3 unstable releases
0.2.1 | May 25, 2023 |
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0.2.0 | May 24, 2023 |
0.1.0 | Nov 4, 2022 |
#1011 in Images
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Efficient Graph-Based Image Segmentation
This repository contains a Rust implementation of the graph-based image segmentation algorithms
described in [1]
(available here)
focussing on generating over-segmentations, also referred to as superpixels.
Contours | Labels |
---|---|
Please note that this is a reference implementation and not particularly fast.
[1] P. F. Felzenswalb and D. P. Huttenlocher.
Efficient Graph-Based Image Segmentation.
International Journal of Computer Vision, volume 59, number 2, 2004.
The implementation is based on this work by David Stutz,
which in turn was used in [2]
for evaluation.
[2] D. Stutz, A. Hermans, B. Leibe.
Superpixels: An Evaluation of the State-of-the-Art.
Computer Vision and Image Understanding, 2018.
Example use
fn main() {
let mut image = imread("data/tree.jpg", IMREAD_COLOR).unwrap();
let threshold = 10f32;
let segment_size = 10;
let mut segmenter = Segmentation::new(
EuclideanRGB::default(),
MagicThreshold::new(threshold),
segment_size,
);
// NOTE: The image should be blurred before use; this is left out here for brevity.
let labels = segmenter.segment_image(&image);
}
Dependencies
~1.7–2.7MB
~29K SLoC