forked from yingxingde/FasterRCNN-pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
log
43 lines (27 loc) · 1.44 KB
/
log
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
VGG:
CUDA_VISIBLE_DEVICES=1 python train.py --net='vgg16' --tag=vgg16 --iters=70000 --cfg='./experiments/cfgs/vgg16.yml' --weight='./data/pretrained_model/vgg16_caffe.pth'
CUDA_VISIBLE_DEVICES=2 python test.py --net='vgg16' --tag=vgg16 --model=60000 --cfg='./experiments/cfgs/vgg16.yml' --model_path='voc_2007_trainval/vgg16/vgg16_faster_rcnn' --imdb='voc_2007_test' --comp
ResNet:
CUDA_VISIBLE_DEVICES=2 python train.py --net='res18' --tag=res18 --iters=70000 --cfg='./experiments/cfgs/res18.yml' --weight='./data/pretrained_model/Resnet18_imagenet.pth'
CUDA_VISIBLE_DEVICES=3 python train.py --net='res50' --tag=res50 --iters=70000 --cfg='./experiments/cfgs/res50.yml' --weight='./data/pretrained_model/Resnet50_imagenet.pth'
CUDA_VISIBLE_DEVICES=7 python train.py --net='res101' --tag=res101 --iters=80000 --cfg='./experiments/cfgs/res101.yml' --weight='./data/pretrained_model/resnet101_caffe.pth'
CUDA_VISIBLE_DEVICES=6 python test.py --net='res101' --tag=res101_1 --cfg='./experiments/cfgs/res101.yml' --model=70000 --model_path='voc_2007_trainval/res101_1' --imdb='voc_2007_test' --comp
GPU model Architecture
TitanX (Maxwell/Pascal) sm_52
GTX 960M sm_50
GTX 1080 (Ti) sm_61
Grid K520 (AWS g2.2xlarge) sm_30
Tesla K80 (AWS p2.xlarge) sm_37
how to use?
1.
cd ./lib
改 make.sh 和 setup.py gpu_id
sh make.sh
2.
cd ../
mkdir ./data
mkdir ./data/pretrained_model
下载权重在 ./data/pretrained_model中
3.
训练 train.py
评估 test.py