yolov5 centos7 설치 및 training

python3 -m venv yolov5

export TORCH_CUDA_ARCH_LIST=8.6

git clone https://github.com/ultralytics/yolov5.git

pip3 install -r requirements.txt

pip3 uninstall torch

pip3 install torch==1.7.1+cu110 torchvision==0.8.2+cu110 -f https://download.pytorch.org/whl/torch_stable.html

 

 

from glob import glob
img_list = glob('/home/admin/darknet/Training/SealNumLogo/dataset/*.jpg')
print(len(img_list))

from sklearn.model_selection import train_test_split

train_img_list, val_img_list = train_test_split(img_list, test_size=0.2, random_state=2000)
print(len(train_img_list), len(val_img_list))

with open('/home/admin/darknet/Training/SealNumLogo/Network/train.txt', 'w') as f:
    f.write('\n'.join(train_img_list) + '\n')
with open('/home/admin/darknet/Training/SealNumLogo/Network/val.txt', 'w') as f:
    f.write('\n'.join(val_img_list) + '\n')

import yaml

with open('/home/admin/darknet/Training/SealNumLogo/yolov5/data.yaml', 'r') as f:
    data = yaml.full_load(f)
print(data)

data['train'] = '/home/admin/darknet/Training/SealNumLogo/Network/train.txt'
data['val'] = '/home/admin/darknet/Training/SealNumLogo/Network/val.txt'

with open('/home/admin/darknet/Training/SealNumLogo/yolov5/data.yaml', 'w') as f:
    yaml.dump(data, f)
print(data)

 

python3 /home/admin/darknet/Training/SealNumLogo/yolov5/train.py --img 416 --batch 16 --epochs 36000 \
--data /home/admin/darknet/Training/SealNumLogo/yolov5/data.yaml --cfg /home/admin/darknet/Training/SealNumLogo/yolov5/models/yolov5s.yaml --weights yolov5s.pt \
--name seal_yolov5m_results