位映射存储格式，除了图像深度可选以外，不采用其他任何压缩，因此，BMP文件所占用的空间很大。BMP文件的图像深度可选1bit、4bit、8bit及24bit。BMP文件存储数据时，图像的扫描方式是按从左到右、从下到上的顺序。 由于BMP文件格式是Windows环境中交换与图有关的数据的一种标准，因此在Windows环境中运行的图形图像软件都支持BMP图像格式。
BMP文件格式由文件头和原始位图数据Raw Bitmap Data构成（详见https://en.wikipedia.org/wiki/BMP_file_format）。
位图格式的文件头长度可变，而且其中参数繁多。但通常情况下bmp格式图片的文件头长度均为54字节，其中包括14字节的Bitmap文件头以及40字节的DIB（Device Independent Bitmap）数据头，或称位图信息数据头（BItmap Information Header）。
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位图文件头 Bitmap File Header (14 bytes)
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位图信息数据头 DIB Header (54 bytes)
图像数据块从文件头中起始偏移量字段所指出的位置开始，其中存放着位图图像的数据，数据格式由图像参数信息块中的压缩方式选项的取值决定。操作图像数据块时，需要注意： 当压缩方式为RGB时，图像数据块以“行”为单位双字（4字节）对齐，如1行像素的字节数不为4的倍数，则进行填充，直至4字节对齐为止（一般填充0）。
参考资料：UG902 (v2018.2) July 2, 2018
HLS视频库(包含在头文件hls_video.h)中包含的视频处理函数与现有的OpenCV功能兼容，名称类似。它们不会直接取代现有的OpenCV视频库函数。视频处理函数使用一种数据类型hls::Mat。这种数据类型允许将函数作为高性能硬件进行综合和实现。
在HLS视频库中提供了三种类型的函数：
- OpenCV Interface Functions
实现在AXI4流式数据类型和标准的OpenCV数据类型之间的转换。 - AXI Interface Functions
实现在视频数据和hls::Mat数据类型之间的转换。 - Video Processing Functions
兼容标准的OpenCV函数，以操作和处理视频图像。这些函数使用hls::Mat数据类型，并可由Vivado HLS综合。Vivado HLS视频库中包含的视频处理函数是专门用于操作视频图像的。这些函数大多是为了加速相应的OpenCV函数而设计的。
下表总结了HLS视频库中提供的函数：
| Function Type | Function | Description |
|---|---|---|
| OpenCV Interface | AXIvideo2cvMat | Converts data from AXI4 video stream (hls::stream) format to OpenCV cv::Mat format |
| OpenCV Interface | AXIvideo2CvMat | Converts data from AXI4 video stream (hls::stream) format to OpenCV CvMat format2 |
| OpenCV Interface | AXIvideo2IplImage | Converts data from AXI4 video stream (hls::stream) format to OpenCV IplImage format |
| OpenCV Interface | cvMat2AXIvideo | Converts data from OpenCV cv::Mat format to AXI4 video stream (hls::stream) format |
| OpenCV Interface | CvMat2AXIvideo | Converts data from OpenCV CvMat format to AXI4 video stream (hls::stream) format |
| OpenCV Interface | cvMat2hlsMat | Converts data from OpenCV cv::Mat format to hls::Mat format |
| OpenCV Interface | CvMat2hlsMat | Converts data from OpenCV CvMat format to hls::Mat format |
| OpenCV Interface | CvMat2hlsWindow | Converts data from OpenCV CvMat format to hls::Window format |
| OpenCV Interface | hlsMat2cvMat | Converts data from hls::Mat format to OpenCV cv::Mat format |
| OpenCV Interface | hlsMat2CvMat | Converts data from hls::Mat format to OpenCV CvMat format |
| OpenCV Interface | hlsMat2IplImage | Converts data from hls::Mat format to OpenCV IplImage format |
| OpenCV Interface | hlsWindow2CvMat | Converts data from hls::Window format to OpenCV CvMat format |
| OpenCV Interface | IplImage2AXIvideo | Converts data from OpenCV IplImage format to AXI4 video stream (hls::stream) format |
| OpenCV Interface | IplImage2hlsMat | Converts data from OpenCV IplImage format to hls::Mat format |
| AXI4-Interface | AXIvideo2Mat | Converts image data stored in hls::Mat format to an AXI4 video stream (hls::stream) format |
| AXI4-Interface | Mat2AXIvideo | Converts image data stored in AXI4 video stream (hls::stream) format to an image of hls::Mat format |
| AXI4-Interface | Array2Mat | Converts image data stored in an array to an image of hls::Mat format. |
| AXI4-Interface | Array2Mat | Converts image data stored hls::Mat format to an array. |
| Video Processing | AbsDiff | Computes the absolute difference between two input images src1 and src2 and saves the result in dst |
| Video Processing | AddS | Computes the per-element sum of an image src and a scalar scl |
| Video Processing | AddWeighted | Computes the weighted per-element sum of two image src1 and src2 |
| Video Processing | And | Calculates the per-element bitwise logical conjunction of two images src1 and src2 |
| Video Processing | Avg | Calculates an average of elements in image src |
| Video Processing | AvgSdv | Calculates an average of elements in image src |
| Video Processing | Cmp | Performs the per-element comparison of two input images src1 and src2 |
| Video Processing | CmpS | Performs the comparison between the elements of input images src and the input value and saves the result in dst |
| Video Processing | CornerHarris | This function implements a Harris edge/corner detector |
| Video Processing | CvtColor | Converts a color image from or to a grayscale image |
| Video Processing | Dilate | Dilates the image src using the specified structuring element constructed within the kernel |
| Video Processing | Duplicate | Copies the input image src to two output images dst1 and dst2, for divergent point of two datapaths |
| Video Processing | EqualizeHist | Computes a histogram of each frame and uses it to normalize the range of the following frame |
| Video Processing | Erode | Erodes the image src using the specified structuring element constructed within kernel |
| Video Processing | FASTX | Implements the FAST corner detector, generating either a mask of corners, or an array of coordinates |
| Video Processing | Filter2D | Applies an arbitrary linear filter to the image src using the specified kernel |
| Video Processing | GaussianBlur | Applies a normalized 2D Gaussian Blur filter to the input |
| Video Processing | Harris | This function implements a Harris edge or corner detector |
| Video Processing | HoughLines2 | Implements the Hough line transform |
| Video Processing | Integral | Implements the computation of an integral image |
| Video Processing | InitUndistortRectifyMap | Generates map1 and map2, based on a set of parameters, where map1 and map2 are suitable inputs for hls::Remap() |
| Video Processing | Max | Calculates per-element maximum of two input images src1 and src2 and saves the result in dst |
| Video Processing | MaxS | Calculates the maximum between the elements of input images src and the input value and saves the result in dst |
| Video Processing | Mean | Calculates an average of elements in image src, and return the value of first channel of result scalar |
| Video Processing | Merge | Composes a multichannel image dst from several single-channel images |
| Video Processing | Min | Calculates per-element minimum of two input images src1 and src2 and saves the result in dst |
| Video Processing | MinMaxLoc | Finds the global minimum and maximum and their locations in input image src |
| Video Processing | MinS | Calculates the minimum between the elements of input images src and the input value and saves the result in dst |
| Video Processing | Mul | Calculates the per-element product of two input images src1 and src2 |
| Video Processing | Not | Performs per-element bitwise inversion of image src |
| Video Processing | PaintMask | Each pixel of the destination image is either set to color (if mask is not zero) or the corresponding pixel from the input image |
| Video Processing | PyrDown | Blurs the image and then reduces the size by a factor of 2. |
| Video Processing | PyrUp | Upsamples the image by a factor of 2 and then blurs the image. |
| Video Processing | Range | Sets all value in image src by the following rule and return the result as image dst:dst(I) = (end-start)x(ixdst.cols+j)/(dst.rows*dst.cols) |
| Video Processing | Remap | Remaps the source image src to the destination image dst according to the given remapping |
| Video Processing | Reduce | Reduces 2D image src along dimension dim to a vector dst |
| Video Processing | Resize | Resizes the input image to the size of the output image using bilinear interpolation |
| Video Processing | Set | Sets elements in image src to a given scalar value scl |
| Video Processing | Scale | Converts an input image src with optional linear transformation |
| Video Processing | Sobel | Computes a horizontal or vertical Sobel filter, returning an estimate of the horizontal or vertical derivative. |
| Video Processing | Split | Divides a multichannel image src to several single-channel images |
| Video Processing | SubRS | Computes the differences between scalar value scl and elements of image src |
| Video Processing | SubS | Computes the differences between elements of image src and scalar value scl |
| Video Processing | Sum | Sums the elements of an image |
| Video Processing | Threshold | Performs a fixed-level threshold to each element in a single-channel image |
| Video Processing | Zero | Sets elements in image src to 0 |
- 创建HLS工程，选择板子型号为XC7Z020-CLG484-1，添加hls文件夹内的源文件及测试平台文件，然后依次点击Project、Project Settings...、Synthesis、Browse...，选择sobel作为顶层函数。
- 修改宏INPUT_IMAGE和宏OUTPUT_IMAGE，分别表示待处理图片的文件路径以及图片输出路径。
- 点击Run C Simulation，进行C仿真。
- 点击Run C Synthesis，进行C综合。
- 点击Run C/RTL Cosimulation，进行C/RTL协同仿真。
- 点击Export RTL as IP，将综合后的代码导出为IP。
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创建Vivado工程，选择板子型号为XC7Z020-CLG484-1。
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点击IP Catalog，添加HLS导出IP的路径。
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点击Create Block Design，分别添加HLS导出的IP（名为sobel）、AXI VDMA IP核以及ZYNQ IP核。如下图所示：
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配置IP核
sobel ip：无需配置。
axi vdma ip：将Frame Buffers设置为1，其余保持默认即可。
zynq ip：包括勾选1个AXI GP接口，2个AXI HP接口，设置PL端时钟频率，勾选UART和SD，配置DDR型号（因开发板型号不同而不同）。 -
手动连接AXI STREAM接口，其余自动连线即可，连线完成后，进行Validate Design，最终的硬件系统如下所示
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右键block design文件，点击Create HDL Wrapper。
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点击Generate Bitstream，进行综合、布局布线、生成比特流。
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File-->Export-->Export Hardware，勾选Include bitstream，然后点击OK。
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Tool-->Launch Vitis。
- Launch Vitis后，选择Workspace路径，点击Launch。
- 创建平台
Create Platform Project，输入Project Name，next，next，点击Browse选择vivado导出的.xsa硬件描述文件，最后点击Finish。 - 选择zynq_fsbl下的Board Support Package，点击Modify BSP Settings，勾选xilffs，并将xilffs设置中的use_lfn的修改为1，以支持长文件名的读取。对standalone on ps7_cortexa9_0下的Board Support Package进行相同的操作。
- 创建SDK工程
点击File-->New-->Application Project，填写Project name，next，next，next，选择Empty Application，点击Finish。 - 将sdk文件夹下的所有文件拷贝至创建工程的src文件夹下。
- 双击lscript.ld，修改堆栈大小。如将Stack Size和Heap Size均调节为0x2000000。
- 右键工程，点击Build Project。连接开发板，打开串口调试助手（波特率选择115200）。将bmp图片存入SD卡，插到FPGA开发板上。
- 烧写程序。右键工程，点击Run As-->Run Configuartions，双击Single Application Debug，点击Run。
- 可通过修改const char* input_image和const char* output_image来改变待测试图片和输出图片的文件名。
- 运行完成后，拔出SD卡，在PC上通过读卡器查看结果。
在hls源文件imgProc.cpp中，共包含6个图像处理的示例函数，分别为
//Sobel边缘检测
void sobel(AXI_STREAM& INPUT_STREAM,AXI_STREAM& OUTPUT_STREAM,int rows,int cols);
//彩色图转灰度图
void rgb2gray(AXI_STREAM& INPUT_STREAM,AXI_STREAM& OUTPUT_STREAM,int rows,int cols);
//高斯滤波
void gaussian(AXI_STREAM& INPUT_STREAM,AXI_STREAM& OUTPUT_STREAM,int rows,int cols);
//图像二值化
void binary(AXI_STREAM& INPUT_STREAM,AXI_STREAM& OUTPUT_STREAM,int rows,int cols);
//膨胀和腐蚀
void dilate_erode(AXI_STREAM& INPUT_STREAM,AXI_STREAM& OUTPUT_STREAM,int rows,int cols);
//角点检测
void fast_corner(AXI_STREAM & INPUT_STREAM,AXI_STREAM & OUTPUT_STREAM,int rows,int cols);可以看到，这6个函数的参数是一致的：其中，INPUT_STREAM表示通过AXI STREAM接口输入的待处理图像，OUTPUT_STREAM表示通过AXI STREAM接口输出的已处理图像，rows、cols分别表示待处理图像的高、宽。其处理流程也类似，如下图方框内所示：
首先，将AXI STREAM协议输入的图片或视频通过hls::AXIvideo2Mat转化为hls::Mat数据类型，然后，通过HLS Video library函数链对其进行处理，处理完毕后，再通过hls::Mat2AXIvideo将hls::Mat数据类型转化为AXI STREAM协议的输出。
为了测试其它HLS Open-CV处理函数，仅需修改Demo中的：
- HLS开发中的第1步：选择顶层函数，例如选择fast_corner。
- SDK开发中的第5步：将main.c中的第11、80、110-113以及122行中的IP核名称修改为当前IP核的名字。
//line11,头文件
#include "xsobel.h"--->#include "fast_corner.h"
//line80,结构体定义
XSobel hls_inst;--->XFast_corner hls_inst;
//line 110-113,驱动函数
XSobel_Initialize(&hls_inst,0)--->XFast_corner_Initialize(&hls_inst,0);
XSobel_Set_rows(&hls_inst, (u32)h);--->XFast_corner_Set_rows(&hls_inst,(u32)h);
XSobel_Set_cols(&hls_inst, (u32)w);--->XFast_corner_Set_cols(&hls_inst, (u32)w);
XSobel_Start(&hls_inst);--->XFast_corner_Start(&hls_inst);
//line122,驱动函数
while(XSobel_IsDone(&hls_inst));--->while(XFast_corner_IsDone(&hls_inst));由于在绝大多数情况下，HLS编写的图像处理IP核均具有上述形式，因此，仅需修改HLS代码，以及HLS开发中第1步、SDK开发中第5步，即可实现功能的快速切换。