diff --git a/Cargo.toml b/Cargo.toml
index d74896c..eb198de 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -11,6 +11,4 @@ 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"
\ No newline at end of file
+hdbscan = "0.10.0"
\ No newline at end of file
diff --git a/src/main.rs b/src/main.rs
index fab0196..3ffabae 100644
--- a/src/main.rs
+++ b/src/main.rs
@@ -1,20 +1,15 @@
-use linfa::traits::Transformer;
 use std::collections::VecDeque;
+use std::iter::zip;
 use std::time::{Duration, Instant};
-use image::{DynamicImage, ImageReader, Rgb};
-use linfa_clustering::Dbscan;
+use hdbscan::{Hdbscan, HdbscanHyperParams};
+use image::{DynamicImage, ImageReader, Rgb, RgbImage};
 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> {
+fn extract_highlights_and_distort(image: &Vec<u8>, width: u32, threshold: u8, downsample: f64) -> Vec<Vec<f64>> {
     let max_rng = (u32::MAX as f64 * downsample) as u32;
+    let width_2 = width as f64 / 2.0;
     let poi = image
         .par_iter()
         .enumerate()
@@ -23,11 +18,13 @@ fn extract_highlights(image: &Vec<u8>, width: u32, threshold: u8, downsample: f6
             let mut rng = rand::rng();
             rng.random::<u32>() < max_rng
         })
-        .map(move |(i, _)| [ i as u32 % width, i as u32 / width ]);
+        .map(move |(i, _)| {
+            vec![ i as f64 % width as f64 - width_2, i as f64 / width as f64 ]
+        });
 
     let mut vec = Vec::new();
     vec.par_extend(poi);
-    Array2::from(vec)
+    vec
 }
 
 #[show_image::main]
@@ -40,15 +37,39 @@ fn main() {
 
     let window = create_window("image", Default::default()).unwrap();
     let mut t: VecDeque<Duration> = VecDeque::with_capacity(25);
+    let params = HdbscanHyperParams::builder()
+        .epsilon(5.0)
+        .min_samples(5)
+        .min_cluster_size(100)
+        .build();
+
     loop {
         let start = Instant::now();
-        let poi = extract_highlights(&img_data, width, 196, 1.0);
+        let poi = extract_highlights_and_distort(&img_data, width, 196, 0.05);
 
-        let mut rgb_image = img.to_rgb8();
+        let clusterer = Hdbscan::new(&poi, params.clone());
+        let labels = clusterer.cluster().unwrap();
 
+        let mut rgb_image = RgbImage::new(width, height);
 
-        poi.outer_iter().for_each(|pixel| {
-            rgb_image.put_pixel(pixel[0], pixel[1], Rgb([255, 0, 0]))
+        zip(poi, labels).for_each(|(pixel, label)| {
+            if label != -1 {
+                let color = vec![Rgb([255, 0, 0]), Rgb([0, 255, 0]), Rgb([0, 0, 255]), Rgb([0, 0, 0])][label as usize];
+                let x = (pixel[0] + width as f64 / 2.0) as u32;
+                rgb_image.put_pixel(x, pixel[1] as u32, color);
+                if pixel[0] > 0.0 {
+                    rgb_image.put_pixel(x - 1, pixel[1] as u32, color);
+                }
+                if pixel[0] < width as f64 - 1.0 {
+                    rgb_image.put_pixel(x + 1, pixel[1] as u32, color);
+                }
+                if pixel[1] > 0.0 {
+                    rgb_image.put_pixel(x, pixel[1] as u32 - 1, color);
+                }
+                if pixel[1] < height as f64 - 1.0 {
+                    rgb_image.put_pixel(x, pixel[1] as u32 + 1, Rgb([label as u8 * 8, 0, 0]));
+                }
+            }
         });
 
         let image = ImageView::new(ImageInfo::new(PixelFormat::Rgb8, width, height), rgb_image.iter().as_slice());