Crates.io | ffimage_yuv |
lib.rs | ffimage_yuv |
version | 0.10.0 |
source | src |
created_at | 2021-03-06 14:47:26.625684 |
updated_at | 2023-10-28 11:59:36.464678 |
description | YUV (aka YCbCr) pixel types for ffimage |
homepage | |
repository | https://github.com/raymanfx/ffimage |
max_upload_size | |
id | 364811 |
size | 17,749 |
This crate provides easy image pixel handling and conversion capabilities in Rust. It is designed to work with image buffers originating from foreign functions, which could be a C API or a camera driver which maps device buffers into userspace.
Pixels are represented as array wrapper types, e.g. [T; 3]
would be the inner type for an Rgb
pixel. The crate provides iterator extensions so you can easily convert between color formats, e.g. Yuv
and Rgb
.
Packed images have their pixels reside beneath each other in memory while planar images require separate memory planes for pixel components.
For example, a packed RGB image would look like this in memory:
R1G1B1 .. RnGnnn (single memory plane)
whereas a planar YUV420p image would look like this:
Y1Y2 .. Yn | U1U2 .. Un | V1V2 .. Vn (three memory planes)
Below you can find a quick example usage of this crate. It introduces the basics necessary for image conversion.
use ffimage::color::{Gray, Rgb};
use ffimage::iter::{BytesExt, ColorConvertExt, PixelsExt};
fn main() {
// This is our RGB image memory (2x2 pixels).
// Usually, this will be allocated by a foreign function (e.g. kernel driver) and contain
// read-only memory.
let rgb = [10; 4 * 3];
// We need an output buffer as well to host the converted grayscale pixels.
let mut gray = [0; 4 * 1];
// Convert from rgb to grayscale by mapping each pixel. The Pixels iterator extension creates
// a typed pixel iterator from a bytestream. The ColorConvert extension knows how to convert
// between pixel types and the Write extension finally writes the pixels back into a
// bytestream.
rgb.iter()
.copied()
.pixels::<Rgb<u8>>()
.colorconvert::<Gray<u8>>()
.bytes()
.write(&mut gray);
}
A benchmark suite is included in this crate. Run it using
$ cargo bench
These are my results for ffimage v0.10.0
on a MacBook Pro 14" (M1 Pro):
In | Out | 640x480 | 1280x720 |
---|---|---|---|
Rgb[u8] | Bgr[u8] | 18.028 µs | 53.882 µs |
Rgb[u8] | Gray[u8] | 381.48 µs | 1.1442 ms |
Yuv[u8] | Rgb[u8] | 165.32 µs | 496.33 µs |
Yuv422[u8] | Rgb[u8] | 1.2097 ms | 3.6284 ms |