From d22df005eeed4012aaf33f1b3718ac1f77937c01 Mon Sep 17 00:00:00 2001
From: Sefik Ilkin Serengil <serengil@gmail.com>
Date: Mon, 20 Jan 2025 09:44:12 +0000
Subject: [PATCH] Update README.md

github trending in end of badge area
---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 66fd2af..3b38a35 100644
--- a/README.md
+++ b/README.md
@@ -19,6 +19,8 @@
 [![Hacker News](https://img.shields.io/badge/dynamic/json?color=orange&label=Hacker%20News&query=score&url=https%3A%2F%2Fhacker-news.firebaseio.com%2Fv0%2Fitem%2F42584896.json&logo=y-combinator)](https://news.ycombinator.com/item?id=42584896)
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+<a href="https://trendshift.io/repositories/4227" target="_blank"><img src="https://trendshift.io/api/badge/repositories/4227" alt="serengil%2Fdeepface | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
+
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@@ -26,8 +28,6 @@
 
 <p align="center"><img src="https://raw.githubusercontent.com/serengil/deepface/master/icon/deepface-icon-labeled.png" width="200" height="240"></p>
 
-<a href="https://trendshift.io/repositories/4227" target="_blank"><img src="https://trendshift.io/api/badge/repositories/4227" alt="serengil%2Fdeepface | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
-
 DeepFace is a lightweight [face recognition](https://sefiks.com/2018/08/06/deep-face-recognition-with-keras/) and facial attribute analysis ([age](https://sefiks.com/2019/02/13/apparent-age-and-gender-prediction-in-keras/), [gender](https://sefiks.com/2019/02/13/apparent-age-and-gender-prediction-in-keras/), [emotion](https://sefiks.com/2018/01/01/facial-expression-recognition-with-keras/) and [race](https://sefiks.com/2019/11/11/race-and-ethnicity-prediction-in-keras/)) framework for python. It is a hybrid face recognition framework wrapping **state-of-the-art** models: [`VGG-Face`](https://sefiks.com/2018/08/06/deep-face-recognition-with-keras/), [`FaceNet`](https://sefiks.com/2018/09/03/face-recognition-with-facenet-in-keras/), [`OpenFace`](https://sefiks.com/2019/07/21/face-recognition-with-openface-in-keras/), [`DeepFace`](https://sefiks.com/2020/02/17/face-recognition-with-facebook-deepface-in-keras/), [`DeepID`](https://sefiks.com/2020/06/16/face-recognition-with-deepid-in-keras/), [`ArcFace`](https://sefiks.com/2020/12/14/deep-face-recognition-with-arcface-in-keras-and-python/), [`Dlib`](https://sefiks.com/2020/07/11/face-recognition-with-dlib-in-python/), `SFace` and `GhostFaceNet`.
 
 [`Experiments`](https://github.com/serengil/deepface/tree/master/benchmarks) show that **human beings have 97.53% accuracy** on facial recognition tasks whereas those models already reached and passed that accuracy level.