Crates.io | dcv-color-primitives |
lib.rs | dcv-color-primitives |
version | 0.6.1 |
source | src |
created_at | 2019-12-23 14:13:25.454341 |
updated_at | 2023-11-03 16:31:37.322787 |
description | a library to perform image color model conversion |
homepage | |
repository | https://github.com/aws/dcv-color-primitives |
max_upload_size | |
id | 191728 |
size | 499,512 |
DCV Color Primitives is a library to perform image color model conversion.
[*]: Supplemental cpu extension sets not yet supported.
The library is currenty able to convert the following pixel formats:
Source pixel format | Destination pixel formats |
---|---|
ARGB | I420, I444, NV12 |
BGR | I420, I444, NV12, RGB |
BGRA | I420, I444, NV12, RGB |
I420 | BGRA, RGBA |
I444 | BGRA, RGBA |
NV12 | BGRA, RGB, RGBA |
RGB | BGRA |
The supported color models are:
Both standard range (0-235) and full range (0-255) are supported.
curl https://sh.rustup.rs -sSf | sh
You may require administrative privileges.
Open a terminal inside the library root directory.
To build for debug experience:
cargo build
To build an optimized library:
cargo build --release
Run unit tests:
cargo test
Run benchmark:
cargo bench
Advanced benchmark mode. There are two benchmark scripts:
run-bench.ps1
for Windowsrun-bench.sh
for Linux and MacOSThey allow to obtain more stable results than cargo bench
, by reducing variance due to:
Moreover, the Linux script support hardware performance counters, e.g. it is possible to output consumed CPU cycles instead of elapsed time.
Linux examples:
./run-bench -c 1 # runs cargo bench and outputs CPU cycles
./run.bench -c 1 -p "/i420" # runs cargo bench, output CPU cycles, filtering tests that contains '/i420'
Install the needed dependencies:
rustup target add wasm32-unknown-unknown
To build for debug experience:
cargo build --target wasm32-unknown-unknown
To test, ensure you have installed wasm-pack. Then:
wasm-pack test --node
Convert an image from bgra to nv12 (single plane) format containing yuv in BT601:
use dcv_color_primitives as dcp;
use dcp::{convert_image, ColorSpace, ImageFormat, PixelFormat};
fn main() {
const WIDTH: u32 = 640;
const HEIGHT: u32 = 480;
let src_data = Box::new([0u8; 4 * (WIDTH as usize) * (HEIGHT as usize)]);
let mut dst_data = Box::new([0u8; 3 * (WIDTH as usize) * (HEIGHT as usize) / 2]);
let src_format = ImageFormat {
pixel_format: PixelFormat::Bgra,
color_space: ColorSpace::Rgb,
num_planes: 1,
};
let dst_format = ImageFormat {
pixel_format: PixelFormat::Nv12,
color_space: ColorSpace::Bt601,
num_planes: 1,
};
convert_image(
WIDTH,
HEIGHT,
&src_format,
None,
&[&*src_data],
&dst_format,
None,
&mut [&mut *dst_data],
);
}
The library functions return a Result
describing the operation outcome:
Result | Description |
---|---|
Ok(()) |
The operation succeeded |
Err(ErrorKind::InvalidValue) |
One or more parameters have invalid values for the called function |
Err(ErrorKind::InvalidOperation) |
The combination of parameters is unsupported for the called function |
Err(ErrorKind::NotEnoughData) |
One or more buffers are not correctly sized |
In the following example, result
will match Err(ErrorKind::InvalidValue)
, because ColorSpace::Bt709
color space is not compatible with PixelFormat::Bgra
:
use dcv_color_primitives as dcp;
use dcp::{convert_image, ColorSpace, ErrorKind, ImageFormat, PixelFormat};
fn main() {
const WIDTH: u32 = 640;
const HEIGHT: u32 = 480;
let src_data = Box::new([0u8; 4 * (WIDTH as usize) * (HEIGHT as usize)]);
let mut dst_data = Box::new([0u8; 3 * (WIDTH as usize) * (HEIGHT as usize) / 2]);
let src_format = ImageFormat {
pixel_format: PixelFormat::Bgra,
color_space: ColorSpace::Bt709,
num_planes: 1,
};
let dst_format = ImageFormat {
pixel_format: PixelFormat::Nv12,
color_space: ColorSpace::Bt601,
num_planes: 1,
};
let status = convert_image(
WIDTH,
HEIGHT,
&src_format,
None,
&[&*src_data],
&dst_format,
None,
&mut [&mut *dst_data],
);
match status {
Err(ErrorKind::InvalidValue) => (),
_ => panic!("Expected ErrorKind::InvalidValue"),
}
}
Even better, you might want to propagate errors to the caller function or mix with some other error types:
use dcv_color_primitives as dcp;
use dcp::{convert_image, ColorSpace, ImageFormat, PixelFormat};
use std::error;
fn main() -> Result<(), Box<dyn error::Error>> {
const WIDTH: u32 = 640;
const HEIGHT: u32 = 480;
let src_data = Box::new([0u8; 4 * (WIDTH as usize) * (HEIGHT as usize)]);
let mut dst_data = Box::new([0u8; 3 * (WIDTH as usize) * (HEIGHT as usize) / 2]);
let src_format = ImageFormat {
pixel_format: PixelFormat::Bgra,
color_space: ColorSpace::Bt709,
num_planes: 1,
};
let dst_format = ImageFormat {
pixel_format: PixelFormat::Nv12,
color_space: ColorSpace::Bt601,
num_planes: 1,
};
convert_image(
WIDTH,
HEIGHT,
&src_format,
None,
&[&*src_data],
&dst_format,
None,
&mut [&mut *dst_data],
)?;
Ok(())
}
So far, buffers were sized taking into account the image pixel format and dimensions; However, you can use a function to compute how many bytes are needed to store an image of a given format and size:
use dcv_color_primitives as dcp;
use dcp::{get_buffers_size, ColorSpace, ImageFormat, PixelFormat};
use std::error;
fn main() -> Result<(), Box<dyn error::Error>> {
const WIDTH: u32 = 640;
const HEIGHT: u32 = 480;
const NUM_PLANES: u32 = 1;
let format = ImageFormat {
pixel_format: PixelFormat::Bgra,
color_space: ColorSpace::Rgb,
num_planes: NUM_PLANES,
};
let sizes: &mut [usize] = &mut [0usize; NUM_PLANES as usize];
get_buffers_size(WIDTH, HEIGHT, &format, None, sizes)?;
let buffer: Vec<_> = vec![0u8; sizes[0]];
// Do something with buffer
// --snip--
Ok(())
}
If your data is scattered in multiple buffers that are not necessarily contiguous, you can provide image planes:
use dcv_color_primitives as dcp;
use dcp::{convert_image, get_buffers_size, ColorSpace, ImageFormat, PixelFormat};
use std::error;
fn main() -> Result<(), Box<dyn error::Error>> {
const WIDTH: u32 = 640;
const HEIGHT: u32 = 480;
const NUM_SRC_PLANES: u32 = 2;
const NUM_DST_PLANES: u32 = 1;
let src_format = ImageFormat {
pixel_format: PixelFormat::Nv12,
color_space: ColorSpace::Bt709,
num_planes: NUM_SRC_PLANES,
};
let src_sizes: &mut [usize] = &mut [0usize; NUM_SRC_PLANES as usize];
get_buffers_size(WIDTH, HEIGHT, &src_format, None, src_sizes)?;
let src_y: Vec<_> = vec![0u8; src_sizes[0]];
let src_uv: Vec<_> = vec![0u8; src_sizes[1]];
let dst_format = ImageFormat {
pixel_format: PixelFormat::Bgra,
color_space: ColorSpace::Rgb,
num_planes: NUM_DST_PLANES,
};
let dst_sizes: &mut [usize] = &mut [0usize; NUM_DST_PLANES as usize];
get_buffers_size(WIDTH, HEIGHT, &dst_format, None, dst_sizes)?;
let mut dst_rgba: Vec<_> = vec![0u8; dst_sizes[0]];
convert_image(
WIDTH,
HEIGHT,
&src_format,
None,
&[&src_y[..], &src_uv[..]],
&dst_format,
None,
&mut [&mut dst_rgba[..]],
)?;
Ok(())
}
To take into account data which is not tightly packed, you can provide image strides:
use dcv_color_primitives as dcp;
use dcp::{convert_image, get_buffers_size, ColorSpace, ImageFormat, PixelFormat};
use std::error;
fn main() -> Result<(), Box<dyn error::Error>> {
const WIDTH: u32 = 640;
const HEIGHT: u32 = 480;
const NUM_SRC_PLANES: u32 = 1;
const NUM_DST_PLANES: u32 = 2;
const RGB_STRIDE: usize = 4 * (((3 * (WIDTH as usize)) + 3) / 4);
let src_format = ImageFormat {
pixel_format: PixelFormat::Bgr,
color_space: ColorSpace::Rgb,
num_planes: NUM_SRC_PLANES,
};
let src_strides: &[usize] = &[RGB_STRIDE];
let src_sizes: &mut [usize] = &mut [0usize; NUM_SRC_PLANES as usize];
get_buffers_size(WIDTH, HEIGHT, &src_format, Some(src_strides), src_sizes)?;
let src_rgba: Vec<_> = vec![0u8; src_sizes[0]];
let dst_format = ImageFormat {
pixel_format: PixelFormat::Nv12,
color_space: ColorSpace::Bt709,
num_planes: NUM_DST_PLANES,
};
let dst_sizes: &mut [usize] = &mut [0usize; NUM_DST_PLANES as usize];
get_buffers_size(WIDTH, HEIGHT, &dst_format, None, dst_sizes)?;
let mut dst_y: Vec<_> = vec![0u8; dst_sizes[0]];
let mut dst_uv: Vec<_> = vec![0u8; dst_sizes[1]];
convert_image(
WIDTH,
HEIGHT,
&src_format,
Some(src_strides),
&[&src_rgba[..]],
&dst_format,
None,
&mut [&mut dst_y[..], &mut dst_uv[..]],
)?;
Ok(())
}
See documentation for further information.
DCV Color Primitives provides C bindings. A static library will be automatically generated for the default build.
In order to include DCV Color Primitives inside your application library, you need to:
The API is slightly different than the rust one. Check dcv_color_primitives.h for examples and further information.
A meson build system is provided in order to build the static library and install it together with include file and a pkgconfig file. There are also some unit tests written in C, to add some coverage also for the bindings. Minimal instructions are provided below, refer to meson's help for further instructions:
Windows Visual Studio is required. At least the following packages are required:
Install meson, you can choose one of the following methods:
pip install meson ninja
Note: Minimum required meson version is 1.0.0.
All build commands have to be issued from Native Tools Command Prompt for VS (x86 or x64 depending on what platform you want to build)
Linux The following example is for Ubuntu:
#install python3
apt install python3
#install meson. See https://mesonbuild.com/Getting-meson.html for details or if you want to install through pip.
apt install meson
#install ninja
apt install ninja-build
You may require administrative privileges.
Build Move inside the library root directory:
cd `dcv_color_primitives_root_dir`
Then:
meson setup --buildtype release builddir
ninja -C builddir
Run the tests
cd builddir
meson test -t 10
A timeout scale factor of 10 is required because some tests take longer than default 30 seconds to complete.
Install
ninja -C builddir install
This library is licensed under the MIT-0 License. See the LICENSE file.