友情提示，想直接看實現就跳到后面，但如果是跟我一樣的初學者，可以把過程看完，有助於對 OpenCVSharp、NumSharp 以及相關東西有更多的了解。
初學OpenCV，雖然從語法上Python更人性化，但考慮到學習成本，而且總是想用自己較為熟悉的語言，所以選擇了 OpenCVSharp 和 NumSharp。其實 SciSharp 的庫上已經有了融合了 OpenCV 和 NumPy 的 SharpCV，但由於這個庫對OpenCV API的實現相對不完全，所以暫不考慮。
因為市面的教材大部分都基於Python，少部分基於C++，沒有辦法，只能選擇基於Python的教材。剛上手就碰見了Cv2.ImShow(string winName, Mat mat)無法直接使用NDArray作為參數生成圖像，網上還找不到解決方案，還能怎樣，自己不想學Python，那就看看怎么解決吧。
看到Mat有一個構造函數Mat(int rows, int cols, MatType type, Array data, long step = 0)，在 NdArray.Implicit.Array.cs 中找到了NDArray到Array顯性轉換的實現，而NDArray有一個構造函數NDArray(Array values, Shape shape = default, char order = 'C')，Mat又有一個函數bool GetArray<T>(out T[] data)可以提取Array，有戲！
NDArray支持的類型在 NPTypeCode，Mat支持的類型在 MatType，然后我鬼知道這些奇奇怪怪的類型是什么東西，更不知道他們之間是什么對應關系。
public unsafe NDArray GetData()
{
// we pass donothing as it keeps reference to src preventing its disposal by GC
switch (MatType)
{
case MatType.CV_32SC1:
case MatType.CV_32SC2:
{
cv2_native_api.core_Mat_data(_handle, out int* dataPtr);
dtype = TF_DataType.TF_INT32;
return new NDArray(new IntPtr(dataPtr), shape, dtype);
}
case MatType.CV_32FC1:
{
cv2_native_api.core_Mat_data(_handle, out float* dataPtr);
dtype = TF_DataType.TF_FLOAT;
return new NDArray(new IntPtr(dataPtr), shape, dtype);
}
case MatType.CV_8UC1:
case MatType.CV_8UC3:
{
cv2_native_api.core_Mat_data(_handle, out byte* dataPtr);
dtype = TF_DataType.TF_UINT8;
return new NDArray(new IntPtr(dataPtr), shape, dtype);
}
default:
throw new NotImplementedException($"Can't find type: {_matType}");
}
}
所以基本確定Mat和NDArray之間的轉換支持5種類型，分別是CV_32SC1、CV_32SC2、CV_32FC1、CV_8UC1、CV_8UC3，然后查了一下，在 LIST OF MAT TYPE IN OPENCV 這里可以知道這些字母分別代表什么數據類型，綜合看兩者對應關系應該是
NPTypeCode.Int32(1通道) - MatType.CV_32SC1
NPTypeCode.Int32(2通道) - MatType.CV_32SC2
NPTypeCode.Float(1通道) - MatType.CV_32FC1
NPTypeCode.Byte(1通道) - MatType.CV_8UC1
NPTypeCode.Byte(3通道) - MatType.CV_8UC3
OK，寫個擴展函數就搞定。然而，寫完測試發現 bool GetArray<T>(out T[] data) 這個函數導出的數據只有通道數是1的類型才能被NDArray(Array values, Shape shape = default, char order = 'C')支持，Mat 里的acceptableTypesMap這個字典列出了對應類型。
至於為什么不直接用上面 SharpCV 里GetData()的代碼，原因很簡單，因為 OpenCVSharp 只引入了public static extern unsafe ExceptionStatus core_Mat_data(IntPtr self, out byte* returnValue)這個API (NativeMethods_core_Mat.cs)，也就是只支持byte，不支持int32和float，😠😠😠
那只能從NDArray其他的構造函數入手了，沒錯，就是這個 public NDArray(IArraySlice values, Shape shape = default, char order = 'C')。看着看着NDArray的源碼，然后試出了可以使用的方法。接下來就直接上菜吧。
后來在學習 OpenCV 的過程中發現上面提到的幾種轉換是不夠的，至少要把4通道的考慮進去，不然沒法操作透明度。
Mat 轉 NDArray (safe)
public static NDArray ToNDArray(this Mat mat)
{
var matType = mat.Type();
var channels = mat.Channels();
var size = mat.Rows * mat.Cols * channels;
var shape = channels == 1 ? new Shape(mat.Rows, mat.Cols) : new Shape(mat.Rows, mat.Cols, channels);
if (matType == MatType.CV_32SC1 || matType == MatType.CV_32SC2)
{
var managedArray = new int[size];
Marshal.Copy(mat.Data, managedArray, 0, size);
var aslice = ArraySlice.FromArray(managedArray);
return new NDArray(aslice, shape);
}
if (matType == MatType.CV_32FC1)
{
var managedArray = new float[size];
Marshal.Copy(mat.Data, managedArray, 0, size);
var aslice = ArraySlice.FromArray(managedArray);
return new NDArray(aslice, shape);
}
if (matType == MatType.CV_64FC1)
{
var managedArray = new double[size];
Marshal.Copy(mat.Data, managedArray, 0, size);
var aslice = ArraySlice.FromArray(managedArray);
return new NDArray(aslice, shape);
}
if (matType == MatType.CV_8UC1 || matType == MatType.CV_8UC3 || matType == MatType.CV_8UC4)
{
var managedArray = new byte[size];
Marshal.Copy(mat.Data, managedArray, 0, size);
var aslice = ArraySlice.FromArray(managedArray);
return new NDArray(aslice, shape);
}
throw new Exception($"mat data type = {matType} is not supported");
}
NDArray 轉 Mat (safe)
public static Mat ToMat(this NDArray nDArray) =>
new Mat(nDArray.shape[0], nDArray.shape[1], nDArray.GetMatType(), (Array)nDArray);
public static MatType GetMatType(this NDArray nDArray)
{
int channels = nDArray.ndim == 3 ? nDArray.shape[2] : 1;
return nDArray.typecode switch
{
NPTypeCode.Int32 => channels == 1 ? MatType.CV_32SC1 :
channels == 2 ? MatType.CV_32SC2 :
throw new ArgumentException($"nDArray data type = {nDArray.typecode} & channels = {channels} is not supported"),
NPTypeCode.Float => channels == 1 ? MatType.CV_32FC1 :
throw new ArgumentException($"nDArray data type = {nDArray.typecode} & channels = {channels} is not supported"),
NPTypeCode.Double => channels == 1 ? MatType.CV_64FC1 :
throw new ArgumentException($"nDArray data type = {nDArray.typecode} & channels = {channels} is not supported"),
NPTypeCode.Byte => channels == 1 ? MatType.CV_8UC1 :
channels == 3 ? MatType.CV_8UC3 :
channels == 4 ? MatType.CV_8UC4 :
throw new ArgumentException($"nDArray data type = {nDArray.typecode} & channels = {channels} is not supported"),
_ => throw new ArgumentException($"nDArray data type = {nDArray.typecode} is not supported")
};
}
其實中途還找到了應該是 SharpCV 的 Mat 舊版的實現，里面的GetData()是這樣的
public unsafe NDArray GetData()
{
// we pass donothing as it keeps reference to src preventing its disposal by GC
switch (MatType)
{
case MatType.CV_32FC1:
{
cv2_native_api.core_Mat_data(_handle, out float* dataPtr);
var block = new UnmanagedMemoryBlock<float>(dataPtr, shape.Size, () => DoNothing(_handle));
var storage = new UnmanagedStorage(new ArraySlice<float>(block), shape);
return new NDArray(storage);
}
case MatType.CV_8UC1:
case MatType.CV_8UC3:
{
cv2_native_api.core_Mat_data(_handle, out byte* dataPtr);
var block = new UnmanagedMemoryBlock<byte>(dataPtr, size, () => DoNothing(_handle));
var storage = new UnmanagedStorage(new ArraySlice<byte>(block), shape);
return new NDArray(storage);
}
default:
throw new NotImplementedException($"Can't find type: {_matType}");
}
}
[MethodImpl(MethodImplOptions.NoOptimization)]
private void DoNothing(IntPtr ptr)
{
var p = ptr;
}
有人（應該是）根據上面的代碼實現了轉換 issues17
public static unsafe NDArray OpenCvSharpToNDArray(Mat input, int channels = 3)
{
Shape shape = new Shape(new int[] { input.Height, input.Width, channels });
var i = IntPtr.Zero;
if (input.Type() == MatType.CV_32SC1 || input.Type() == MatType.CV_32SC2)
{
int* ptr = (int*)input.DataPointer;
var block = new UnmanagedMemoryBlock<int>(ptr, shape.Size, () => DoNothing(i));
var storage = new UnmanagedStorage(new ArraySlice<int>(block), shape);
return new NDArray(storage);
}
else if (input.Type() == MatType.CV_32FC1)
{
float* ptr = (float*)input.DataPointer;
var block = new UnmanagedMemoryBlock<float>(ptr, shape.Size, () => DoNothing(i));
var storage = new UnmanagedStorage(new ArraySlice<float>(block), shape);
return new NDArray(storage);
}
else if (input.Type() == MatType.CV_8UC1 || input.Type() == MatType.CV_8UC3)
{
byte* ptr = (byte*)input.DataPointer;
var block = new UnmanagedMemoryBlock<byte>(ptr, shape.Size, () => DoNothing(i));
var storage = new UnmanagedStorage(new ArraySlice<byte>(block), shape);
return new NDArray(storage);
}
else
throw new NotImplementedException($"Can't find type: {input.Type()}");
}
[MethodImpl(MethodImplOptions.NoOptimization)]
private static void DoNothing(IntPtr ptr)
{
var p = ptr;
}
這里的 new Shape沒有考慮 channels數，但改一改其實就能用了（沒有親自測試過）。另一點是觸碰到指針，SharpCV 庫修改了GetData()的實現可能也是基於安全的考慮，我是覺得無問題不大，只是想看看還有沒有別的實現方法。反正問題已經解決又可以不碰指針，完事。
20211119
在實踐中發現上面的 ToNDArray()方法效率太低，一張 (500, 500, 3)，np.uint8 的畫布轉換一次(6700HQ)竟然需要40-50ms，相比之下 ToMat()僅需不到1ms。高分辨率畫布的轉換會更明顯，而通過指針進行轉化幾乎不受分辨率的影響。雖然目前還不知道有什么應用場景需要高性能的轉化，但推薦還是通過指針轉換，這樣可以適應更多的應用場景。
Mat 轉 NDArray (unsafe, hi-perf)
public static unsafe NDArray ToNDArrayUnsafe(this Mat mat)
{
var matType = mat.Type();
var channels = mat.Channels();
var size = mat.Rows * mat.Cols * channels;
var shape = channels == 1 ? new Shape(mat.Rows, mat.Cols) : new Shape(mat.Rows, mat.Cols, channels);
if (matType == MatType.CV_32SC1 || matType == MatType.CV_32SC2)
{
int* ptr = (int*)mat.DataPointer;
var block = new UnmanagedMemoryBlock<int>(ptr, shape.Size, () => DoNothing(IntPtr.Zero));
var storage = new UnmanagedStorage(new ArraySlice<int>(block), shape);
return new NDArray(storage);
}
if (matType == MatType.CV_32FC1)
{
float* ptr = (float*)mat.DataPointer;
var block = new UnmanagedMemoryBlock<float>(ptr, shape.Size, () => DoNothing(IntPtr.Zero));
var storage = new UnmanagedStorage(new ArraySlice<float>(block), shape);
return new NDArray(storage);
}
if (matType == MatType.CV_64FC1)
{
double* ptr = (double*)mat.DataPointer;
var block = new UnmanagedMemoryBlock<double>(ptr, shape.Size, () => DoNothing(IntPtr.Zero));
var storage = new UnmanagedStorage(new ArraySlice<double>(block), shape);
return new NDArray(storage);
}
if (matType == MatType.CV_8UC1 || matType == MatType.CV_8UC3 || matType == MatType.CV_8UC4)
{
byte* ptr = (byte*)mat.DataPointer;
var block = new UnmanagedMemoryBlock<byte>(ptr, shape.Size, () => DoNothing(IntPtr.Zero));
var storage = new UnmanagedStorage(new ArraySlice<byte>(block), shape);
return new NDArray(storage);
}
throw new Exception($"mat data type = {matType} is not supported");
}
[MethodImpl(MethodImplOptions.NoOptimization)]
private static void DoNothing(IntPtr ptr)
{
var p = ptr;
}
NDArray 轉 Mat (unsafe, hi-perf)
public unsafe static Mat ToMatUnsafe(this NDArray nDArray) =>
new Mat(nDArray.shape[0], nDArray.shape[1], nDArray.GetMatType(), new IntPtr(nDArray.Unsafe.Address));
public static MatType GetMatType(this NDArray nDArray)
{
int channels = nDArray.ndim == 3 ? nDArray.shape[2] : 1;
return nDArray.typecode switch
{
NPTypeCode.Int32 => channels == 1 ? MatType.CV_32SC1 :
channels == 2 ? MatType.CV_32SC2 :
throw new ArgumentException($"nDArray data type = {nDArray.typecode} & channels = {channels} is not supported"),
NPTypeCode.Float => channels == 1 ? MatType.CV_32FC1 :
throw new ArgumentException($"nDArray data type = {nDArray.typecode} & channels = {channels} is not supported"),
NPTypeCode.Double => channels == 1 ? MatType.CV_64FC1 :
throw new ArgumentException($"nDArray data type = {nDArray.typecode} & channels = {channels} is not supported"),
NPTypeCode.Byte => channels == 1 ? MatType.CV_8UC1 :
channels == 3 ? MatType.CV_8UC3 :
channels == 4 ? MatType.CV_8UC4 :
throw new ArgumentException($"nDArray data type = {nDArray.typecode} & channels = {channels} is not supported"),
_ => throw new ArgumentException($"nDArray data type = {nDArray.typecode} is not supported")
};
}