bendns' repos / fimg
fast image operations
Diffstat (limited to 'src/scale/algorithms.rs')
-rw-r--r--src/scale/algorithms.rs113
1 files changed, 0 insertions, 113 deletions
diff --git a/src/scale/algorithms.rs b/src/scale/algorithms.rs
deleted file mode 100644
index eaec38c..0000000
--- a/src/scale/algorithms.rs
+++ /dev/null
@@ -1,113 +0,0 @@
-use super::{traits::*, *};
-use std::num::NonZeroU32;
-
-/// [Nearest Neighbor](https://en.wikipedia.org/wiki/Nearest-neighbor_interpolation) image scaling algorithm.
-pub struct Nearest;
-
-impl ScalingAlgorithm for Nearest {
- /// Can be used on non opaque too! (Nearest is special like that).
- fn scale_opaque<const N: usize>(
- i: Image<&[u8], N>,
- w: NonZeroU32,
- h: NonZeroU32,
- ) -> Image<std::boxed::Box<[u8]>, N>
- where
- ChannelCount<N>: ToImageView<N>,
- {
- let mut dst = fr::Image::new(w, h);
- // SAFETY: swear, the pixel types are the same
- unsafe {
- fr::Resizer::new(fr::ResizeAlg::Nearest)
- .resize(&ChannelCount::<N>::wrap(i), &mut dst.view_mut())
- };
-
- // SAFETY: ctor
- unsafe { Image::new(dst.width(), dst.height(), dst.into_vec().into()) }
- }
-
- #[inline]
- fn scale_transparent<const N: usize>(
- i: Image<&mut [u8], N>,
- w: NonZeroU32,
- h: NonZeroU32,
- ) -> Image<std::boxed::Box<[u8]>, N>
- where
- ChannelCount<N>: AlphaDiv<N>,
- {
- Self::scale_opaque(i.as_ref(), w, h)
- }
-}
-
-macro_rules! alg {
- ($for:ident) => {
- impl ScalingAlgorithm for $for {
- fn scale_opaque<const N: usize>(
- i: Image<&[u8], N>,
- w: NonZeroU32,
- h: NonZeroU32,
- ) -> Image<std::boxed::Box<[u8]>, N>
- where
- ChannelCount<N>: ToImageView<N>,
- {
- let mut dst = fr::Image::new(w, h);
- // SAFETY: swear, the pixel types are the same
- unsafe {
- fr::Resizer::new(fr::ResizeAlg::Convolution(fr::FilterType::$for))
- .resize(&ChannelCount::<N>::wrap(i), &mut dst.view_mut())
- };
-
- // SAFETY: ctor
- unsafe { Image::new(dst.width(), dst.height(), dst.into_vec().into()) }
- }
-
- fn scale_transparent<const N: usize>(
- i: Image<&mut [u8], N>,
- w: NonZeroU32,
- h: NonZeroU32,
- ) -> Image<std::boxed::Box<[u8]>, N>
- where
- ChannelCount<N>: AlphaDiv<N>,
- {
- let mut dst = fr::Image::new(w, h);
- // SAFETY: yes
- unsafe {
- fr::Resizer::new(fr::ResizeAlg::Convolution(fr::FilterType::$for))
- .resize(&ChannelCount::<N>::handle(i).view(), &mut dst.view_mut())
- }
-
- ChannelCount::<N>::unhandle(&mut dst);
-
- // SAFETY: ctor
- unsafe { Image::new(dst.width(), dst.height(), dst.into_vec().into()) }
- }
- }
- };
-}
-
-/// [Lanczos](https://en.wikipedia.org/wiki/Lanczos_resampling) scaling with a filter size (*a*) of 3.
-pub struct Lanczos3 {}
-alg!(Lanczos3);
-
-/// [Catmull-Rom](https://en.wikipedia.org/wiki/Centripetal_Catmull%E2%80%93Rom_spline) bicubic filtering.
-pub struct CatmullRom {}
-alg!(CatmullRom);
-
-/// Linear interpolation.
-pub struct Bilinear {}
-alg!(Bilinear);
-
-/// The opposite of [`Nearest`].
-pub struct Box {}
-alg!(Box);
-
-/// Hamming filtering has the same performance as a [`Bilinear`] filter, while
-/// providing image (downscaling) quality comparable to bicubic filters like
-/// [`CatmullRom`] or [`Mitchell`]. Creates a sharper image than [`Bilinear`] filtering,
-/// and doesn't have dislocations on local level like [`Box`] suffers from.
-/// Not recommended for upscaling.
-pub struct Hamming {}
-alg!(Hamming);
-
-/// [Mitchell–Netravali](https://en.wikipedia.org/wiki/Mitchell%E2%80%93Netravali_filters) bicubic filtering.
-pub struct Mitchell {}
-alg!(Mitchell);