Initial vendor packages

Signed-off-by: Valentin Popov <valentin@popov.link>

1 files changed, 1228 insertions, 0 deletions

diff --git a/vendor/image/src/imageops/sample.rs b/vendor/image/src/imageops/sample.rs
new file mode 100644
index 0000000..a362f83
--- /dev/null
+++ b/vendor/image/src/imageops/sample.rs
@@ -0,0 +1,1228 @@
+//! Functions and filters for the sampling of pixels.
+
+// See http://cs.brown.edu/courses/cs123/lectures/08_Image_Processing_IV.pdf
+// for some of the theory behind image scaling and convolution
+
+use std::f32;
+
+use num_traits::{NumCast, ToPrimitive, Zero};
+
+use crate::image::{GenericImage, GenericImageView};
+use crate::traits::{Enlargeable, Pixel, Primitive};
+use crate::utils::clamp;
+use crate::{ImageBuffer, Rgba32FImage};
+
+/// Available Sampling Filters.
+///
+/// ## Examples
+///
+/// To test the different sampling filters on a real example, you can find two
+/// examples called
+/// [`scaledown`](https://github.com/image-rs/image/tree/master/examples/scaledown)
+/// and
+/// [`scaleup`](https://github.com/image-rs/image/tree/master/examples/scaleup)
+/// in the `examples` directory of the crate source code.
+///
+/// Here is a 3.58 MiB
+/// [test image](https://github.com/image-rs/image/blob/master/examples/scaledown/test.jpg)
+/// that has been scaled down to 300x225 px:
+///
+/// <!-- NOTE: To test new test images locally, replace the GitHub path with `../../../docs/` -->
+/// <div style="display: flex; flex-wrap: wrap; align-items: flex-start;">
+///   <div style="margin: 0 8px 8px 0;">
+///     <img src="https://raw.githubusercontent.com/image-rs/image/master/examples/scaledown/scaledown-test-near.png" title="Nearest"><br>
+///     Nearest Neighbor
+///   </div>
+///   <div style="margin: 0 8px 8px 0;">
+///     <img src="https://raw.githubusercontent.com/image-rs/image/master/examples/scaledown/scaledown-test-tri.png" title="Triangle"><br>
+///     Linear: Triangle
+///   </div>
+///   <div style="margin: 0 8px 8px 0;">
+///     <img src="https://raw.githubusercontent.com/image-rs/image/master/examples/scaledown/scaledown-test-cmr.png" title="CatmullRom"><br>
+///     Cubic: Catmull-Rom
+///   </div>
+///   <div style="margin: 0 8px 8px 0;">
+///     <img src="https://raw.githubusercontent.com/image-rs/image/master/examples/scaledown/scaledown-test-gauss.png" title="Gaussian"><br>
+///     Gaussian
+///   </div>
+///   <div style="margin: 0 8px 8px 0;">
+///     <img src="https://raw.githubusercontent.com/image-rs/image/master/examples/scaledown/scaledown-test-lcz2.png" title="Lanczos3"><br>
+///     Lanczos with window 3
+///   </div>
+/// </div>
+///
+/// ## Speed
+///
+/// Time required to create each of the examples above, tested on an Intel
+/// i7-4770 CPU with Rust 1.37 in release mode:
+///
+/// <table style="width: auto;">
+///   <tr>
+///     <th>Nearest</th>
+///     <td>31 ms</td>
+///   </tr>
+///   <tr>
+///     <th>Triangle</th>
+///     <td>414 ms</td>
+///   </tr>
+///   <tr>
+///     <th>CatmullRom</th>
+///     <td>817 ms</td>
+///   </tr>
+///   <tr>
+///     <th>Gaussian</th>
+///     <td>1180 ms</td>
+///   </tr>
+///   <tr>
+///     <th>Lanczos3</th>
+///     <td>1170 ms</td>
+///   </tr>
+/// </table>
+#[derive(Clone, Copy, Debug, PartialEq)]
+pub enum FilterType {
+    /// Nearest Neighbor
+    Nearest,
+
+    /// Linear Filter
+    Triangle,
+
+    /// Cubic Filter
+    CatmullRom,
+
+    /// Gaussian Filter
+    Gaussian,
+
+    /// Lanczos with window 3
+    Lanczos3,
+}
+
+/// A Representation of a separable filter.
+pub(crate) struct Filter<'a> {
+    /// The filter's filter function.
+    pub(crate) kernel: Box<dyn Fn(f32) -> f32 + 'a>,
+
+    /// The window on which this filter operates.
+    pub(crate) support: f32,
+}
+
+struct FloatNearest(f32);
+
+// to_i64, to_u64, and to_f64 implicitly affect all other lower conversions.
+// Note that to_f64 by default calls to_i64 and thus needs to be overridden.
+impl ToPrimitive for FloatNearest {
+    // to_{i,u}64 is required, to_{i,u}{8,16} are useful.
+    // If a usecase for full 32 bits is found its trivial to add
+    fn to_i8(&self) -> Option<i8> {
+        self.0.round().to_i8()
+    }
+    fn to_i16(&self) -> Option<i16> {
+        self.0.round().to_i16()
+    }
+    fn to_i64(&self) -> Option<i64> {
+        self.0.round().to_i64()
+    }
+    fn to_u8(&self) -> Option<u8> {
+        self.0.round().to_u8()
+    }
+    fn to_u16(&self) -> Option<u16> {
+        self.0.round().to_u16()
+    }
+    fn to_u64(&self) -> Option<u64> {
+        self.0.round().to_u64()
+    }
+    fn to_f64(&self) -> Option<f64> {
+        self.0.to_f64()
+    }
+}
+
+// sinc function: the ideal sampling filter.
+fn sinc(t: f32) -> f32 {
+    let a = t * f32::consts::PI;
+
+    if t == 0.0 {
+        1.0
+    } else {
+        a.sin() / a
+    }
+}
+
+// lanczos kernel function. A windowed sinc function.
+fn lanczos(x: f32, t: f32) -> f32 {
+    if x.abs() < t {
+        sinc(x) * sinc(x / t)
+    } else {
+        0.0
+    }
+}
+
+// Calculate a splice based on the b and c parameters.
+// from authors Mitchell and Netravali.
+fn bc_cubic_spline(x: f32, b: f32, c: f32) -> f32 {
+    let a = x.abs();
+
+    let k = if a < 1.0 {
+        (12.0 - 9.0 * b - 6.0 * c) * a.powi(3)
+            + (-18.0 + 12.0 * b + 6.0 * c) * a.powi(2)
+            + (6.0 - 2.0 * b)
+    } else if a < 2.0 {
+        (-b - 6.0 * c) * a.powi(3)
+            + (6.0 * b + 30.0 * c) * a.powi(2)
+            + (-12.0 * b - 48.0 * c) * a
+            + (8.0 * b + 24.0 * c)
+    } else {
+        0.0
+    };
+
+    k / 6.0
+}
+
+/// The Gaussian Function.
+/// ```r``` is the standard deviation.
+pub(crate) fn gaussian(x: f32, r: f32) -> f32 {
+    ((2.0 * f32::consts::PI).sqrt() * r).recip() * (-x.powi(2) / (2.0 * r.powi(2))).exp()
+}
+
+/// Calculate the lanczos kernel with a window of 3
+pub(crate) fn lanczos3_kernel(x: f32) -> f32 {
+    lanczos(x, 3.0)
+}
+
+/// Calculate the gaussian function with a
+/// standard deviation of 0.5
+pub(crate) fn gaussian_kernel(x: f32) -> f32 {
+    gaussian(x, 0.5)
+}
+
+/// Calculate the Catmull-Rom cubic spline.
+/// Also known as a form of `BiCubic` sampling in two dimensions.
+pub(crate) fn catmullrom_kernel(x: f32) -> f32 {
+    bc_cubic_spline(x, 0.0, 0.5)
+}
+
+/// Calculate the triangle function.
+/// Also known as `BiLinear` sampling in two dimensions.
+pub(crate) fn triangle_kernel(x: f32) -> f32 {
+    if x.abs() < 1.0 {
+        1.0 - x.abs()
+    } else {
+        0.0
+    }
+}
+
+/// Calculate the box kernel.
+/// Only pixels inside the box should be considered, and those
+/// contribute equally.  So this method simply returns 1.
+pub(crate) fn box_kernel(_x: f32) -> f32 {
+    1.0
+}
+
+// Sample the rows of the supplied image using the provided filter.
+// The height of the image remains unchanged.
+// ```new_width``` is the desired width of the new image
+// ```filter``` is the filter to use for sampling.
+// ```image``` is not necessarily Rgba and the order of channels is passed through.
+fn horizontal_sample<P, S>(
+    image: &Rgba32FImage,
+    new_width: u32,
+    filter: &mut Filter,
+) -> ImageBuffer<P, Vec<S>>
+where
+    P: Pixel<Subpixel = S> + 'static,
+    S: Primitive + 'static,
+{
+    let (width, height) = image.dimensions();
+    let mut out = ImageBuffer::new(new_width, height);
+    let mut ws = Vec::new();
+
+    let max: f32 = NumCast::from(S::DEFAULT_MAX_VALUE).unwrap();
+    let min: f32 = NumCast::from(S::DEFAULT_MIN_VALUE).unwrap();
+    let ratio = width as f32 / new_width as f32;
+    let sratio = if ratio < 1.0 { 1.0 } else { ratio };
+    let src_support = filter.support * sratio;
+
+    for outx in 0..new_width {
+        // Find the point in the input image corresponding to the centre
+        // of the current pixel in the output image.
+        let inputx = (outx as f32 + 0.5) * ratio;
+
+        // Left and right are slice bounds for the input pixels relevant
+        // to the output pixel we are calculating.  Pixel x is relevant
+        // if and only if (x >= left) && (x < right).
+
+        // Invariant: 0 <= left < right <= width
+
+        let left = (inputx - src_support).floor() as i64;
+        let left = clamp(left, 0, <i64 as From<_>>::from(width) - 1) as u32;
+
+        let right = (inputx + src_support).ceil() as i64;
+        let right = clamp(
+            right,
+            <i64 as From<_>>::from(left) + 1,
+            <i64 as From<_>>::from(width),
+        ) as u32;
+
+        // Go back to left boundary of pixel, to properly compare with i
+        // below, as the kernel treats the centre of a pixel as 0.
+        let inputx = inputx - 0.5;
+
+        ws.clear();
+        let mut sum = 0.0;
+        for i in left..right {
+            let w = (filter.kernel)((i as f32 - inputx) / sratio);
+            ws.push(w);
+            sum += w;
+        }
+        ws.iter_mut().for_each(|w| *w /= sum);
+
+        for y in 0..height {
+            let mut t = (0.0, 0.0, 0.0, 0.0);
+
+            for (i, w) in ws.iter().enumerate() {
+                let p = image.get_pixel(left + i as u32, y);
+
+                #[allow(deprecated)]
+                let vec = p.channels4();
+
+                t.0 += vec.0 * w;
+                t.1 += vec.1 * w;
+                t.2 += vec.2 * w;
+                t.3 += vec.3 * w;
+            }
+
+            #[allow(deprecated)]
+            let t = Pixel::from_channels(
+                NumCast::from(FloatNearest(clamp(t.0, min, max))).unwrap(),
+                NumCast::from(FloatNearest(clamp(t.1, min, max))).unwrap(),
+                NumCast::from(FloatNearest(clamp(t.2, min, max))).unwrap(),
+                NumCast::from(FloatNearest(clamp(t.3, min, max))).unwrap(),
+            );
+
+            out.put_pixel(outx, y, t);
+        }
+    }
+
+    out
+}
+
+/// Linearly sample from an image using coordinates in [0, 1].
+pub fn sample_bilinear<P: Pixel>(
+    img: &impl GenericImageView<Pixel = P>,
+    u: f32,
+    v: f32,
+) -> Option<P> {
+    if ![u, v].iter().all(|c| (0.0..=1.0).contains(c)) {
+        return None;
+    }
+
+    let (w, h) = img.dimensions();
+    if w == 0 || h == 0 {
+        return None;
+    }
+
+    let ui = w as f32 * u - 0.5;
+    let vi = h as f32 * v - 0.5;
+    interpolate_bilinear(
+        img,
+        ui.max(0.).min((w - 1) as f32),
+        vi.max(0.).min((h - 1) as f32),
+    )
+}
+
+/// Sample from an image using coordinates in [0, 1], taking the nearest coordinate.
+pub fn sample_nearest<P: Pixel>(
+    img: &impl GenericImageView<Pixel = P>,
+    u: f32,
+    v: f32,
+) -> Option<P> {
+    if ![u, v].iter().all(|c| (0.0..=1.0).contains(c)) {
+        return None;
+    }
+
+    let (w, h) = img.dimensions();
+    let ui = w as f32 * u - 0.5;
+    let ui = ui.max(0.).min((w.saturating_sub(1)) as f32);
+
+    let vi = h as f32 * v - 0.5;
+    let vi = vi.max(0.).min((h.saturating_sub(1)) as f32);
+    interpolate_nearest(img, ui, vi)
+}
+
+/// Sample from an image using coordinates in [0, w-1] and [0, h-1], taking the
+/// nearest pixel.
+///
+/// Coordinates outside the image bounds will return `None`, however the
+/// behavior for points within half a pixel of the image bounds may change in
+/// the future.
+pub fn interpolate_nearest<P: Pixel>(
+    img: &impl GenericImageView<Pixel = P>,
+    x: f32,
+    y: f32,
+) -> Option<P> {
+    let (w, h) = img.dimensions();
+    if w == 0 || h == 0 {
+        return None;
+    }
+    if !(0.0..=((w - 1) as f32)).contains(&x) {
+        return None;
+    }
+    if !(0.0..=((h - 1) as f32)).contains(&y) {
+        return None;
+    }
+
+    Some(img.get_pixel(x.round() as u32, y.round() as u32))
+}
+
+/// Linearly sample from an image using coordinates in [0, w-1] and [0, h-1].
+pub fn interpolate_bilinear<P: Pixel>(
+    img: &impl GenericImageView<Pixel = P>,
+    x: f32,
+    y: f32,
+) -> Option<P> {
+    let (w, h) = img.dimensions();
+    if w == 0 || h == 0 {
+        return None;
+    }
+    if !(0.0..=((w - 1) as f32)).contains(&x) {
+        return None;
+    }
+    if !(0.0..=((h - 1) as f32)).contains(&y) {
+        return None;
+    }
+
+    let uf = x.floor();
+    let vf = y.floor();
+    let uc = (x + 1.).min((w - 1) as f32);
+    let vc = (y + 1.).min((h - 1) as f32);
+
+    // clamp coords to the range of the image
+    let coords = [[uf, vf], [uf, vc], [uc, vf], [uc, vc]];
+
+    assert!(coords
+        .iter()
+        .all(|&[u, v]| { img.in_bounds(u as u32, v as u32) }));
+    let samples = coords.map(|[u, v]| img.get_pixel(u as u32, v as u32));
+    assert!(P::CHANNEL_COUNT <= 4);
+
+    // convert samples to f32
+    // currently rgba is the largest one,
+    // so just store as many items as necessary,
+    // because there's not a simple way to be generic over all of them.
+    let [sff, sfc, scf, scc] = samples.map(|s| {
+        let mut out = [0.; 4];
+        for (i, c) in s.channels().iter().enumerate() {
+            out[i] = c.to_f32().unwrap();
+        }
+        out
+    });
+    // weights
+    let [ufw, vfw] = [x - uf, y - vf];
+    let [ucw, vcw] = [1. - ufw, 1. - vfw];
+
+    // https://en.wikipedia.org/wiki/Bilinear_interpolation#Weighted_mean
+    // the distance between pixels is 1 so there is no denominator
+    let wff = ucw * vcw;
+    let wfc = ucw * vfw;
+    let wcf = ufw * vcw;
+    let wcc = ufw * vfw;
+    assert!(f32::abs((wff + wfc + wcf + wcc) - 1.) < 1e-3);
+
+    // hack to get around not being able to construct a generic Pixel
+    let mut out = samples[0];
+    for (i, c) in out.channels_mut().iter_mut().enumerate() {
+        let v = wff * sff[i] + wfc * sfc[i] + wcf * scf[i] + wcc * scc[i];
+        // this rounding may introduce quantization errors,
+        // but cannot do anything about it.
+        *c = <P::Subpixel as NumCast>::from(v.round()).unwrap_or({
+            if v < 0.0 {
+                P::Subpixel::DEFAULT_MIN_VALUE
+            } else {
+                P::Subpixel::DEFAULT_MAX_VALUE
+            }
+        })
+    }
+    Some(out)
+}
+
+// Sample the columns of the supplied image using the provided filter.
+// The width of the image remains unchanged.
+// ```new_height``` is the desired height of the new image
+// ```filter``` is the filter to use for sampling.
+// The return value is not necessarily Rgba, the underlying order of channels in ```image``` is
+// preserved.
+fn vertical_sample<I, P, S>(image: &I, new_height: u32, filter: &mut Filter) -> Rgba32FImage
+where
+    I: GenericImageView<Pixel = P>,
+    P: Pixel<Subpixel = S> + 'static,
+    S: Primitive + 'static,
+{
+    let (width, height) = image.dimensions();
+    let mut out = ImageBuffer::new(width, new_height);
+    let mut ws = Vec::new();
+
+    let ratio = height as f32 / new_height as f32;
+    let sratio = if ratio < 1.0 { 1.0 } else { ratio };
+    let src_support = filter.support * sratio;
+
+    for outy in 0..new_height {
+        // For an explanation of this algorithm, see the comments
+        // in horizontal_sample.
+        let inputy = (outy as f32 + 0.5) * ratio;
+
+        let left = (inputy - src_support).floor() as i64;
+        let left = clamp(left, 0, <i64 as From<_>>::from(height) - 1) as u32;
+
+        let right = (inputy + src_support).ceil() as i64;
+        let right = clamp(
+            right,
+            <i64 as From<_>>::from(left) + 1,
+            <i64 as From<_>>::from(height),
+        ) as u32;
+
+        let inputy = inputy - 0.5;
+
+        ws.clear();
+        let mut sum = 0.0;
+        for i in left..right {
+            let w = (filter.kernel)((i as f32 - inputy) / sratio);
+            ws.push(w);
+            sum += w;
+        }
+        ws.iter_mut().for_each(|w| *w /= sum);
+
+        for x in 0..width {
+            let mut t = (0.0, 0.0, 0.0, 0.0);
+
+            for (i, w) in ws.iter().enumerate() {
+                let p = image.get_pixel(x, left + i as u32);
+
+                #[allow(deprecated)]
+                let (k1, k2, k3, k4) = p.channels4();
+                let vec: (f32, f32, f32, f32) = (
+                    NumCast::from(k1).unwrap(),
+                    NumCast::from(k2).unwrap(),
+                    NumCast::from(k3).unwrap(),
+                    NumCast::from(k4).unwrap(),
+                );
+
+                t.0 += vec.0 * w;
+                t.1 += vec.1 * w;
+                t.2 += vec.2 * w;
+                t.3 += vec.3 * w;
+            }
+
+            #[allow(deprecated)]
+            // This is not necessarily Rgba.
+            let t = Pixel::from_channels(t.0, t.1, t.2, t.3);
+
+            out.put_pixel(x, outy, t);
+        }
+    }
+
+    out
+}
+
+/// Local struct for keeping track of pixel sums for fast thumbnail averaging
+struct ThumbnailSum<S: Primitive + Enlargeable>(S::Larger, S::Larger, S::Larger, S::Larger);
+
+impl<S: Primitive + Enlargeable> ThumbnailSum<S> {
+    fn zeroed() -> Self {
+        ThumbnailSum(
+            S::Larger::zero(),
+            S::Larger::zero(),
+            S::Larger::zero(),
+            S::Larger::zero(),
+        )
+    }
+
+    fn sample_val(val: S) -> S::Larger {
+        <S::Larger as NumCast>::from(val).unwrap()
+    }
+
+    fn add_pixel<P: Pixel<Subpixel = S>>(&mut self, pixel: P) {
+        #[allow(deprecated)]
+        let pixel = pixel.channels4();
+        self.0 += Self::sample_val(pixel.0);
+        self.1 += Self::sample_val(pixel.1);
+        self.2 += Self::sample_val(pixel.2);
+        self.3 += Self::sample_val(pixel.3);
+    }
+}
+
+/// Resize the supplied image to the specific dimensions.
+///
+/// For downscaling, this method uses a fast integer algorithm where each source pixel contributes
+/// to exactly one target pixel.  May give aliasing artifacts if new size is close to old size.
+///
+/// In case the current width is smaller than the new width or similar for the height, another
+/// strategy is used instead.  For each pixel in the output, a rectangular region of the input is
+/// determined, just as previously.  But when no input pixel is part of this region, the nearest
+/// pixels are interpolated instead.
+///
+/// For speed reasons, all interpolation is performed linearly over the colour values.  It will not
+/// take the pixel colour spaces into account.
+pub fn thumbnail<I, P, S>(image: &I, new_width: u32, new_height: u32) -> ImageBuffer<P, Vec<S>>
+where
+    I: GenericImageView<Pixel = P>,
+    P: Pixel<Subpixel = S> + 'static,
+    S: Primitive + Enlargeable + 'static,
+{
+    let (width, height) = image.dimensions();
+    let mut out = ImageBuffer::new(new_width, new_height);
+
+    let x_ratio = width as f32 / new_width as f32;
+    let y_ratio = height as f32 / new_height as f32;
+
+    for outy in 0..new_height {
+        let bottomf = outy as f32 * y_ratio;
+        let topf = bottomf + y_ratio;
+
+        let bottom = clamp(bottomf.ceil() as u32, 0, height - 1);
+        let top = clamp(topf.ceil() as u32, bottom, height);
+
+        for outx in 0..new_width {
+            let leftf = outx as f32 * x_ratio;
+            let rightf = leftf + x_ratio;
+
+            let left = clamp(leftf.ceil() as u32, 0, width - 1);
+            let right = clamp(rightf.ceil() as u32, left, width);
+
+            let avg = if bottom != top && left != right {
+                thumbnail_sample_block(image, left, right, bottom, top)
+            } else if bottom != top {
+                // && left == right
+                // In the first column we have left == 0 and right > ceil(y_scale) > 0 so this
+                // assertion can never trigger.
+                debug_assert!(
+                    left > 0 && right > 0,
+                    "First output column must have corresponding pixels"
+                );
+
+                let fraction_horizontal = (leftf.fract() + rightf.fract()) / 2.;
+                thumbnail_sample_fraction_horizontal(
+                    image,
+                    right - 1,
+                    fraction_horizontal,
+                    bottom,
+                    top,
+                )
+            } else if left != right {
+                // && bottom == top
+                // In the first line we have bottom == 0 and top > ceil(x_scale) > 0 so this
+                // assertion can never trigger.
+                debug_assert!(
+                    bottom > 0 && top > 0,
+                    "First output row must have corresponding pixels"
+                );
+
+                let fraction_vertical = (topf.fract() + bottomf.fract()) / 2.;
+                thumbnail_sample_fraction_vertical(image, left, right, top - 1, fraction_vertical)
+            } else {
+                // bottom == top && left == right
+                let fraction_horizontal = (topf.fract() + bottomf.fract()) / 2.;
+                let fraction_vertical = (leftf.fract() + rightf.fract()) / 2.;
+
+                thumbnail_sample_fraction_both(
+                    image,
+                    right - 1,
+                    fraction_horizontal,
+                    top - 1,
+                    fraction_vertical,
+                )
+            };
+
+            #[allow(deprecated)]
+            let pixel = Pixel::from_channels(avg.0, avg.1, avg.2, avg.3);
+            out.put_pixel(outx, outy, pixel);
+        }
+    }
+
+    out
+}
+
+/// Get a pixel for a thumbnail where the input window encloses at least a full pixel.
+fn thumbnail_sample_block<I, P, S>(
+    image: &I,
+    left: u32,
+    right: u32,
+    bottom: u32,
+    top: u32,
+) -> (S, S, S, S)
+where
+    I: GenericImageView<Pixel = P>,
+    P: Pixel<Subpixel = S>,
+    S: Primitive + Enlargeable,
+{
+    let mut sum = ThumbnailSum::zeroed();
+
+    for y in bottom..top {
+        for x in left..right {
+            let k = image.get_pixel(x, y);
+            sum.add_pixel(k);
+        }
+    }
+
+    let n = <S::Larger as NumCast>::from((right - left) * (top - bottom)).unwrap();
+    let round = <S::Larger as NumCast>::from(n / NumCast::from(2).unwrap()).unwrap();
+    (
+        S::clamp_from((sum.0 + round) / n),
+        S::clamp_from((sum.1 + round) / n),
+        S::clamp_from((sum.2 + round) / n),
+        S::clamp_from((sum.3 + round) / n),
+    )
+}
+
+/// Get a thumbnail pixel where the input window encloses at least a vertical pixel.
+fn thumbnail_sample_fraction_horizontal<I, P, S>(
+    image: &I,
+    left: u32,
+    fraction_horizontal: f32,
+    bottom: u32,
+    top: u32,
+) -> (S, S, S, S)
+where
+    I: GenericImageView<Pixel = P>,
+    P: Pixel<Subpixel = S>,
+    S: Primitive + Enlargeable,
+{
+    let fract = fraction_horizontal;
+
+    let mut sum_left = ThumbnailSum::zeroed();
+    let mut sum_right = ThumbnailSum::zeroed();
+    for x in bottom..top {
+        let k_left = image.get_pixel(left, x);
+        sum_left.add_pixel(k_left);
+
+        let k_right = image.get_pixel(left + 1, x);
+        sum_right.add_pixel(k_right);
+    }
+
+    // Now we approximate: left/n*(1-fract) + right/n*fract
+    let fact_right = fract / ((top - bottom) as f32);
+    let fact_left = (1. - fract) / ((top - bottom) as f32);
+
+    let mix_left_and_right = |leftv: S::Larger, rightv: S::Larger| {
+        <S as NumCast>::from(
+            fact_left * leftv.to_f32().unwrap() + fact_right * rightv.to_f32().unwrap(),
+        )
+        .expect("Average sample value should fit into sample type")
+    };
+
+    (
+        mix_left_and_right(sum_left.0, sum_right.0),
+        mix_left_and_right(sum_left.1, sum_right.1),
+        mix_left_and_right(sum_left.2, sum_right.2),
+        mix_left_and_right(sum_left.3, sum_right.3),
+    )
+}
+
+/// Get a thumbnail pixel where the input window encloses at least a horizontal pixel.
+fn thumbnail_sample_fraction_vertical<I, P, S>(
+    image: &I,
+    left: u32,
+    right: u32,
+    bottom: u32,
+    fraction_vertical: f32,
+) -> (S, S, S, S)
+where
+    I: GenericImageView<Pixel = P>,
+    P: Pixel<Subpixel = S>,
+    S: Primitive + Enlargeable,
+{
+    let fract = fraction_vertical;
+
+    let mut sum_bot = ThumbnailSum::zeroed();
+    let mut sum_top = ThumbnailSum::zeroed();
+    for x in left..right {
+        let k_bot = image.get_pixel(x, bottom);
+        sum_bot.add_pixel(k_bot);
+
+        let k_top = image.get_pixel(x, bottom + 1);
+        sum_top.add_pixel(k_top);
+    }
+
+    // Now we approximate: bot/n*fract + top/n*(1-fract)
+    let fact_top = fract / ((right - left) as f32);
+    let fact_bot = (1. - fract) / ((right - left) as f32);
+
+    let mix_bot_and_top = |botv: S::Larger, topv: S::Larger| {
+        <S as NumCast>::from(fact_bot * botv.to_f32().unwrap() + fact_top * topv.to_f32().unwrap())
+            .expect("Average sample value should fit into sample type")
+    };
+
+    (
+        mix_bot_and_top(sum_bot.0, sum_top.0),
+        mix_bot_and_top(sum_bot.1, sum_top.1),
+        mix_bot_and_top(sum_bot.2, sum_top.2),
+        mix_bot_and_top(sum_bot.3, sum_top.3),
+    )
+}
+
+/// Get a single pixel for a thumbnail where the input window does not enclose any full pixel.
+fn thumbnail_sample_fraction_both<I, P, S>(
+    image: &I,
+    left: u32,
+    fraction_vertical: f32,
+    bottom: u32,
+    fraction_horizontal: f32,
+) -> (S, S, S, S)
+where
+    I: GenericImageView<Pixel = P>,
+    P: Pixel<Subpixel = S>,
+    S: Primitive + Enlargeable,
+{
+    #[allow(deprecated)]
+    let k_bl = image.get_pixel(left, bottom).channels4();
+    #[allow(deprecated)]
+    let k_tl = image.get_pixel(left, bottom + 1).channels4();
+    #[allow(deprecated)]
+    let k_br = image.get_pixel(left + 1, bottom).channels4();
+    #[allow(deprecated)]
+    let k_tr = image.get_pixel(left + 1, bottom + 1).channels4();
+
+    let frac_v = fraction_vertical;
+    let frac_h = fraction_horizontal;
+
+    let fact_tr = frac_v * frac_h;
+    let fact_tl = frac_v * (1. - frac_h);
+    let fact_br = (1. - frac_v) * frac_h;
+    let fact_bl = (1. - frac_v) * (1. - frac_h);
+
+    let mix = |br: S, tr: S, bl: S, tl: S| {
+        <S as NumCast>::from(
+            fact_br * br.to_f32().unwrap()
+                + fact_tr * tr.to_f32().unwrap()
+                + fact_bl * bl.to_f32().unwrap()
+                + fact_tl * tl.to_f32().unwrap(),
+        )
+        .expect("Average sample value should fit into sample type")
+    };
+
+    (
+        mix(k_br.0, k_tr.0, k_bl.0, k_tl.0),
+        mix(k_br.1, k_tr.1, k_bl.1, k_tl.1),
+        mix(k_br.2, k_tr.2, k_bl.2, k_tl.2),
+        mix(k_br.3, k_tr.3, k_bl.3, k_tl.3),
+    )
+}
+
+/// Perform a 3x3 box filter on the supplied image.
+/// ```kernel``` is an array of the filter weights of length 9.
+pub fn filter3x3<I, P, S>(image: &I, kernel: &[f32]) -> ImageBuffer<P, Vec<S>>
+where
+    I: GenericImageView<Pixel = P>,
+    P: Pixel<Subpixel = S> + 'static,
+    S: Primitive + 'static,
+{
+    // The kernel's input positions relative to the current pixel.
+    let taps: &[(isize, isize)] = &[
+        (-1, -1),
+        (0, -1),
+        (1, -1),
+        (-1, 0),
+        (0, 0),
+        (1, 0),
+        (-1, 1),
+        (0, 1),
+        (1, 1),
+    ];
+
+    let (width, height) = image.dimensions();
+
+    let mut out = ImageBuffer::new(width, height);
+
+    let max = S::DEFAULT_MAX_VALUE;
+    let max: f32 = NumCast::from(max).unwrap();
+
+    let sum = match kernel.iter().fold(0.0, |s, &item| s + item) {
+        x if x == 0.0 => 1.0,
+        sum => sum,
+    };
+    let sum = (sum, sum, sum, sum);
+
+    for y in 1..height - 1 {
+        for x in 1..width - 1 {
+            let mut t = (0.0, 0.0, 0.0, 0.0);
+
+            // TODO: There is no need to recalculate the kernel for each pixel.
+            // Only a subtract and addition is needed for pixels after the first
+            // in each row.
+            for (&k, &(a, b)) in kernel.iter().zip(taps.iter()) {
+                let k = (k, k, k, k);
+                let x0 = x as isize + a;
+                let y0 = y as isize + b;
+
+                let p = image.get_pixel(x0 as u32, y0 as u32);
+
+                #[allow(deprecated)]
+                let (k1, k2, k3, k4) = p.channels4();
+
+                let vec: (f32, f32, f32, f32) = (
+                    NumCast::from(k1).unwrap(),
+                    NumCast::from(k2).unwrap(),
+                    NumCast::from(k3).unwrap(),
+                    NumCast::from(k4).unwrap(),
+                );
+
+                t.0 += vec.0 * k.0;
+                t.1 += vec.1 * k.1;
+                t.2 += vec.2 * k.2;
+                t.3 += vec.3 * k.3;
+            }
+
+            let (t1, t2, t3, t4) = (t.0 / sum.0, t.1 / sum.1, t.2 / sum.2, t.3 / sum.3);
+
+            #[allow(deprecated)]
+            let t = Pixel::from_channels(
+                NumCast::from(clamp(t1, 0.0, max)).unwrap(),
+                NumCast::from(clamp(t2, 0.0, max)).unwrap(),
+                NumCast::from(clamp(t3, 0.0, max)).unwrap(),
+                NumCast::from(clamp(t4, 0.0, max)).unwrap(),
+            );
+
+            out.put_pixel(x, y, t);
+        }
+    }
+
+    out
+}
+
+/// Resize the supplied image to the specified dimensions.
+/// ```nwidth``` and ```nheight``` are the new dimensions.
+/// ```filter``` is the sampling filter to use.
+pub fn resize<I: GenericImageView>(
+    image: &I,
+    nwidth: u32,
+    nheight: u32,
+    filter: FilterType,
+) -> ImageBuffer<I::Pixel, Vec<<I::Pixel as Pixel>::Subpixel>>
+where
+    I::Pixel: 'static,
+    <I::Pixel as Pixel>::Subpixel: 'static,
+{
+    // check if the new dimensions are the same as the old. if they are, make a copy instead of resampling
+    if (nwidth, nheight) == image.dimensions() {
+        let mut tmp = ImageBuffer::new(image.width(), image.height());
+        tmp.copy_from(image, 0, 0).unwrap();
+        return tmp;
+    }
+
+    let mut method = match filter {
+        FilterType::Nearest => Filter {
+            kernel: Box::new(box_kernel),
+            support: 0.0,
+        },
+        FilterType::Triangle => Filter {
+            kernel: Box::new(triangle_kernel),
+            support: 1.0,
+        },
+        FilterType::CatmullRom => Filter {
+            kernel: Box::new(catmullrom_kernel),
+            support: 2.0,
+        },
+        FilterType::Gaussian => Filter {
+            kernel: Box::new(gaussian_kernel),
+            support: 3.0,
+        },
+        FilterType::Lanczos3 => Filter {
+            kernel: Box::new(lanczos3_kernel),
+            support: 3.0,
+        },
+    };
+
+    // Note: tmp is not necessarily actually Rgba
+    let tmp: Rgba32FImage = vertical_sample(image, nheight, &mut method);
+    horizontal_sample(&tmp, nwidth, &mut method)
+}
+
+/// Performs a Gaussian blur on the supplied image.
+/// ```sigma``` is a measure of how much to blur by.
+pub fn blur<I: GenericImageView>(
+    image: &I,
+    sigma: f32,
+) -> ImageBuffer<I::Pixel, Vec<<I::Pixel as Pixel>::Subpixel>>
+where
+    I::Pixel: 'static,
+{
+    let sigma = if sigma <= 0.0 { 1.0 } else { sigma };
+
+    let mut method = Filter {
+        kernel: Box::new(|x| gaussian(x, sigma)),
+        support: 2.0 * sigma,
+    };
+
+    let (width, height) = image.dimensions();
+
+    // Keep width and height the same for horizontal and
+    // vertical sampling.
+    // Note: tmp is not necessarily actually Rgba
+    let tmp: Rgba32FImage = vertical_sample(image, height, &mut method);
+    horizontal_sample(&tmp, width, &mut method)
+}
+
+/// Performs an unsharpen mask on the supplied image.
+/// ```sigma``` is the amount to blur the image by.
+/// ```threshold``` is the threshold for minimal brightness change that will be sharpened.
+///
+/// See <https://en.wikipedia.org/wiki/Unsharp_masking#Digital_unsharp_masking>
+pub fn unsharpen<I, P, S>(image: &I, sigma: f32, threshold: i32) -> ImageBuffer<P, Vec<S>>
+where
+    I: GenericImageView<Pixel = P>,
+    P: Pixel<Subpixel = S> + 'static,
+    S: Primitive + 'static,
+{
+    let mut tmp = blur(image, sigma);
+
+    let max = S::DEFAULT_MAX_VALUE;
+    let max: i32 = NumCast::from(max).unwrap();
+    let (width, height) = image.dimensions();
+
+    for y in 0..height {
+        for x in 0..width {
+            let a = image.get_pixel(x, y);
+            let b = tmp.get_pixel_mut(x, y);
+
+            let p = a.map2(b, |c, d| {
+                let ic: i32 = NumCast::from(c).unwrap();
+                let id: i32 = NumCast::from(d).unwrap();
+
+                let diff = (ic - id).abs();
+
+                if diff > threshold {
+                    let e = clamp(ic + diff, 0, max); // FIXME what does this do for f32? clamp 0-1 integers??
+
+                    NumCast::from(e).unwrap()
+                } else {
+                    c
+                }
+            });
+
+            *b = p;
+        }
+    }
+
+    tmp
+}
+
+#[cfg(test)]
+mod tests {
+    use super::{resize, sample_bilinear, sample_nearest, FilterType};
+    use crate::{GenericImageView, ImageBuffer, RgbImage};
+    #[cfg(feature = "benchmarks")]
+    use test;
+
+    #[bench]
+    #[cfg(all(feature = "benchmarks", feature = "png"))]
+    fn bench_resize(b: &mut test::Bencher) {
+        use std::path::Path;
+        let img = crate::open(&Path::new("./examples/fractal.png")).unwrap();
+        b.iter(|| {
+            test::black_box(resize(&img, 200, 200, FilterType::Nearest));
+        });
+        b.bytes = 800 * 800 * 3 + 200 * 200 * 3;
+    }
+
+    #[test]
+    #[cfg(feature = "png")]
+    fn test_resize_same_size() {
+        use std::path::Path;
+        let img = crate::open(&Path::new("./examples/fractal.png")).unwrap();
+        let resize = img.resize(img.width(), img.height(), FilterType::Triangle);
+        assert!(img.pixels().eq(resize.pixels()))
+    }
+
+    #[test]
+    #[cfg(feature = "png")]
+    fn test_sample_bilinear() {
+        use std::path::Path;
+        let img = crate::open(&Path::new("./examples/fractal.png")).unwrap();
+        assert!(sample_bilinear(&img, 0., 0.).is_some());
+        assert!(sample_bilinear(&img, 1., 0.).is_some());
+        assert!(sample_bilinear(&img, 0., 1.).is_some());
+        assert!(sample_bilinear(&img, 1., 1.).is_some());
+        assert!(sample_bilinear(&img, 0.5, 0.5).is_some());
+
+        assert!(sample_bilinear(&img, 1.2, 0.5).is_none());
+        assert!(sample_bilinear(&img, 0.5, 1.2).is_none());
+        assert!(sample_bilinear(&img, 1.2, 1.2).is_none());
+
+        assert!(sample_bilinear(&img, -0.1, 0.2).is_none());
+        assert!(sample_bilinear(&img, 0.2, -0.1).is_none());
+        assert!(sample_bilinear(&img, -0.1, -0.1).is_none());
+    }
+    #[test]
+    #[cfg(feature = "png")]
+    fn test_sample_nearest() {
+        use std::path::Path;
+        let img = crate::open(&Path::new("./examples/fractal.png")).unwrap();
+        assert!(sample_nearest(&img, 0., 0.).is_some());
+        assert!(sample_nearest(&img, 1., 0.).is_some());
+        assert!(sample_nearest(&img, 0., 1.).is_some());
+        assert!(sample_nearest(&img, 1., 1.).is_some());
+        assert!(sample_nearest(&img, 0.5, 0.5).is_some());
+
+        assert!(sample_nearest(&img, 1.2, 0.5).is_none());
+        assert!(sample_nearest(&img, 0.5, 1.2).is_none());
+        assert!(sample_nearest(&img, 1.2, 1.2).is_none());
+
+        assert!(sample_nearest(&img, -0.1, 0.2).is_none());
+        assert!(sample_nearest(&img, 0.2, -0.1).is_none());
+        assert!(sample_nearest(&img, -0.1, -0.1).is_none());
+    }
+    #[test]
+    fn test_sample_bilinear_correctness() {
+        use crate::Rgba;
+        let img = ImageBuffer::from_fn(2, 2, |x, y| match (x, y) {
+            (0, 0) => Rgba([255, 0, 0, 0]),
+            (0, 1) => Rgba([0, 255, 0, 0]),
+            (1, 0) => Rgba([0, 0, 255, 0]),
+            (1, 1) => Rgba([0, 0, 0, 255]),
+            _ => panic!(),
+        });
+        assert_eq!(sample_bilinear(&img, 0.5, 0.5), Some(Rgba([64; 4])));
+        assert_eq!(sample_bilinear(&img, 0.0, 0.0), Some(Rgba([255, 0, 0, 0])));
+        assert_eq!(sample_bilinear(&img, 0.0, 1.0), Some(Rgba([0, 255, 0, 0])));
+        assert_eq!(sample_bilinear(&img, 1.0, 0.0), Some(Rgba([0, 0, 255, 0])));
+        assert_eq!(sample_bilinear(&img, 1.0, 1.0), Some(Rgba([0, 0, 0, 255])));
+
+        assert_eq!(
+            sample_bilinear(&img, 0.5, 0.0),
+            Some(Rgba([128, 0, 128, 0]))
+        );
+        assert_eq!(
+            sample_bilinear(&img, 0.0, 0.5),
+            Some(Rgba([128, 128, 0, 0]))
+        );
+        assert_eq!(
+            sample_bilinear(&img, 0.5, 1.0),
+            Some(Rgba([0, 128, 0, 128]))
+        );
+        assert_eq!(
+            sample_bilinear(&img, 1.0, 0.5),
+            Some(Rgba([0, 0, 128, 128]))
+        );
+    }
+    #[test]
+    fn test_sample_nearest_correctness() {
+        use crate::Rgba;
+        let img = ImageBuffer::from_fn(2, 2, |x, y| match (x, y) {
+            (0, 0) => Rgba([255, 0, 0, 0]),
+            (0, 1) => Rgba([0, 255, 0, 0]),
+            (1, 0) => Rgba([0, 0, 255, 0]),
+            (1, 1) => Rgba([0, 0, 0, 255]),
+            _ => panic!(),
+        });
+
+        assert_eq!(sample_nearest(&img, 0.0, 0.0), Some(Rgba([255, 0, 0, 0])));
+        assert_eq!(sample_nearest(&img, 0.0, 1.0), Some(Rgba([0, 255, 0, 0])));
+        assert_eq!(sample_nearest(&img, 1.0, 0.0), Some(Rgba([0, 0, 255, 0])));
+        assert_eq!(sample_nearest(&img, 1.0, 1.0), Some(Rgba([0, 0, 0, 255])));
+
+        assert_eq!(sample_nearest(&img, 0.5, 0.5), Some(Rgba([0, 0, 0, 255])));
+        assert_eq!(sample_nearest(&img, 0.5, 0.0), Some(Rgba([0, 0, 255, 0])));
+        assert_eq!(sample_nearest(&img, 0.0, 0.5), Some(Rgba([0, 255, 0, 0])));
+        assert_eq!(sample_nearest(&img, 0.5, 1.0), Some(Rgba([0, 0, 0, 255])));
+        assert_eq!(sample_nearest(&img, 1.0, 0.5), Some(Rgba([0, 0, 0, 255])));
+    }
+
+    #[bench]
+    #[cfg(all(feature = "benchmarks", feature = "tiff"))]
+    fn bench_resize_same_size(b: &mut test::Bencher) {
+        let path = concat!(
+            env!("CARGO_MANIFEST_DIR"),
+            "/tests/images/tiff/testsuite/mandrill.tiff"
+        );
+        let image = crate::open(path).unwrap();
+        b.iter(|| {
+            test::black_box(image.resize(image.width(), image.height(), FilterType::CatmullRom));
+        });
+        b.bytes = (image.width() * image.height() * 3) as u64;
+    }
+
+    #[test]
+    fn test_issue_186() {
+        let img: RgbImage = ImageBuffer::new(100, 100);
+        let _ = resize(&img, 50, 50, FilterType::Lanczos3);
+    }
+
+    #[bench]
+    #[cfg(all(feature = "benchmarks", feature = "tiff"))]
+    fn bench_thumbnail(b: &mut test::Bencher) {
+        let path = concat!(
+            env!("CARGO_MANIFEST_DIR"),
+            "/tests/images/tiff/testsuite/mandrill.tiff"
+        );
+        let image = crate::open(path).unwrap();
+        b.iter(|| {
+            test::black_box(image.thumbnail(256, 256));
+        });
+        b.bytes = 512 * 512 * 4 + 256 * 256 * 4;
+    }
+
+    #[bench]
+    #[cfg(all(feature = "benchmarks", feature = "tiff"))]
+    fn bench_thumbnail_upsize(b: &mut test::Bencher) {
+        let path = concat!(
+            env!("CARGO_MANIFEST_DIR"),
+            "/tests/images/tiff/testsuite/mandrill.tiff"
+        );
+        let image = crate::open(path).unwrap().thumbnail(256, 256);
+        b.iter(|| {
+            test::black_box(image.thumbnail(512, 512));
+        });
+        b.bytes = 512 * 512 * 4 + 256 * 256 * 4;
+    }
+
+    #[bench]
+    #[cfg(all(feature = "benchmarks", feature = "tiff"))]
+    fn bench_thumbnail_upsize_irregular(b: &mut test::Bencher) {
+        let path = concat!(
+            env!("CARGO_MANIFEST_DIR"),
+            "/tests/images/tiff/testsuite/mandrill.tiff"
+        );
+        let image = crate::open(path).unwrap().thumbnail(193, 193);
+        b.iter(|| {
+            test::black_box(image.thumbnail(256, 256));
+        });
+        b.bytes = 193 * 193 * 4 + 256 * 256 * 4;
+    }
+
+    #[test]
+    #[cfg(feature = "png")]
+    fn resize_transparent_image() {
+        use super::FilterType::{CatmullRom, Gaussian, Lanczos3, Nearest, Triangle};
+        use crate::imageops::crop_imm;
+        use crate::RgbaImage;
+
+        fn assert_resize(image: &RgbaImage, filter: FilterType) {
+            let resized = resize(image, 16, 16, filter);
+            let cropped = crop_imm(&resized, 5, 5, 6, 6).to_image();
+            for pixel in cropped.pixels() {
+                let alpha = pixel.0[3];
+                assert!(
+                    alpha != 254 && alpha != 253,
+                    "alpha value: {}, {:?}",
+                    alpha,
+                    filter
+                );
+            }
+        }
+
+        let path = concat!(
+            env!("CARGO_MANIFEST_DIR"),
+            "/tests/images/png/transparency/tp1n3p08.png"
+        );
+        let img = crate::open(path).unwrap();
+        let rgba8 = img.as_rgba8().unwrap();
+        let filters = &[Nearest, Triangle, CatmullRom, Gaussian, Lanczos3];
+        for filter in filters {
+            assert_resize(rgba8, *filter);
+        }
+    }
+
+    #[test]
+    fn bug_1600() {
+        let image = crate::RgbaImage::from_raw(629, 627, vec![255; 629 * 627 * 4]).unwrap();
+        let result = resize(&image, 22, 22, FilterType::Lanczos3);
+        assert!(result.into_raw().into_iter().any(|c| c != 0));
+    }
+}