C#，OpenCv开发指南（02）——OpenCvSharp编程入门与矩阵Mat的基础知识
1 认识 OpenCV 矩阵Mat的属性 Attributes
1.1 一段关于Mat属性的代码
using System;
using System.IO;
using System.Text;
using System.Collections.Generic;
using System.Windows.Forms;
using System.Drawing;
using System.Drawing.Imaging;
using System.Drawing.Drawing2D;
using System.Runtime.InteropServices;
using OpenCvSharp;
using OpenCvSharp.Extensions;
/// <summary>
/// 部分 OpenCVSharp 拓展函数
/// </summary>
public static partial class CVUtility
{
public static string Attributes(Mat src)
{
StringBuilder sb = new StringBuilder();
sb.AppendLine("<html>");
sb.AppendLine("<style>");
sb.AppendLine("td { padding:5px;font-size:12px; } ");
sb.AppendLine(".atd { text-align:right;white-space:nowrap; } ");
sb.AppendLine("</style>");
sb.AppendLine("<table width='100%' border='1' bordercolor='#AAAAAA' style='border-collapse:collapse;'>");
sb.AppendLine("<tr><td rowspan='5'>属<br>性</td><td class='atd'>数据首地址Data(IntPtr): </td><td>" + src.Data + "</td></tr>");
sb.AppendLine("<tr><td class='atd'>行数Rows(=Height): </td><td>" + src.Rows + "=" + src.Height + "</td></tr>");
sb.AppendLine("<tr><td class='atd'>列数Cols(=Width): </td><td>" + src.Cols + "=" + src.Width + "</td></tr>");
sb.AppendLine("<tr><td class='atd'>尺寸Size(Width x Height): </td><td>" + src.Size().Width + "x" + src.Size().Height + "</td></tr>");
sb.AppendLine("<tr><td class='atd'>矩阵维度Dims: </td><td>" + src.Dims + "</td></tr>");
sb.AppendLine("<tr><td rowspan='7'>方<br>法</td><td class='atd'>通道数Channels: </td><td>" + src.Channels() + "</td></tr>");
sb.AppendLine("<tr><td class='atd'>通道的深度Depth: </td><td>" + src.Depth() + "</td></tr>");
sb.AppendLine("<tr><td class='atd'>元素的数据大小ElemSize(bytes): </td><td>" + src.ElemSize() + "</td></tr>");
sb.AppendLine("<tr><td class='atd'>通道1元素的数据大小ElemSize1(bytes): </td><td>" + src.ElemSize1() + "</td></tr>");
sb.AppendLine("<tr><td class='atd'>每行步长Step(bytes): </td><td>" + src.Step() + "</td></tr>");
sb.AppendLine("<tr><td class='atd'>通道1每行步长Step1(bytes): </td><td>" + src.Step1() + "</td></tr>");
sb.AppendLine("<tr><td class='atd'>矩阵类型Type: </td><td>" + src.Type() + "</td></tr>");
sb.AppendLine("</table>");
sb.AppendLine("</html>");
return sb.ToString();
}
}
1.4 属性和常量方法的解释
1.4.7 Depth()
每一个像素中每一个通道的精度。
在Opencv中，Mat.Depth()得到的是一个 0~6 的数字，分别代表不同的位数，
对应关系如下：
CV_8U=0
CV_8S=1
CV_16U=2
CV_16S=3
CV_32S=4
CV_32F=5
CV_64F=6
其中U是unsigned的意思，S表示signed，也就是有符号和无符号数。
1.4.8 ElemSize() and ElemSize1()
矩阵中每一个元素的数据字节数(bytes)。
如果Mat中的数据类型是CV_8UC1，那么ElemSize = 1；
如果是CV_8UC3或CV_8SC3，那么 ElemSize = 3；
如果是CV_16UC3或者CV_16SC3，那么 ElemSize = 6；
可见，ElemSize是以字节为单位的；
ElemSize1() 就是通道1的数据字节数。有：
ElemSize1 = ElemSize / Channels
1.4.9 Step() and Step1()
Mat矩阵中每一行的步长(字节)，即为每一行中所有元素的字节总量。
Step1() 是通道1的步长。有：
Step1 = Step / ElemSize1
1.5 Mat Type 的定义
/// <summary>
/// typeof(T) -> MatType
/// </summary>
protected static readonly IReadOnlyDictionary<Type, MatType> TypeMap = new Dictionary<Type, MatType>
{
[typeof(byte)] = MatType.CV_8UC1,
[typeof(sbyte)] = MatType.CV_8SC1,
[typeof(short)] = MatType.CV_16SC1,
[typeof(char)] = MatType.CV_16UC1,
[typeof(ushort)] = MatType.CV_16UC1,
[typeof(int)] = MatType.CV_32SC1,
[typeof(float)] = MatType.CV_32FC1,
[typeof(double)] = MatType.CV_64FC1,
[typeof(Vec2b)] = MatType.CV_8UC2,
[typeof(Vec3b)] = MatType.CV_8UC3,
[typeof(Vec4b)] = MatType.CV_8UC4,
[typeof(Vec6b)] = MatType.CV_8UC(6),
[typeof(Vec2s)] = MatType.CV_16SC2,
[typeof(Vec3s)] = MatType.CV_16SC3,
[typeof(Vec4s)] = MatType.CV_16SC4,
[typeof(Vec6s)] = MatType.CV_16SC(6),
[typeof(Vec2w)] = MatType.CV_16UC2,
[typeof(Vec3w)] = MatType.CV_16UC3,
[typeof(Vec4w)] = MatType.CV_16UC4,
[typeof(Vec6w)] = MatType.CV_16UC(6),
[typeof(Vec2i)] = MatType.CV_32SC2,
[typeof(Vec3i)] = MatType.CV_32SC3,
[typeof(Vec4i)] = MatType.CV_32SC4,
[typeof(Vec6i)] = MatType.CV_32SC(6),
[typeof(Vec2f)] = MatType.CV_32FC2,
[typeof(Vec3f)] = MatType.CV_32FC3,
[typeof(Vec4f)] = MatType.CV_32FC4,
[typeof(Vec6f)] = MatType.CV_32FC(6),
[typeof(Vec2d)] = MatType.CV_64FC2,
[typeof(Vec3d)] = MatType.CV_64FC3,
[typeof(Vec4d)] = MatType.CV_64FC4,
[typeof(Vec6d)] = MatType.CV_64FC(6),
[typeof(Point)] = MatType.CV_32SC2,
[typeof(Point2f)] = MatType.CV_32FC2,
[typeof(Point2d)] = MatType.CV_64FC2,
[typeof(Point3i)] = MatType.CV_32SC3,
[typeof(Point3f)] = MatType.CV_32FC3,
[typeof(Point3d)] = MatType.CV_64FC3,
[typeof(Size)] = MatType.CV_32SC2,
[typeof(Size2f)] = MatType.CV_32FC2,
[typeof(Size2d)] = MatType.CV_64FC2,
[typeof(Rect)] = MatType.CV_32SC4,
[typeof(Rect2f)] = MatType.CV_32FC4,
[typeof(Rect2d)] = MatType.CV_64FC4,
[typeof(DMatch)] = MatType.CV_32FC4,
};
2 创建 Mat 实例
有多达 15 种方法可以创建 Mat 的实例。选择常用的介绍一下。
2.1 从数据（数组）创建 Mat
可以从数组创建一维、二维及更多为的矩阵。
using System;
using System.IO;
using System.Collections;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Windows.Forms;
using System.Drawing.Imaging;
using OpenCvSharp;
namespace Legalsoft.OpenCv.Train
{
public partial class Form1 : Form
{
private void button1_Click(object sender, EventArgs e)
{
double[,] a = new double[4, 3] {
{
1, 2, 3 },
{
4, 5, 6 },
{
7, 8, 9 },
{
10, 11, 12 }
};
Mat src = new Mat(4, 3, MatType.CV_64F, a, 0);
webBrowser1.DocumentText = CVUtility.ToHtmlTable(src);
}
}
}
其中显示 矩阵 的方法 ToHtmlTable 源代码为：
using System;
using System.Text;
using System.Collections;
using System.Collections.Generic;
using OpenCvSharp;
using OpenCvSharp.Extensions;
/// <summary>
/// 部分 OpenCVSharp 拓展函数
/// </summary>
public static partial class CVUtility
{
/// <summary>
/// 矩阵输出为HTML表格
/// </summary>
/// <param name="src"></param>
/// <returns></returns>
public static string ToHtmlTable(Mat src)
{
StringBuilder sb = new StringBuilder();
sb.AppendLine("<html>");
sb.AppendLine("<style>");
sb.AppendLine("td { padding:10px; } ");
sb.AppendLine(".atd { background-color:#FAFAFF; } ");
sb.AppendLine("</style>");
sb.AppendLine("<table width='100%' border='1' bordercolor='#AAAAAA' style='border-collapse:collapse;'>");
for (int y = 0; y < src.Height; y++)
{
if (y == 0)
{
// 标题行
sb.AppendLine("<tr class='atd'>");
sb.Append("<td class='atd'></td>");
for (int x = 0; x < src.Width; x++)
{
sb.AppendFormat("<td class='atd'>{0:D}</td>", (x + 1));
}
sb.Append("<td class='atd'></td>");
sb.AppendLine("</tr>");
}
sb.AppendLine("<tr>");
sb.AppendFormat("<td class='atd'>{0:D}</td>", (y + 1));
for (int x = 0; x < src.Width; x++)
{
sb.AppendFormat("<td>{0:F6}</td>", src.At<double>(y, x));
}
sb.AppendFormat("<td class='atd'>{0:D}</td>", (y + 1));
sb.AppendLine("</tr>");
if (y == (src.Height - 1))
{
// 标题行
sb.AppendLine("<tr class='atd'>");
sb.Append("<td class='atd'></td>");
for (int x = 0; x < src.Width; x++)
{
sb.AppendFormat("<td class='atd'>{0:D}</td>", (x + 1));
}
sb.Append("<td class='atd'></td>");
sb.AppendLine("</tr>");
}
}
sb.AppendLine("</table>");
sb.AppendLine("</html>");
return sb.ToString();
}
}
矩阵数据显示：
2.4 一些特殊的矩阵
2.4.1 单位矩阵
Mat m1 = Mat.Eye(new OpenCvSharp.Size(5, 5), MatType.CV_64F);
webBrowser1.DocumentText = CVUtility.ToHtmlTable(m1);
2.4.2 全0矩阵
// 全为0的矩阵
Mat m2 = Mat.Zeros(new OpenCvSharp.Size(5, 5), MatType.CV_64F);
webBrowser1.DocumentText = CVUtility.ToHtmlTable(m2);
2.4.3 全1矩阵
// 全为1的矩阵
Mat m3 = Mat.Ones(new OpenCvSharp.Size(5, 5), MatType.CV_64F);
webBrowser1.DocumentText = CVUtility.ToHtmlTable(m3);
3 访问矩阵元素（图片像素）的多种方法
下面列出 3 种访问图片像素的方法，并交换 Red Blue 通道的实例。
3.1 Get/Set (slow)
/// <summary>
/// 普通访问方式
/// Get/Set (slow)
/// </summary>
/// <param name="src"></param>
public static void Search_GetSet(Mat src)
{
for (int y = 0; y < src.Height; y++)
{
for (int x = 0; x < src.Width; x++)
{
Vec3b color = src.Get<Vec3b>(y, x);
byte temp = color.Item0;
color.Item0 = color.Item2; // B <- R
color.Item2 = temp; // R <- B
src.Set<Vec3b>(y, x, color);
}
}
}
3.2 GenericIndexer (reasonably fast)
/// <summary>
/// 通用索引器方式访问像素
/// GenericIndexer(reasonably fast)
/// </summary>
/// <param name="src"></param>
public static void Search_Indexer(Mat src)
{
Mat.Indexer<Vec3b> indexer = src.GetGenericIndexer<Vec3b>();
for (int y = 0; y < src.Height; y++)
{
for (int x = 0; x < src.Width; x++)
{
Vec3b color = indexer[y, x];
byte temp = color.Item0;
color.Item0 = color.Item2; // B <- R
color.Item2 = temp; // R <- B
indexer[y, x] = color;
}
}
}
3.3 TypeSpecificMat (faster)
/// <summary>
/// TypeSpecificMat(faster)
/// </summary>
/// <param name="src"></param>
public static void Search_TypeSpecific(Mat src)
{
Mat<Vec3b> mat3 = new Mat<Vec3b>(src);
var indexer = mat3.GetIndexer();
for (int y = 0; y < src.Height; y++)
{
for (int x = 0; x < src.Width; x++)
{
Vec3b color = indexer[y, x];
byte temp = color.Item0;
color.Item0 = color.Item2; // B <- R
color.Item2 = temp; // R <- B
indexer[y, x] = color;
}
}
}
4 矩阵与其他图片数据的转换
利用 OpenCvSharp 进行计算或图片处理后，图片需要以各种方式予以体现，因而需要将 Mat 转为其他格式的图片信息，或反其道行之。
4.1 Mat -> System.Drawing.Bitmap
using OpenCvSharp;
using OpenCvSharp.Extensions;
Mat mat = new Mat("demo.jpg", ImreadModes.Color);
Bitmap bitmap = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(mat);
4.2 System.Drawing.Bitmap -> Mat
using OpenCvSharp;
using OpenCvSharp.Extensions;
Bitmap bitmap = new Bitmap("demo.png");
Mat mat = OpenCvSharp.Extensions.BitmapConverter.ToMat(bitmap);
4.3 Mat -> byte[]
Mat mat = new Mat("demo.png", ImreadModes.Color);
byte[] bytes1 = mat.ToBytes(".png");
// or
Cv2.ImEncode(".png", mat, out byte[] bytes2);
4.4 彩色图转灰度图或其他
常用的函数是
Cv2.CvtColor(Mat src, Mat dst, ColorConversionCodes code, int dstCn: 0);
常见的实例：
/// <summary>
/// 转为灰色图（8 bit）
/// </summary>
/// <param name="src"></param>
/// <returns></returns>
public static Mat ToGray(Mat src)
{
Mat dst = new Mat();
// 转为灰度图 但通道 8 bit (必须)
Cv2.CvtColor(src, dst, ColorConversionCodes.BGR2GRAY);
return dst;
}
其中的 ColorConversionCodes 枚举类型极多，记住几个常用的即可。
enum ColorConversionCodes {
COLOR_BGR2BGRA = 0, //!< add alpha channel to RGB or BGR image
COLOR_RGB2RGBA = COLOR_BGR2BGRA,
COLOR_BGRA2BGR = 1, //!< remove alpha channel from RGB or BGR image
COLOR_RGBA2RGB = COLOR_BGRA2BGR,
COLOR_BGR2RGBA = 2, //!< convert between RGB and BGR color spaces (with or without alpha channel)
COLOR_RGB2BGRA = COLOR_BGR2RGBA,
COLOR_RGBA2BGR = 3,
COLOR_BGRA2RGB = COLOR_RGBA2BGR,
COLOR_BGR2RGB = 4,
COLOR_RGB2BGR = COLOR_BGR2RGB,
COLOR_BGRA2RGBA = 5,
COLOR_RGBA2BGRA = COLOR_BGRA2RGBA,
COLOR_BGR2GRAY = 6, //!< convert between RGB/BGR and grayscale, @ref color_convert_rgb_gray "color conversions"
COLOR_RGB2GRAY = 7,
COLOR_GRAY2BGR = 8,
COLOR_GRAY2RGB = COLOR_GRAY2BGR,
COLOR_GRAY2BGRA = 9,
COLOR_GRAY2RGBA = COLOR_GRAY2BGRA,
COLOR_BGRA2GRAY = 10,
COLOR_RGBA2GRAY = 11,
COLOR_BGR2BGR565 = 12, //!< convert between RGB/BGR and BGR565 (16-bit images)
COLOR_RGB2BGR565 = 13,
COLOR_BGR5652BGR = 14,
COLOR_BGR5652RGB = 15,
COLOR_BGRA2BGR565 = 16,
COLOR_RGBA2BGR565 = 17,
COLOR_BGR5652BGRA = 18,
COLOR_BGR5652RGBA = 19,
COLOR_GRAY2BGR565 = 20, //!< convert between grayscale to BGR565 (16-bit images)
COLOR_BGR5652GRAY = 21,
COLOR_BGR2BGR555 = 22, //!< convert between RGB/BGR and BGR555 (16-bit images)
COLOR_RGB2BGR555 = 23,
COLOR_BGR5552BGR = 24,
COLOR_BGR5552RGB = 25,
COLOR_BGRA2BGR555 = 26,
COLOR_RGBA2BGR555 = 27,
COLOR_BGR5552BGRA = 28,
COLOR_BGR5552RGBA = 29,
COLOR_GRAY2BGR555 = 30, //!< convert between grayscale and BGR555 (16-bit images)
COLOR_BGR5552GRAY = 31,
COLOR_BGR2XYZ = 32, //!< convert RGB/BGR to CIE XYZ, @ref color_convert_rgb_xyz "color conversions"
COLOR_RGB2XYZ = 33,
COLOR_XYZ2BGR = 34,
COLOR_XYZ2RGB = 35,
COLOR_BGR2YCrCb = 36, //!< convert RGB/BGR to luma-chroma (aka YCC), @ref color_convert_rgb_ycrcb "color conversions"
COLOR_RGB2YCrCb = 37,
COLOR_YCrCb2BGR = 38,
COLOR_YCrCb2RGB = 39,
COLOR_BGR2HSV = 40, //!< convert RGB/BGR to HSV (hue saturation value), @ref color_convert_rgb_hsv "color conversions"
COLOR_RGB2HSV = 41,
COLOR_BGR2Lab = 44, //!< convert RGB/BGR to CIE Lab, @ref color_convert_rgb_lab "color conversions"
COLOR_RGB2Lab = 45,
COLOR_BGR2Luv = 50, //!< convert RGB/BGR to CIE Luv, @ref color_convert_rgb_luv "color conversions"
COLOR_RGB2Luv = 51,
COLOR_BGR2HLS = 52, //!< convert RGB/BGR to HLS (hue lightness saturation), @ref color_convert_rgb_hls "color conversions"
COLOR_RGB2HLS = 53,
COLOR_HSV2BGR = 54, //!< backward conversions to RGB/BGR
COLOR_HSV2RGB = 55,
COLOR_Lab2BGR = 56,
COLOR_Lab2RGB = 57,
COLOR_Luv2BGR = 58,
COLOR_Luv2RGB = 59,
COLOR_HLS2BGR = 60,
COLOR_HLS2RGB = 61,
COLOR_BGR2HSV_FULL = 66,
COLOR_RGB2HSV_FULL = 67,
COLOR_BGR2HLS_FULL = 68,
COLOR_RGB2HLS_FULL = 69,
COLOR_HSV2BGR_FULL = 70,
COLOR_HSV2RGB_FULL = 71,
COLOR_HLS2BGR_FULL = 72,
COLOR_HLS2RGB_FULL = 73,
COLOR_LBGR2Lab = 74,
COLOR_LRGB2Lab = 75,
COLOR_LBGR2Luv = 76,
COLOR_LRGB2Luv = 77,
COLOR_Lab2LBGR = 78,
COLOR_Lab2LRGB = 79,
COLOR_Luv2LBGR = 80,
COLOR_Luv2LRGB = 81,
COLOR_BGR2YUV = 82, //!< convert between RGB/BGR and YUV
COLOR_RGB2YUV = 83,
COLOR_YUV2BGR = 84,
COLOR_YUV2RGB = 85,
//! YUV 4:2:0 family to RGB
COLOR_YUV2RGB_NV12 = 90,
COLOR_YUV2BGR_NV12 = 91,
COLOR_YUV2RGB_NV21 = 92,
COLOR_YUV2BGR_NV21 = 93,
COLOR_YUV420sp2RGB = COLOR_YUV2RGB_NV21,
COLOR_YUV420sp2BGR = COLOR_YUV2BGR_NV21,
COLOR_YUV2RGBA_NV12 = 94,
COLOR_YUV2BGRA_NV12 = 95,
COLOR_YUV2RGBA_NV21 = 96,
COLOR_YUV2BGRA_NV21 = 97,
COLOR_YUV420sp2RGBA = COLOR_YUV2RGBA_NV21,
COLOR_YUV420sp2BGRA = COLOR_YUV2BGRA_NV21,
COLOR_YUV2RGB_YV12 = 98,
COLOR_YUV2BGR_YV12 = 99,
COLOR_YUV2RGB_IYUV = 100,
COLOR_YUV2BGR_IYUV = 101,
COLOR_YUV2RGB_I420 = COLOR_YUV2RGB_IYUV,
COLOR_YUV2BGR_I420 = COLOR_YUV2BGR_IYUV,
COLOR_YUV420p2RGB = COLOR_YUV2RGB_YV12,
COLOR_YUV420p2BGR = COLOR_YUV2BGR_YV12,
COLOR_YUV2RGBA_YV12 = 102,
COLOR_YUV2BGRA_YV12 = 103,
COLOR_YUV2RGBA_IYUV = 104,
COLOR_YUV2BGRA_IYUV = 105,
COLOR_YUV2RGBA_I420 = COLOR_YUV2RGBA_IYUV,
COLOR_YUV2BGRA_I420 = COLOR_YUV2BGRA_IYUV,
COLOR_YUV420p2RGBA = COLOR_YUV2RGBA_YV12,
COLOR_YUV420p2BGRA = COLOR_YUV2BGRA_YV12,
COLOR_YUV2GRAY_420 = 106,
COLOR_YUV2GRAY_NV21 = COLOR_YUV2GRAY_420,
COLOR_YUV2GRAY_NV12 = COLOR_YUV2GRAY_420,
COLOR_YUV2GRAY_YV12 = COLOR_YUV2GRAY_420,
COLOR_YUV2GRAY_IYUV = COLOR_YUV2GRAY_420,
COLOR_YUV2GRAY_I420 = COLOR_YUV2GRAY_420,
COLOR_YUV420sp2GRAY = COLOR_YUV2GRAY_420,
COLOR_YUV420p2GRAY = COLOR_YUV2GRAY_420,
//! YUV 4:2:2 family to RGB
COLOR_YUV2RGB_UYVY = 107,
COLOR_YUV2BGR_UYVY = 108,
//COLOR_YUV2RGB_VYUY = 109,
//COLOR_YUV2BGR_VYUY = 110,
COLOR_YUV2RGB_Y422 = COLOR_YUV2RGB_UYVY,
COLOR_YUV2BGR_Y422 = COLOR_YUV2BGR_UYVY,
COLOR_YUV2RGB_UYNV = COLOR_YUV2RGB_UYVY,
COLOR_YUV2BGR_UYNV = COLOR_YUV2BGR_UYVY,
COLOR_YUV2RGBA_UYVY = 111,
COLOR_YUV2BGRA_UYVY = 112,
//COLOR_YUV2RGBA_VYUY = 113,
//COLOR_YUV2BGRA_VYUY = 114,
COLOR_YUV2RGBA_Y422 = COLOR_YUV2RGBA_UYVY,
COLOR_YUV2BGRA_Y422 = COLOR_YUV2BGRA_UYVY,
COLOR_YUV2RGBA_UYNV = COLOR_YUV2RGBA_UYVY,
COLOR_YUV2BGRA_UYNV = COLOR_YUV2BGRA_UYVY,
COLOR_YUV2RGB_YUY2 = 115,
COLOR_YUV2BGR_YUY2 = 116,
COLOR_YUV2RGB_YVYU = 117,
COLOR_YUV2BGR_YVYU = 118,
COLOR_YUV2RGB_YUYV = COLOR_YUV2RGB_YUY2,
COLOR_YUV2BGR_YUYV = COLOR_YUV2BGR_YUY2,
COLOR_YUV2RGB_YUNV = COLOR_YUV2RGB_YUY2,
COLOR_YUV2BGR_YUNV = COLOR_YUV2BGR_YUY2,
COLOR_YUV2RGBA_YUY2 = 119,
COLOR_YUV2BGRA_YUY2 = 120,
COLOR_YUV2RGBA_YVYU = 121,
COLOR_YUV2BGRA_YVYU = 122,
COLOR_YUV2RGBA_YUYV = COLOR_YUV2RGBA_YUY2,
COLOR_YUV2BGRA_YUYV = COLOR_YUV2BGRA_YUY2,
COLOR_YUV2RGBA_YUNV = COLOR_YUV2RGBA_YUY2,
COLOR_YUV2BGRA_YUNV = COLOR_YUV2BGRA_YUY2,
COLOR_YUV2GRAY_UYVY = 123,
COLOR_YUV2GRAY_YUY2 = 124,
//CV_YUV2GRAY_VYUY = CV_YUV2GRAY_UYVY,
COLOR_YUV2GRAY_Y422 = COLOR_YUV2GRAY_UYVY,
COLOR_YUV2GRAY_UYNV = COLOR_YUV2GRAY_UYVY,
COLOR_YUV2GRAY_YVYU = COLOR_YUV2GRAY_YUY2,
COLOR_YUV2GRAY_YUYV = COLOR_YUV2GRAY_YUY2,
COLOR_YUV2GRAY_YUNV = COLOR_YUV2GRAY_YUY2,
//! alpha premultiplication
COLOR_RGBA2mRGBA = 125,
COLOR_mRGBA2RGBA = 126,
//! RGB to YUV 4:2:0 family
COLOR_RGB2YUV_I420 = 127,
COLOR_BGR2YUV_I420 = 128,
COLOR_RGB2YUV_IYUV = COLOR_RGB2YUV_I420,
COLOR_BGR2YUV_IYUV = COLOR_BGR2YUV_I420,
COLOR_RGBA2YUV_I420 = 129,
COLOR_BGRA2YUV_I420 = 130,
COLOR_RGBA2YUV_IYUV = COLOR_RGBA2YUV_I420,
COLOR_BGRA2YUV_IYUV = COLOR_BGRA2YUV_I420,
COLOR_RGB2YUV_YV12 = 131,
COLOR_BGR2YUV_YV12 = 132,
COLOR_RGBA2YUV_YV12 = 133,
COLOR_BGRA2YUV_YV12 = 134,
//! Demosaicing
COLOR_BayerBG2BGR = 46,
COLOR_BayerGB2BGR = 47,
COLOR_BayerRG2BGR = 48,
COLOR_BayerGR2BGR = 49,
COLOR_BayerBG2RGB = COLOR_BayerRG2BGR,
COLOR_BayerGB2RGB = COLOR_BayerGR2BGR,
COLOR_BayerRG2RGB = COLOR_BayerBG2BGR,
COLOR_BayerGR2RGB = COLOR_BayerGB2BGR,
COLOR_BayerBG2GRAY = 86,
COLOR_BayerGB2GRAY = 87,
COLOR_BayerRG2GRAY = 88,
COLOR_BayerGR2GRAY = 89,
//! Demosaicing using Variable Number of Gradients
COLOR_BayerBG2BGR_VNG = 62,
COLOR_BayerGB2BGR_VNG = 63,
COLOR_BayerRG2BGR_VNG = 64,
COLOR_BayerGR2BGR_VNG = 65,
COLOR_BayerBG2RGB_VNG = COLOR_BayerRG2BGR_VNG,
COLOR_BayerGB2RGB_VNG = COLOR_BayerGR2BGR_VNG,
COLOR_BayerRG2RGB_VNG = COLOR_BayerBG2BGR_VNG,
COLOR_BayerGR2RGB_VNG = COLOR_BayerGB2BGR_VNG,
//! Edge-Aware Demosaicing
COLOR_BayerBG2BGR_EA = 135,
COLOR_BayerGB2BGR_EA = 136,
COLOR_BayerRG2BGR_EA = 137,
COLOR_BayerGR2BGR_EA = 138,
COLOR_BayerBG2RGB_EA = COLOR_BayerRG2BGR_EA,
COLOR_BayerGB2RGB_EA = COLOR_BayerGR2BGR_EA,
COLOR_BayerRG2RGB_EA = COLOR_BayerBG2BGR_EA,
COLOR_BayerGR2RGB_EA = COLOR_BayerGB2BGR_EA,
//! Demosaicing with alpha channel
COLOR_BayerBG2BGRA = 139,
COLOR_BayerGB2BGRA = 140,
COLOR_BayerRG2BGRA = 141,
COLOR_BayerGR2BGRA = 142,
COLOR_BayerBG2RGBA = COLOR_BayerRG2BGRA,
COLOR_BayerGB2RGBA = COLOR_BayerGR2BGRA,
COLOR_BayerRG2RGBA = COLOR_BayerBG2BGRA,
COLOR_BayerGR2RGBA = COLOR_BayerGB2BGRA,
COLOR_COLORCVT_MAX = 143
};