From 2748cb565a42d3ecd29897c371ac391ce0e80835 Mon Sep 17 00:00:00 2001 From: Jia Guo Date: Tue, 15 Jan 2019 22:17:21 +0800 Subject: [PATCH] Update README.md --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 30e1516..b356d86 100644 --- a/README.md +++ b/README.md @@ -120,7 +120,7 @@ We give some examples below. Our experiments were conducted on the Tesla P40 GPU (1). Train ArcFace with LResNet100E-IR. ```Shell -CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train_softmax.py --network r100 --loss arcface --dataset emore +CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train.py --network r100 --loss arcface --dataset emore ``` It will output verification results of *LFW*, *CFP-FP* and *AgeDB-30* every 2000 batches. You can check all command line options in *train\_softmax.py*. This model can achieve *LFW 99.80+* and *MegaFace 98.3%+*. @@ -128,19 +128,19 @@ This model can achieve *LFW 99.80+* and *MegaFace 98.3%+*. (2). Train CosineFace with LResNet50E-IR. ```Shell -CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train_softmax.py --network r50 --loss cosface --dataset emore +CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train.py --network r50 --loss cosface --dataset emore ``` (3). Train Softmax with LMobileNet-GAP. ```Shell -CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train_softmax.py --network m1 --loss softmax --dataset emore +CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train.py --network m1 --loss softmax --dataset emore ``` (4). Fine-turn the above Softmax model with Triplet loss. ```Shell -CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train_triplet.py --network m1 --lr 0.005 --mom 0.0 --per-batch-size 150 --data-dir ../datasets/faces_ms1m_112x112 --pretrained ../model-m1-softmax,50 --prefix ../model-m1-triplet +CUDA_VISIBLE_DEVICES='0,1,2,3' python -u train.py --network m1 --loss triplet --lr 0.005 --pretrained ./models/m1-softmax-emore,1 ```