From 688a729d12e94f13b4d07ac68bf1c4d7fa5a9307 Mon Sep 17 00:00:00 2001 From: Sefik Ilkin Serengil Date: Thu, 23 Dec 2021 17:01:05 +0300 Subject: [PATCH] typo --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 23f063f..65b2092 100644 --- a/README.md +++ b/README.md @@ -141,7 +141,7 @@ Face recognition models are actually CNN models and they expect standard sized i [RetinaFace](https://sefiks.com/2021/04/27/deep-face-detection-with-retinaface-in-python/) and [MTCNN](https://sefiks.com/2020/09/09/deep-face-detection-with-mtcnn-in-python/) seem to overperform in detection and alignment stages but they are much slower. If the speed of your pipeline is more important, then you should use opencv or ssd. On the other hand, if you consider the accuracy, then you should use retinaface or mtcnn. -The performance of RetinaFace is very satisfactory even in the crowd as seen in the following illustration. Besides, it comes with incredible facial landmark detection performance. Please notice that the landmarks in the detected face areas highlighted with red points. This will improve the alignment score as well. +The performance of RetinaFace is very satisfactory even in the crowd as seen in the following illustration. Besides, it comes with an incredible facial landmark detection performance. Please notice that the landmarks in the detected face areas highlighted with red points. This will improve the alignment score as well.