From 97791121b3c41b28817882bfcc9dd3b3a1e5ffcd Mon Sep 17 00:00:00 2001 From: Jia Guo Date: Wed, 26 Aug 2020 16:06:32 +0800 Subject: [PATCH] Update README.md --- README.md | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index c2428ef..3a08ea5 100644 --- a/README.md +++ b/README.md @@ -43,7 +43,7 @@ Please click the image to watch the Youtube video. For Bilibili users, click [he **`2019.04.04`**: Arcface achieved state-of-the-art performance (7/109) on the NIST Face Recognition Vendor Test (FRVT) (1:1 verification) [report](https://www.nist.gov/sites/default/files/documents/2019/04/04/frvt_report_2019_04_04.pdf) (name: Imperial-000 and Imperial-001). Our solution is based on [MS1MV2+DeepGlintAsian, ResNet100, ArcFace loss]. -**`2019.02.08`**: Please check [https://github.com/deepinsight/insightface/tree/master/recognition](https://github.com/deepinsight/insightface/tree/master/recognition) for our parallel training code which can easily and efficiently support one million identities on a single machine (8* 1080ti). +**`2019.02.08`**: Please check [https://github.com/deepinsight/insightface/tree/master/recognition/ArcFace](https://github.com/deepinsight/insightface/tree/master/recognition/ArcFace) for our parallel training code which can easily and efficiently support one million identities on a single machine (8* 1080ti). **`2018.12.13`**: Inference acceleration [TVM-Benchmark](https://github.com/deepinsight/insightface/wiki/TVM-Benchmark). @@ -165,6 +165,11 @@ CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train.py --network m1 --loss softmax -- CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train.py --network m1 --loss triplet --lr 0.005 --pretrained ./models/m1-softmax-emore,1 ``` +(5). Training in model parallel acceleration. + +```Shell +CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train_parall.py --network r100 --loss arcface --dataset emore +``` 5. Verification results.