From a75d45bf075d1bf0a463c152c9293015a10e7560 Mon Sep 17 00:00:00 2001 From: Sefik Ilkin Serengil Date: Mon, 20 Jan 2025 09:43:37 +0000 Subject: [PATCH] Update README.md location of github trending moved to under of logo --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 6f09b1b..66fd2af 100644 --- a/README.md +++ b/README.md @@ -2,8 +2,6 @@
-serengil%2Fdeepface | Trendshift - [![Downloads](https://static.pepy.tech/personalized-badge/deepface?period=total&units=international_system&left_color=grey&right_color=blue&left_text=downloads)](https://pepy.tech/project/deepface) [![Stars](https://img.shields.io/github/stars/serengil/deepface?color=yellow&style=flat&label=%E2%AD%90%20stars)](https://github.com/serengil/deepface/stargazers) [![License](http://img.shields.io/:license-MIT-green.svg?style=flat)](https://github.com/serengil/deepface/blob/master/LICENSE) @@ -28,6 +26,8 @@

+serengil%2Fdeepface | Trendshift + 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.