From 6cf7d73a21f8c68c03ce099b39305825d6be0bb3 Mon Sep 17 00:00:00 2001 From: Sefik Ilkin Serengil Date: Thu, 23 Dec 2021 21:25:35 +0300 Subject: [PATCH] kaggle removed --- README.md | 2 -- 1 file changed, 2 deletions(-) diff --git a/README.md b/README.md index 2b296dd..7d3730a 100644 --- a/README.md +++ b/README.md @@ -25,8 +25,6 @@ Then you will be able to import the library and use its functionalities. from deepface import DeepFace ``` -If you are going to use deepface in a kaggle competition, then please consider [this kernel](https://www.kaggle.com/serengil/deepface-framework-for-python). You will be able to use GPU as well. - **Facial Recognition** - [`Demo`](https://youtu.be/WnUVYQP4h44) A modern [**face recognition pipeline**](https://sefiks.com/2020/05/01/a-gentle-introduction-to-face-recognition-in-deep-learning/) consists of 5 common stages: [detect](https://sefiks.com/2020/08/25/deep-face-detection-with-opencv-in-python/), [align](https://sefiks.com/2020/02/23/face-alignment-for-face-recognition-in-python-within-opencv/), [normalize](https://sefiks.com/2020/11/20/facial-landmarks-for-face-recognition-with-dlib/), [represent](https://sefiks.com/2018/08/06/deep-face-recognition-with-keras/) and [verify](https://sefiks.com/2020/05/22/fine-tuning-the-threshold-in-face-recognition/). Deepface handles all these common stages in the background. You can just call its verification, find or analysis function with a single line of code.