ndarray-conv is a crate that provides a fast convolutions library in pure Rust.
Inspired by
ndarray-vision (https://github.com/rust-cv/ndarray-vision)
convolutions-rs (https://github.com/Conzel/convolutions-rs#readme)
pocketfft (https://github.com/mreineck/pocketfft)
ndarray-conv is still under heavily developing, the first stage aims to provide a fast conv_2d func for ndarray::Array2.
- basic conv_2d
- use rayon to accelerate big matrix's conv_2d computation
- use fft to accelerate big kernel's conv_2d computation
without rayon
2x-4x faster than ndarray-vision and 4x-10x faster than convolutions-rs. 2x-4x slower than opencv with small kernel (size < 11)
with rayon
2x faster than opencv with small kernel (size < 11)
use ndarray_conv::conv_2d::*;
x.conv_2d(&k);
fn main() {
use ndarray_conv::conv_2d::*;
use ndarray::prelude::*;
use ndarray_rand::rand_distr::Uniform;
use ndarray_rand::RandomExt;
use std::time::Instant;
let mut small_duration = 0u128;
let test_cycles_small = 1;
// small input images
for _ in 0..test_cycles_small {
let x = Array::random((2000, 4000), Uniform::new(0., 1.));
let k = Array::random((9, 9), Uniform::new(0., 1.));
let now = Instant::now();
x.conv_2d(&k);
small_duration += now.elapsed().as_nanos();
}
println!(
"Time for small arrays, {} iterations: {} milliseconds",
test_cycles_small,
small_duration / 1_000_000
);
}