From eeabd593e5cf3be53dc4e0143ac8efb7d706a8e6 Mon Sep 17 00:00:00 2001 From: Sefik Ilkin Serengil Date: Sun, 9 Feb 2020 11:27:14 +0300 Subject: [PATCH] reference models licenses --- README.md | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/README.md b/README.md index f0436c7..4c0357a 100644 --- a/README.md +++ b/README.md @@ -28,6 +28,8 @@ result = DeepFace.verify("img1.jpg", "img2.jpg", model_name = "VGG-Face", distan result = DeepFace.verify("img1.jpg", "img2.jpg", model_name = "VGG-Face", distance_metric = "euclidean_l2") ``` +VGG-Face has the highest accuracy score but it is not convenient for real time studies because of its complex structure. Facenet is a complex model as well. On the other hand, OpenFace has a close accuracy score but it performs the fastest. That's why, OpenFace is much more convenient for real time studies. + # Verification Verification function returns a tuple including boolean verification result, distance between two faces and max threshold to identify. @@ -80,6 +82,12 @@ pip install tensorflow==1.9.0 pip install keras==2.2.0 ``` +# Disclaimer + +Reference face recognition models have different type of licenses. This framework is just a wrapper for those models. That's why, licence types are inherited as well. You should check the licenses for the face recognition models before use. + +Herein, [OpenFace](https://github.com/cmusatyalab/openface/blob/master/LICENSE) is licensed under Apache License 2.0, and [Facenet](https://github.com/davidsandberg/facenet/blob/master/LICENSE.md) is licensed under MIT License. They both allow you to use commercial use. On the other hand, [VGG-Face](http://www.robots.ox.ac.uk/~vgg/software/vgg_face/) is licensed under Creative Commons Attribution License. That's why, it is restricted to adopt VGG-Face for commercial use. + # Support There are many ways to support a project - starring⭐️ the GitHub repos is just one.