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dnn: don't use Mat expressions with async UMat functions

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This commit is contained in:
Alexander Alekhin 2018-10-05 17:06:50 +03:00
parent 0101fa789c
commit 634dd656d5
1 changed files with 12 additions and 2 deletions
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14
modules/dnn/src/dnn.cpp
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@ -483,6 +483,7 @@ struct DataLayer : public Layer
}
#ifdef HAVE_OPENCL
std::vector<Mat> tmp_expressions;
bool forward_ocl(InputArrayOfArrays, OutputArrayOfArrays outputs_, OutputArrayOfArrays internals_)
{
// Supported modes:
@ -493,8 +494,11 @@ struct DataLayer : public Layer
std::vector<UMat> outputs;
outputs_.getUMatVector(outputs);
tmp_expressions.clear();
for (int i = 0; i < inputsData.size(); ++i)
{
Mat inputData = inputsData[i];
double scale = scaleFactors[i];
Scalar& mean = means[i];
@ -508,7 +512,10 @@ struct DataLayer : public Layer
if (outputs_.depth() == CV_16S)
{
if (singleMean)
convertFp16(scale * (inputsData[i] - mean[0]), outputs[i]);
{
tmp_expressions.push_back(Mat(scale * (inputsData[i] - mean[0])));
convertFp16(tmp_expressions.back(), outputs[i]);
}
else
{
for (int n = 0; n < inputsData[i].size[0]; ++n)
@ -521,7 +528,8 @@ struct DataLayer : public Layer
plane[1] = Range(c, c + 1);
UMat out = outputs[i](plane).reshape(1, inp.dims, inp.size);
convertFp16(scale * (inp - mean[c]), out);
tmp_expressions.push_back(scale * (inp - mean[c]));
convertFp16(tmp_expressions.back(), out);
}
}
}
@ -529,7 +537,9 @@ struct DataLayer : public Layer
{
CV_Assert(outputs_.depth() == CV_32F);
if (singleMean)
{
inputsData[i].convertTo(outputs[i], CV_32F, scale, -mean[0] * scale);
}
else
{
for (int n = 0; n < inputsData[i].size[0]; ++n)