From 234373f36cf083ee672dad0e7fd7c320f46e4619 Mon Sep 17 00:00:00 2001
From: Muhammad Rizwan Munawar <muhammadrizwanmunawar123@gmail.com>
Date: Wed, 29 May 2024 14:37:41 +0500
Subject: [PATCH] Add https://youtu.be/F7db-EHhxss to docs (#13197)

---
 docs/en/models/fast-sam.md | 13 +++++++++++++
 1 file changed, 13 insertions(+)

diff --git a/docs/en/models/fast-sam.md b/docs/en/models/fast-sam.md
index 720e2c15..dc37aa75 100644
--- a/docs/en/models/fast-sam.md
+++ b/docs/en/models/fast-sam.md
@@ -8,6 +8,19 @@ keywords: FastSAM, machine learning, CNN-based solution, object segmentation, re
 
 The Fast Segment Anything Model (FastSAM) is a novel, real-time CNN-based solution for the Segment Anything task. This task is designed to segment any object within an image based on various possible user interaction prompts. FastSAM significantly reduces computational demands while maintaining competitive performance, making it a practical choice for a variety of vision tasks.
 
+<p align="center">
+  <br>
+  <iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/F7db-EHhxss"
+    title="YouTube video player" frameborder="0"
+    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
+    allowfullscreen>
+  </iframe>
+  <br>
+  <strong>Watch:</strong> Object Tracking using FastSAM with Ultralytics
+</p>
+
+## Model Architecture
+
 ![Fast Segment Anything Model (FastSAM) architecture overview](https://user-images.githubusercontent.com/26833433/248551984-d98f0f6d-7535-45d0-b380-2e1440b52ad7.jpg)
 
 ## Overview