Crates.io | image |
lib.rs | image |
version | 0.25.5 |
source | src |
created_at | 2014-11-20 20:03:29.764042 |
updated_at | 2024-11-05 09:16:36.672249 |
description | Imaging library. Provides basic image processing and encoders/decoders for common image formats. |
homepage | https://github.com/image-rs/image |
repository | https://github.com/image-rs/image |
max_upload_size | |
id | 136 |
size | 1,115,410 |
Maintainers: @HeroicKatora, @fintelia
This crate provides basic image processing functions and methods for converting to and from various image formats.
All image processing functions provided operate on types that implement the GenericImageView
and GenericImage
traits and return an ImageBuffer
.
Load images using [ImageReader
]:
use std::io::Cursor;
use image::ImageReader;
let img = ImageReader::open("myimage.png")?.decode()?;
let img2 = ImageReader::new(Cursor::new(bytes)).with_guessed_format()?.decode()?;
And save them using [save
] or [write_to
] methods:
img.save("empty.jpg")?;
let mut bytes: Vec<u8> = Vec::new();
img2.write_to(&mut Cursor::new(&mut bytes), image::ImageFormat::Png)?;
With default features enabled, image
provides implementations of many common
image format encoders and decoders.
Format | Decoding | Encoding |
---|---|---|
AVIF | Yes * | Yes (lossy only) |
BMP | Yes | Yes |
DDS | Yes | --- |
Farbfeld | Yes | Yes |
GIF | Yes | Yes |
HDR | Yes | Yes |
ICO | Yes | Yes |
JPEG | Yes | Yes |
EXR | Yes | Yes |
PNG | Yes | Yes |
PNM | Yes | Yes |
QOI | Yes | Yes |
TGA | Yes | Yes |
TIFF | Yes | Yes |
WebP | Yes | Yes (lossless only) |
avif-native
feature, uses the libdav1d C library.This crate provides a number of different types for representing images. Individual pixels within images are indexed with (0,0) at the top left corner.
ImageBuffer
An image parameterised by its Pixel type, represented by a width and height and
a vector of pixels. It provides direct access to its pixels and implements the
GenericImageView
and GenericImage
traits.
DynamicImage
A DynamicImage
is an enumeration over all supported ImageBuffer<P>
types.
Its exact image type is determined at runtime. It is the type returned when
opening an image. For convenience DynamicImage
reimplements all image
processing functions.
GenericImageView
and GenericImage
TraitsTraits that provide methods for inspecting (GenericImageView
) and manipulating (GenericImage
) images, parameterised over the image's pixel type.
SubImage
A view into another image, delimited by the coordinates of a rectangle. The coordinates given set the position of the top left corner of the rectangle. This is used to perform image processing functions on a subregion of an image.
ImageDecoder
and ImageDecoderRect
TraitsAll image format decoders implement the ImageDecoder
trait which provide
basic methods for getting image metadata and decoding images. Some formats
additionally provide ImageDecoderRect
implementations which allow for
decoding only part of an image at once.
The most important methods for decoders are...
image
provides the following pixel types:
All pixels are parameterised by their component type.
These are the functions defined in the imageops
module. All functions operate on types that implement the GenericImage
trait.
Note that some of the functions are very slow in debug mode. Make sure to use release mode if you experience any performance issues.
For more options, see the imageproc
crate.
image
provides the open
function for opening images from a path. The image
format is determined from the path's file extension. An io
module provides a
reader which offer some more control.
use image::GenericImageView;
// Use the open function to load an image from a Path.
// `open` returns a `DynamicImage` on success.
let img = image::open("tests/images/jpg/progressive/cat.jpg").unwrap();
// The dimensions method returns the images width and height.
println!("dimensions {:?}", img.dimensions());
// The color method returns the image's `ColorType`.
println!("{:?}", img.color());
// Write the contents of this image to the Writer in PNG format.
img.save("test.png").unwrap();
//! An example of generating julia fractals.
let imgx = 800;
let imgy = 800;
let scalex = 3.0 / imgx as f32;
let scaley = 3.0 / imgy as f32;
// Create a new ImgBuf with width: imgx and height: imgy
let mut imgbuf = image::ImageBuffer::new(imgx, imgy);
// Iterate over the coordinates and pixels of the image
for (x, y, pixel) in imgbuf.enumerate_pixels_mut() {
let r = (0.3 * x as f32) as u8;
let b = (0.3 * y as f32) as u8;
*pixel = image::Rgb([r, 0, b]);
}
// A redundant loop to demonstrate reading image data
for x in 0..imgx {
for y in 0..imgy {
let cx = y as f32 * scalex - 1.5;
let cy = x as f32 * scaley - 1.5;
let c = num_complex::Complex::new(-0.4, 0.6);
let mut z = num_complex::Complex::new(cx, cy);
let mut i = 0;
while i < 255 && z.norm() <= 2.0 {
z = z * z + c;
i += 1;
}
let pixel = imgbuf.get_pixel_mut(x, y);
let image::Rgb(data) = *pixel;
*pixel = image::Rgb([data[0], i as u8, data[2]]);
}
}
// Save the image as “fractal.png”, the format is deduced from the path
imgbuf.save("fractal.png").unwrap();
Example output:
If the high level interface is not needed because the image was obtained by other means, image
provides the function save_buffer
to save a buffer to a file.
let buffer: &[u8] = unimplemented!(); // Generate the image data
// Save the buffer as "image.png"
image::save_buffer("image.png", buffer, 800, 600, image::ExtendedColorType::Rgb8).unwrap()