Comments (3)
The first thing to check is whether opencv is using the GPU in this case or not.
from imageproc.
OpenCV may well be doing something smarter, but one difference here is that you're using a 7x7 filter for OpenCV and a 15x15 filter for imageproc. OpenCV takes a width parameter that it requires to be odd, whereas imageproc takes a radius parameter and uses a filter of size 2*radius + 1 to ensure it's always odd. This is possibly a confusing API!
from imageproc.
Having reminded myself of what the code does, the imageproc implementation is linear in kernel width so your accidental difference in parameters shouldn't account for much of the difference between the two libraries!
Quick empirical sanity check for this:
use std::time::SystemTime;
use image::{GrayImage, Luma};
use imageproc::filter::median_filter;
fn main() {
let image = GrayImage::from_fn(9720, 11340, |_, _| Luma([7]));
let t0 = SystemTime::now();
let _f1 = median_filter(&image, 3, 3);
let t1 = SystemTime::now();
let _f2 = median_filter(&image, 7, 7);
let t2 = SystemTime::now();
println!("{:?}", t1.duration_since(t0));
println!("{:?}", t2.duration_since(t1));
}
Ok(3.232656s)
Ok(6.872397s)
That's still slower than your OpenCV run time, but far faster than your imageproc run time. I suspect you might be running your code in debug mode and so comparing a debug build of imageproc against a release build of OpenCV.
From a quick glance at the source code for OpenCV's implementation, it looks to be doing something roughly similar to what we do in imageproc, but with SIMD acceleration. I wouldn't be too surprised by a 5-10x difference in run time, but 200x looks wrong.
@wangm23456 can you check if you're running imageproc in debug or release mode.
from imageproc.
Related Issues (20)
- How does this crate compare to magick-rust? HOT 2
- Try using doc_auto_cfg to automate addition of docrs attributes
- Rename `imageproc::map::map_colors()` to `map_pixels()` HOT 2
- Another doc-macro for parallel variations of functions?
- `Rect` refactors HOT 2
- Add filter benchmarks for kernels larger than 3x3
- Add hardcoded filter3x3 function to benchmark current generic filter function against HOT 19
- Switch `imageproc::Rect` to `image::Rect` HOT 3
- `Laplacian` from `master` is wrong HOT 4
- Check for any functions missing tests
- Use `Kernel` by `ref` HOT 2
- Document release process
- Agree a sensible API for filtering so we can reduce the risk of frequent breaking changes to signatures HOT 3
- Fix filter performance vs simple hardcoded implementation
- Add Tags for all previous releases where possible HOT 2
- Decide module layout for new imageops functions HOT 1
- how encode drawed image to [u8] ? HOT 6
- Rounded corners on rectangles and images HOT 4
- Projection matrix for rotation is weird
- Add `#[must_use]` to all non-mut image processing functions
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from imageproc.