/// <summary>
/// Private Constructor
/// </summary>
Camera()
{
try
{
// pre-allocate and initialize the variables and data structures for brightness correction
imgGPU = worker.Malloc <byte>(new byte[640 * 640]);
meanImg = worker.Malloc <float>(new float[640 * 640]);
addReduce = DeviceSumModuleF32.Default.Create(numPixels);
correctionFactor = worker.Malloc <float>(640 * 640);
float[] temp = new float[640 * 640];
for (int i = 0; i < temp.Length; i++)
{
temp[i] = 1;
}
correctionFactor.Scatter(temp);
scalarOutput = worker.Malloc <float>(1);
if (File.Exists("correctionFactor.dat"))
{
FileStream stream = new FileStream("correctionFactor.dat", FileMode.Open);
byte[] buffer = new byte[640 * 640 * 4];
stream.Read(buffer, 0, (int)Math.Min(buffer.Length, stream.Length));
for (int i = 0; i < 640 * 640; i++)
{
temp[i] = BitConverter.ToSingle(buffer, 4 * i);
}
stream.Close();
correctionFactor.Scatter(temp);
}
// initialize CUDA parameters
var blockDims = new dim3(32, 32);
var gridDims = new dim3(Common.divup(640, blockDims.x), Common.divup(640, blockDims.y));
lp = new LaunchParam(gridDims, blockDims);
// set up the camera parameters and events
provider = new IduleProviderCsCam(0);
provider.Initialize();
if (provider.IsConnected)
{
provider.ImageTransaction += provider_ImageTransaction;
provider.Interrupt += provider_Interrupt;
provider.Exception += camera_Exception;
provider.WriteRegister(new NanEyeGSRegisterPayload(false, 0x05, true, 0, prescaler));
provider.WriteRegister(new NanEyeGSRegisterPayload(false, 0x06, true, 0, exposure));
ProcessingWrapper.pr[0].ReduceProcessing = true;
}
}
catch (Exception ex) { OnError(ex.Message); }
}
protected override bool Execute(Assignment assignment, ILValue <T> output)
{
var input = assignment.GetInput(Input).ToRValue();
var reduce = Reduction;
var reductionIndices = ReductionIndices;
var shape = Shape;
// unit stride case and reduction is full reduction (to scalar)
if (input.Layout.IsFullyUnitStride && shape.Rank == 0)
{
var length = input.Layout.Shape.Length;
Util.EnsureTrue(length > 0L);
var read = input.BufferReader.GetFlatReader1();
var write = output.Buffer.FlatWriter1;
if (assignment.Context.Type == ContextType.Gpu)
{
var stream = assignment.Context.ToGpuContext().Stream;
var numItems = (int)length;
Func <int, T> sourceOp = i => read(i);
Action <int, T> outputOp = (i, value) => write(i, value);
// first pass, get the size of temp memory
var tempStorageSize = 0;
DeviceReduce.Reduce(stream, new deviceptr <byte>(), ref tempStorageSize, numItems, sourceOp, outputOp, reduce);
// now allocate temp memory
using (var tempMemoryRcpt = assignment.Context.Device.ToGpuDevice().MemoryRepository.Acquire <byte>(tempStorageSize))
{
DeviceReduce.Reduce(stream, tempMemoryRcpt.Memory.Ptr, ref tempStorageSize, numItems, sourceOp, outputOp, reduce);
}
return(true);
}
if (assignment.Context.Type == ContextType.Cpu)
{
var acc = read(0L);
for (var i = 1L; i < length; ++i)
{
acc = reduce(acc, read(i));
}
write(0L, acc);
return(true);
}
}
// currently we only support matrix partial reduce, need TODO to fix this with more generic cases
if (input.Layout.IsFullyUnitStride && input.Layout.Rank == 2 && reductionIndices.Length == 1)
{
var rows = input.Layout.Shape[0];
var cols = input.Layout.Shape[1];
var read = input.BufferReader.GetReader2();
var write = output.Buffer.FlatWriter1;
if (reductionIndices[0] == 1)
{
if (assignment.Context.Type == ContextType.Gpu)
{
var stream = assignment.Context.ToGpuContext().Stream;
var numSegments = (int)rows;
var numItems = (int)cols;
Func <int, int, T> sourceOp = (i, j) => read(i, j);
Action <int, int, T> outputOp = (i, _, value) => write(i, value);
// first pass, get the size of temp memory
var tempStorageSize = 0;
DeviceReduce.Reduce(stream, new deviceptr <byte>(), ref tempStorageSize, numSegments, numItems, sourceOp, outputOp, reduce);
// now allocate temp memory
// TODO: move to assigmnet, manage the temp memory
using (var tempMemoryRcpt = assignment.Context.Device.ToGpuDevice().MemoryRepository.Acquire <byte>(tempStorageSize))
{
DeviceReduce.Reduce(stream, tempMemoryRcpt.Memory.Ptr, ref tempStorageSize, numSegments, numItems, sourceOp, outputOp, reduce);
}
return(true);
}
if (assignment.Context.Type == ContextType.Cpu)
{
for (var row = 0L; row < rows; ++row)
{
var acc = read(row, 0L);
for (var col = 1L; col < cols; ++col)
{
acc = reduce(acc, read(row, col));
}
write(row, acc);
}
return(true);
}
}
if (reductionIndices[0] == 0)
{
if (assignment.Context.Type == ContextType.Gpu)
{
var stream = assignment.Context.ToGpuContext().Stream;
// This is a quick fix, it is not good performance
stream.LongFor(0L, cols, col =>
{
var acc = read(0L, col);
for (var row = 1L; row < rows; ++row)
{
acc = reduce(acc, read(row, col));
}
write(col, acc);
});
return(true);
}
if (assignment.Context.Type == ContextType.Cpu)
{
for (var col = 0L; col < cols; ++col)
{
var acc = read(0L, col);
for (var row = 1L; row < rows; ++row)
{
acc = reduce(acc, read(row, col));
}
write(col, acc);
}
return(true);
}
}
}
return(false);
}
