/// <summary>
/// Constructor that Takes an IImage
/// </summary>
/// <param name="image"></param>
/// <param name="clone"></param>
/// <param name="aspectRatio"></param>
/// <param name="fourCC"></param>
/// <param name="frameRateNumerator"></param>
/// <param name="frameRateDenominator"></param>
/// <param name="format"></param>
public VideoFrame(IImage image, bool clone, float aspectRatio, NDIlib.FourCC_type_e fourCC,
int frameRateNumerator, int frameRateDenominator, NDIlib.frame_format_type_e format)
{
var ar = aspectRatio;
if (ar <= 0.0)
{
ar = (float)image.Info.Width / image.Info.Height;
}
int bufferSize = image.Info.ImageSize;
IntPtr videoBufferPtr;
if (clone)
{
// we have to know to free it later
_memoryOwned = true;
// allocate some memory for a video buffer
videoBufferPtr = Marshal.AllocHGlobal(bufferSize);
using (var handle = image.GetData().Bytes.Pin())
{
unsafe
{
System.Buffer.MemoryCopy((void *)handle.Pointer, (void *)videoBufferPtr.ToPointer(), bufferSize, bufferSize);
}
}
}
else
{
_pinnedBytes = true;
unsafe
{
_handle = image.GetData().Bytes.Pin(); //unpin when frame gets Disposed
videoBufferPtr = (IntPtr)_handle.Pointer;
}
}
_ndiVideoFrame = new NDIlib.video_frame_v2_t()
{
xres = image.Info.Width,
yres = image.Info.Height,
FourCC = fourCC,
frame_rate_N = frameRateNumerator,
frame_rate_D = frameRateDenominator,
picture_aspect_ratio = ar,
frame_format_type = format,
timecode = NDIlib.send_timecode_synthesize,
p_data = videoBufferPtr,
line_stride_in_bytes = image.Info.ScanSize,
p_metadata = IntPtr.Zero,
timestamp = 0
};
}
public unsafe PointerBitmap(System.Buffers.MemoryHandle bitmapData, BitmapInfo bitmapInfo, bool isReadOnly = false)
{
if (bitmapData.Pointer == null)
{
throw new ArgumentNullException(nameof(bitmapData));
}
_Pointer = new IntPtr(bitmapData.Pointer);
_Info = bitmapInfo;
_IsReadOnly = isReadOnly;
}
/// <summary>
/// Creates a new pinned buffer from an existing buffer
/// </summary>
/// <param name="buffer">existing buffer to pin</param>
public PinnedBuffer(T[] buffer)
{
// allocate managed space
ManagedBuffer = buffer;
// pin the memory
Memory = new Memory <T>(ManagedBuffer);
Handle = Memory.Pin();
// get a pointer to the pinned memory
pData = (T *)Handle.Pointer;
}
/// <summary>
/// Runs the loaded model for the given inputs and outputs. Uses the given RunOptions for this run.
///
/// Outputs need to be created with correct type and dimension to receive the fetched data.
/// </summary>
/// <param name="inputNames">Specify a collection of string that indicates the input names. Should match <paramref name="inputValues"/>.</param>
/// <param name="inputValues">Specify a collection of <see cref="FixedBufferOnnxValue"/> that indicates the input values.</param>
/// <param name="output">Specify a collection of <see cref="NamedOnnxValue"/> that indicates the output values.</param>
/// <param name="options"></param>
public void Run(
IReadOnlyCollection <string> inputNames,
IReadOnlyCollection <FixedBufferOnnxValue> inputValues,
IReadOnlyCollection <NamedOnnxValue> outputs,
RunOptions options)
{
if (inputNames.Count != inputValues.Count)
{
throw new ArgumentException($"Length of {nameof(inputNames)} ({inputNames.Count}) must match that of {nameof(inputValues)} ({inputValues.Count}).");
}
var outputNamesArray = new string[outputs.Count];
var outputValuesArray = new IntPtr[outputs.Count];
var pinnedOutputBufferHandles = new System.Buffers.MemoryHandle[outputs.Count];
var disposeOutputs = new bool[outputs.Count];
try
{
// prepare inputs
string[] inputNamesArray = inputNames as string[] ?? inputNames.ToArray();
IntPtr[] inputValuesArray = new IntPtr[inputNames.Count];
int inputIndex = 0;
foreach (var input in inputValues)
{
inputValuesArray[inputIndex] = input.Value;
inputIndex++;
}
// prepare outputs
int outputIndex = 0;
foreach (var output in outputs)
{
outputNamesArray[outputIndex] = output.Name;
// create native OrtValue from the output if feasible, else throw notsupported exception for now
output.ToNativeOnnxValue(
out outputValuesArray[outputIndex],
out pinnedOutputBufferHandles[outputIndex],
out disposeOutputs[outputIndex]);
outputIndex++;
}
IntPtr status = NativeMethods.OrtRun(
_nativeHandle,
options.Handle,
inputNamesArray,
inputValuesArray,
(UIntPtr)inputNames.Count,
outputNamesArray,
(UIntPtr)outputs.Count,
outputValuesArray /* pointers to Pre-allocated OrtValue instances */
);
NativeApiStatus.VerifySuccess(status);
}
finally
{
for (int i = 0; i < outputs.Count; i++)
{
if (disposeOutputs[i])
{
NativeMethods.OrtReleaseValue(outputValuesArray[i]); // For elementary type Tensors, this should not release the buffer, but should delete the native tensor object.
// For string tensors, this releases the native memory allocated for the tensor, including the buffer
pinnedOutputBufferHandles[i].Dispose();
}
}
}
}
/// <summary>
/// Runs the loaded model for the given inputs, and fetches the specified outputs in <paramref name="outputNames"/>. Uses the given RunOptions for this run.
/// </summary>
/// <param name="inputs">Specify a collection of <see cref="NamedOnnxValue"/> that indicates the input values.</param>
/// <param name="outputNames">Specify a collection of string that indicates the output names to fetch.</param>
/// <param name="options"></param>
/// <returns>Output Tensors in a Collection of NamedOnnxValue. User must dispose the output.</returns>
public IDisposableReadOnlyCollection <DisposableNamedOnnxValue> Run(IReadOnlyCollection <NamedOnnxValue> inputs, IReadOnlyCollection <string> outputNames, RunOptions options)
{
// prepare inputs
var inputNamesArray = new string[inputs.Count];
var inputValuesArray = new IntPtr[inputs.Count];
var pinnedInputBufferHandles = new System.Buffers.MemoryHandle[inputs.Count];
var disposeInputs = new bool[inputs.Count];
int inputIndex = 0;
foreach (var input in inputs)
{
inputNamesArray[inputIndex] = input.Name;
// create Tensor from the input if feasible, else throw notsupported exception for now
input.ToNativeOnnxValue(
out inputValuesArray[inputIndex],
out pinnedInputBufferHandles[inputIndex],
out disposeInputs[inputIndex]);
inputIndex++;
}
// prepare outputs
string[] outputNamesArray = outputNames as string[] ?? outputNames.ToArray();
IntPtr[] outputValuesArray = new IntPtr[outputNames.Count];
IntPtr status = NativeMethods.OrtRun(
_nativeHandle,
options.Handle,
inputNamesArray,
inputValuesArray,
(UIntPtr)inputs.Count,
outputNamesArray,
(UIntPtr)outputNames.Count,
outputValuesArray /* Empty array is passed in to receive output OrtValue pointers */
);
try
{
NativeApiStatus.VerifySuccess(status);
var result = new DisposableList <DisposableNamedOnnxValue>(outputValuesArray.Length);
for (int i = 0; i < outputValuesArray.Length; i++)
{
result.Add(DisposableNamedOnnxValue.CreateFromOnnxValue(outputNamesArray[i], outputValuesArray[i]));
}
return(result);
}
catch (OnnxRuntimeException e)
{
//clean up the individual output tensors if it is not null;
for (int i = 0; i < outputValuesArray.Length; i++)
{
if (outputValuesArray[i] != IntPtr.Zero)
{
NativeMethods.OrtReleaseValue(outputValuesArray[i]);
}
}
throw e;
}
finally
{
for (int i = 0; i < inputs.Count; i++)
{
if (disposeInputs[i])
{
NativeMethods.OrtReleaseValue(inputValuesArray[i]); // For elementary type Tensors, this should not release the buffer, but should delete the native tensor object.
// For string tensors, this releases the native memory allocated for the tensor, including the buffer
pinnedInputBufferHandles[i].Dispose();
}
}
}
}
/// <summary>
/// Runs the loaded model for the given inputs, and fetches the specified outputs in <paramref name="outputNames"/>.
/// </summary>
/// <param name="inputs"></param>
/// <param name="outputNames"></param>
/// <param name="options"></param>
/// <returns>Output Tensors in a Dictionary</returns>
//TODO: kept internal until RunOptions is made public
internal IReadOnlyCollection <NamedOnnxValue> Run(IReadOnlyCollection <NamedOnnxValue> inputs, IReadOnlyCollection <string> outputNames, RunOptions options)
{
var inputNames = new string[inputs.Count];
var inputTensors = new IntPtr[inputs.Count];
var pinnedBufferHandles = new System.Buffers.MemoryHandle[inputs.Count];
int offset = 0;
foreach (var input in inputs)
{
inputNames[offset] = input.Name;
// create Tensor from the input if feasible, else throw notsupported exception for now
input.ToNativeOnnxValue(out inputTensors[offset], out pinnedBufferHandles[offset]);
offset++;
}
string[] outputNamesArray = outputNames.ToArray();
IntPtr[] outputValueArray = new IntPtr[outputNames.Count];
IntPtr status = NativeMethods.OrtRunInference(
this._nativeHandle,
IntPtr.Zero, // TODO: use Run options when Run options creation API is available
// Passing null uses the default run options in the C-api
inputNames,
inputTensors,
(ulong)(inputTensors.Length), /* TODO: size_t, make it portable for x86 arm */
outputNamesArray,
(ulong)outputNames.Count, /* TODO: size_t, make it portable for x86 and arm */
outputValueArray /* An array of output value pointers. Array must be allocated by the caller */
);
try
{
NativeApiStatus.VerifySuccess(status);
var result = new List <NamedOnnxValue>();
for (uint i = 0; i < outputValueArray.Length; i++)
{
result.Add(NamedOnnxValue.CreateFromOnnxValue(outputNamesArray[i], outputValueArray[i]));
}
return(result);
}
catch (OnnxRuntimeException e)
{
//clean up the individual output tensors if it is not null;
for (uint i = 0; i < outputValueArray.Length; i++)
{
if (outputValueArray[i] != IntPtr.Zero)
{
NativeMethods.OrtReleaseValue(outputValueArray[i]);
}
}
throw e;
}
finally
{
// always unpin the input buffers, and delete the native Onnx value objects
for (int i = 0; i < inputs.Count; i++)
{
NativeMethods.OrtReleaseValue(inputTensors[i]); // this should not release the buffer, but should delete the native tensor object
pinnedBufferHandles[i].Dispose();
}
}
}
/// <summary>
/// Runs the loaded model for the given inputs, and fetches the specified outputs in <paramref name="outputNames". Uses the given RunOptions for this run./>.
/// </summary>
/// <param name="inputs"></param>
/// <param name="outputNames"></param>
/// <param name="options"></param>
/// <returns>Output Tensors in a Collection of NamedOnnxValue. User must dispose the output.</returns>
public IDisposableReadOnlyCollection <DisposableNamedOnnxValue> Run(IReadOnlyCollection <NamedOnnxValue> inputs, IReadOnlyCollection <string> outputNames, RunOptions options)
{
var inputNames = new string[inputs.Count];
var inputTensors = new IntPtr[inputs.Count];
var pinnedBufferHandles = new System.Buffers.MemoryHandle[inputs.Count];
int inputIndex = 0;
foreach (var input in inputs)
{
inputNames[inputIndex] = input.Name;
// create Tensor from the input if feasible, else throw notsupported exception for now
input.ToNativeOnnxValue(out inputTensors[inputIndex],
out pinnedBufferHandles[inputIndex]);
inputIndex++;
}
string[] outputNamesArray = outputNames.ToArray();
IntPtr[] outputValueArray = new IntPtr[outputNames.Count];
IntPtr status = NativeMethods.OrtRun(
this._nativeHandle,
options.Handle,
inputNames,
inputTensors,
(UIntPtr)(inputTensors.Length),
outputNamesArray,
(UIntPtr)outputNames.Count,
outputValueArray /* An array of output value pointers. Array must be allocated by the caller */
);
try
{
NativeApiStatus.VerifySuccess(status);
var result = new DisposableList <DisposableNamedOnnxValue>();
for (uint i = 0; i < outputValueArray.Length; i++)
{
result.Add(DisposableNamedOnnxValue.CreateFromOnnxValue(outputNamesArray[i], outputValueArray[i]));
}
return(result);
}
catch (OnnxRuntimeException e)
{
//clean up the individual output tensors if it is not null;
for (uint i = 0; i < outputValueArray.Length; i++)
{
if (outputValueArray[i] != IntPtr.Zero)
{
NativeMethods.OrtReleaseValue(outputValueArray[i]);
}
}
throw e;
}
finally
{
inputIndex = 0;
foreach (var input in inputs)
{
// For NamedOnnxValue, always unpin the input buffers, and delete the native Onnx value objects
// For DisposableNamedOnnxValue, the user needs to do this by invoking Dispose
if (input.GetType() == typeof(NamedOnnxValue))
{
NativeMethods.OrtReleaseValue(inputTensors[inputIndex]); // For elementary type Tensors, this should not release the buffer, but should delete the native tensor object.
// For string tensors, this releases the native memory allocated for the tensor, including the buffer
pinnedBufferHandles[inputIndex].Dispose();
}
inputIndex++;
}
}
}
