From 6468dbde2a8bac6f0b410e67420bd48a758dbf74 Mon Sep 17 00:00:00 2001
From: Proyash Paban Sarma Borah <47718224+Spritan@users.noreply.github.com>
Date: Wed, 28 Feb 2024 02:45:08 +0530
Subject: [PATCH] Update README.md

---
 README.md | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 48dde56..66014ae 100644
--- a/README.md
+++ b/README.md
@@ -1,7 +1,6 @@
 # YOLOv8_Explainer
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
-<!-- [![Downloads](https://static.pepy.tech/personalized-badge/grad-cam?period=month&units=international_system&left_color=black&right_color=brightgreen&left_text=Monthly%20Downloads)](https://pepy.tech/project/YOLOv8-Explainer)
-[![Downloads](https://static.pepy.tech/personalized-badge/grad-cam?period=total&units=international_system&left_color=black&right_color=blue&left_text=Total%20Downloads)](https://pepy.tech/project/YOLOv8-Explainer) -->
+[![Downloads](https://static.pepy.tech/badge/YOLOv8-Explainer)](https://pepy.tech/project/YOLOv8-Explainer)
 ## Simplify your understanding of YOLOv8 Results
 This is a package with state of the art methods for Explainable AI for computer vision using YOLOv8. This can be used for diagnosing model predictions, either in production or while developing models. The aim is also to serve as a benchmark of algorithms and metrics for research of new explainability methods.
 
@@ -110,4 +109,4 @@ Suraj Srinivas, Francois Fleuret`
 
 https://arxiv.org/abs/1806.10206 <br>
 `Deep Feature Factorization For Concept Discovery
-Edo Collins, Radhakrishna Achanta, Sabine Süsstrunk`
\ No newline at end of file
+Edo Collins, Radhakrishna Achanta, Sabine Süsstrunk`