Struct color_quant::NeuQuant [−][src]
pub struct NeuQuant { /* fields omitted */ }Implementations
impl NeuQuant[src]
impl NeuQuant[src]pub fn new(samplefac: i32, colors: usize, pixels: &[u8]) -> Self[src]
Creates a new neuronal network and trains it with the supplied data.
Pixels are assumed to be in RGBA format.
colors should be $>=64$. samplefac determines the faction of
the sample that will be used to train the network. Its value must be in the
range $[1, 30]$. A value of $1$ thus produces the best result but is also
slowest. $10$ is a good compromise between speed and quality.
pub fn init(&mut self, pixels: &[u8])[src]
Initializes the neuronal network and trains it with the supplied data.
This method gets called by Self::new.
pub fn map_pixel(&self, pixel: &mut [u8])[src]
Maps the rgba-pixel in-place to the best-matching color in the color map.
pub fn index_of(&self, pixel: &[u8]) -> usize[src]
Finds the best-matching index in the color map.
pixel is assumed to be in RGBA format.
pub fn lookup(&self, idx: usize) -> Option<[u8; 4]>[src]
Lookup pixel values for color at idx in the colormap.
pub fn color_map_rgba(&self) -> Vec<u8>[src]
Returns the RGBA color map calculated from the sample.
pub fn color_map_rgb(&self) -> Vec<u8>[src]
Returns the RGBA color map calculated from the sample.