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25 lines
1.3 KiB
Diff
25 lines
1.3 KiB
Diff
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--- a/libraries/akaze/src/nldiffusion_functions.cpp
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+++ b/libraries/akaze/src/nldiffusion_functions.cpp
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@@ -222,8 +222,8 @@ void halfsample_image(const RowMatrixXf& src, RowMatrixXf& dst) {
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// Do the whole resampling in one pass by using neighboring values. First, we
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// compute the borders.
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- const double x_kernel_size = static_cast<double>(src.cols()) / dst.cols();
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- const double y_kernel_size = static_cast<double>(src.rows()) / dst.rows();
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+ const int x_kernel_size = static_cast<double>(src.cols()) / dst.cols();
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+ const int y_kernel_size = static_cast<double>(src.rows()) / dst.rows();
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// Do simple linear interpolation.
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if (x_kernel_size == 2 && y_kernel_size == 2) {
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@@ -237,8 +237,8 @@ void halfsample_image(const RowMatrixXf& src, RowMatrixXf& dst) {
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return;
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}
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- const double x_kernel_clamped_size = static_cast<int>(ceil(x_kernel_size));
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- const double y_kernel_clamped_size = static_cast<int>(ceil(y_kernel_size));
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+ const int x_kernel_clamped_size = static_cast<int>(ceil(static_cast<double>(src.cols()) / dst.cols()));
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+ const int y_kernel_clamped_size = static_cast<int>(ceil(static_cast<double>(src.rows()) / dst.rows()));
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// Set up precomputed factor matrices.
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Eigen::RowVectorXf x_kernel_mul(static_cast<int>(x_kernel_clamped_size)),
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