init

Cargo.toml

@@ -0,0 +1,16 @@
+[package]
+name = "line_detection_ros2"
+version = "0.1.0"
+edition = "2024"
+
+[profile.release]
+opt-level = 2  # Maximum optimization for release
+
+[dependencies]
+image = "0.25.6"
+show-image = "0.14.1"
+rand = "0.9.1"
+rayon = "1.10.0"
+linfa = "0.7.1"
+linfa-clustering = "0.7.1"
+ndarray = "0.16.1"

src/main.rs

@@ -0,0 +1,63 @@
+use linfa::traits::Transformer;
+use std::collections::VecDeque;
+use std::time::{Duration, Instant};
+use image::{DynamicImage, ImageReader, Rgb};
+use linfa_clustering::Dbscan;
+use rand::{Rng};
+use show_image::{create_window, ImageInfo, ImageView, PixelFormat};
+use rayon::prelude::*;
+use ndarray::{Array2, Axis};
+
+use linfa::prelude::*;
+// We'll build our dataset on our own using ndarray and rand
+use ndarray::prelude::*;
+
+
+fn extract_highlights(image: &Vec<u8>, width: u32, threshold: u8, downsample: f64) -> Array2<u32> {
+    let max_rng = (u32::MAX as f64 * downsample) as u32;
+    let poi = image
+        .par_iter()
+        .enumerate()
+        .filter(move |(_, pixel)| pixel > &&threshold)
+        .filter(move |_| {
+            let mut rng = rand::rng();
+            rng.random::<u32>() < max_rng
+        })
+        .map(move |(i, _)| [ i as u32 % width, i as u32 / width ]);
+
+    let mut vec = Vec::new();
+    vec.par_extend(poi);
+    Array2::from(vec)
+}
+
+#[show_image::main]
+fn main() {
+
+    let img: DynamicImage = ImageReader::open("./images/lane_detection_loop_80.png").unwrap().decode().unwrap();
+    let width: u32 = img.width();
+    let height: u32 = img.height();
+    let img_data: Vec<u8> = img.clone().into_bytes();
+
+    let window = create_window("image", Default::default()).unwrap();
+    let mut t: VecDeque<Duration> = VecDeque::with_capacity(25);
+    loop {
+        let start = Instant::now();
+        let poi = extract_highlights(&img_data, width, 196, 1.0);
+
+        let mut rgb_image = img.to_rgb8();
+
+
+        poi.outer_iter().for_each(|pixel| {
+            rgb_image.put_pixel(pixel[0], pixel[1], Rgb([255, 0, 0]))
+        });
+
+        let image = ImageView::new(ImageInfo::new(PixelFormat::Rgb8, width, height), rgb_image.iter().as_slice());
+        window.set_image("camera", image).unwrap();
+
+        if t.len() == 25 {
+            t.pop_front();
+        }
+        t.push_back(Instant::now() - start);
+        println!("Avg: {} FPS", 1.0 / (t.iter().map(|d| d.as_secs_f64()).sum::<f64>() / t.len() as f64));
+    }
+}