From 9603396490a14b26d34365365aed21f0d7f92bcd Mon Sep 17 00:00:00 2001
From: Allen Gu <42553779+allengu01@users.noreply.github.com>
Date: Sun, 27 Sep 2020 17:19:06 -0500
Subject: [PATCH] Update README.md

---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index 96d4f99..8ba4191 100644
--- a/README.md
+++ b/README.md
@@ -5,8 +5,10 @@ This program uses the k-means clustering algorithm to determine k colors that ar
 K-means clustering is an unsupervised machine learning algorithm that finds k clusters within a given dataset. The algorithm begins by defining k centroids, around which each cluster will be created. A cluster of a centroid is defined as all members of the dataset (in this case, pixels RGB values) which are closest to that given centroid. Next, when all members of the data set are assigned to the closest centroid, the algorithm moves each centroid to the mean of the cluster. The algorithm continues to iterate by creating clusters and updating the centroids until no centroids move during an iteration.
 
 ## Examples
+#### 1)
 <p align="center">
   <img width="400" align="center" src="images/minimalist_landscape1.jpg">
   <img width="500" align="center" src="examples/iterate_animation1.gif">
   <img width="400" align="center" src="examples/rotate_animation1.gif">
 </p>
+<hr>