Deleted vendor folder

1 files changed, 0 insertions, 1228 deletions

diff --git a/vendor/image/src/imageops/sample.rs b/vendor/image/src/imageops/sample.rs
deleted file mode 100644
index a362f83..0000000
--- a/vendor/image/src/imageops/sample.rs
+++ /dev/null
@@ -1,1228 +0,0 @@
-//! 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));
-    }
-}