From 7803083e88eca42460ae0a3f1130be214414e602 Mon Sep 17 00:00:00 2001 From: Sefik Ilkin Serengil Date: Fri, 4 Dec 2020 11:24:20 +0300 Subject: [PATCH] elastic face removed --- README.md | 2 -- 1 file changed, 2 deletions(-) diff --git a/README.md b/README.md index ec8d0b7..4cf9bc1 100644 --- a/README.md +++ b/README.md @@ -115,8 +115,6 @@ user Notice that face recognition has O(n) time complexity and this might be problematic for millions level data. Herein, approximate nearest neighbor (a-nn) algorithm reduces the time complexity dramatically. [Spotify Annoy](https://sefiks.com/2020/09/16/large-scale-face-recognition-with-spotify-annoy/), [Facebook Faiss](https://sefiks.com/2020/09/17/large-scale-face-recognition-with-facebook-faiss/) and [NMSLIB](https://sefiks.com/2020/09/19/large-scale-face-recognition-with-nmslib/) are amazing a-nn libraries. Besides, [Elasticsearch](https://sefiks.com/2020/11/27/large-scale-face-recognition-with-elasticsearch/) wraps an a-nn algorithm and it offers highly scalable feature. You should run deepface within those a-nn frameworks if you have really large scale data sets. -

- **Face Detectors** - [`Demo`](https://youtu.be/GZ2p2hj2H5k) Face detection and alignment are early stages of a modern face recognition pipeline. [OpenCV haar cascade](https://sefiks.com/2020/02/23/face-alignment-for-face-recognition-in-python-within-opencv/), [SSD](https://sefiks.com/2020/08/25/deep-face-detection-with-opencv-in-python/), [Dlib](https://sefiks.com/2020/07/11/face-recognition-with-dlib-in-python/) and [MTCNN](https://sefiks.com/2020/09/09/deep-face-detection-with-mtcnn-in-python/) methods are wrapped in deepface as a detector. You can optionally pass a custom detector to functions in deepface interface. MTCNN is the default detector if you won't pass any detector.