experiments
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@@ -710,7 +710,9 @@ private:
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static bool ocl_threshold( InputArray _src, OutputArray _dst, double & thresh, double maxval, int thresh_type )
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{
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int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type), ktype = CV_MAKE_TYPE(depth, 1);
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int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type),
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kercn = cn <= 4 && cn != 3 ? cn : ocl::predictOptimalVectorWidth(_src, _dst),
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ktype = CV_MAKE_TYPE(depth, kercn);
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bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
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if ( !(thresh_type == THRESH_BINARY || thresh_type == THRESH_BINARY_INV || thresh_type == THRESH_TRUNC ||
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@@ -733,11 +735,11 @@ static bool ocl_threshold( InputArray _src, OutputArray _dst, double & thresh, d
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if (depth <= CV_32S)
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thresh = cvFloor(thresh);
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k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst, cn),
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ocl::KernelArg::Constant(Mat(1, 1, ktype, thresh)),
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ocl::KernelArg::Constant(Mat(1, 1, ktype, maxval)));
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k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst, cn, kercn),
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ocl::KernelArg::Constant(Mat(1, 1, ktype, Scalar::all(thresh))),
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ocl::KernelArg::Constant(Mat(1, 1, ktype, Scalar::all(maxval))));
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size_t globalsize[2] = { dst.cols * cn, dst.rows };
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size_t globalsize[2] = { dst.cols * cn / kercn, dst.rows };
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return k.run(2, globalsize, NULL, false);
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}
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