# coding: utf-8
import sys
sys.path.append('.')
import argparse
from init import Infrastructure
infra = Infrastructure()
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--name',
type=str,
help='name of the metric',
required=True)
parser.add_argument('--description',
type=str,
help="Some words about this metric")
opt = parser.parse_args()
print(opt)
c = infra.conn.cursor()
c.execute(
'''
INSERT INTO metrics (name, description) VALUES (?, ?)
''', (opt.name, opt.description))
infra.conn.commit()
from tensorboard_logger import configure, log_value
from torch.autograd import Variable
from torch.utils.data import DataLoader
from torchvision import transforms
from init import Infrastructure
from transforms.myrandomsample import MyRandomSample
from transforms.myresize import MyResize
from transforms.totensor import MyToTensor
from transforms.toycbcr import ToYCbCr
from utils.find_klass_in_folder import find_klass
from utils.write_metrics import write_metrics
from visualizers.srgan_vis import Visualizer
if __name__ == '__main__':
infra = Infrastructure()
parser = argparse.ArgumentParser()
parser.add_argument('--dataset',
type=str,
default='mixed-flowers-berkley',
help='One of the datasets listed in your database')
parser.add_argument('--model',
type=str,
help="One of the models listed in your database")
parser.add_argument('--resLayersNumber',
type=int,
default=5,
help="Number of residual blocks")
parser.add_argument('--workers',
type=int,
# coding: utf-8
from init import Infrastructure
if __name__ == "__main__":
infra = Infrastructure()
infra.compress_for_git()
from init import Infrastructure
from models.srgan import Generator
from transforms.mycentercrop import MyCenterCrop
from transforms.myrandomsample import MyRandomSample
from transforms.myresize import MyResize
from transforms.totensor import MyToTensor
from transforms.toycbcr import ToYCbCr
from utils.find_klass_in_folder import find_klass
from utils.save_viz import save_viz
from utils.write_metrics import count_metrics
sys.path.append('.')
if __name__ == '__main__':
infra = Infrastructure()
parser = argparse.ArgumentParser()
parser.add_argument('--dataset',
type=str,
default='set5-test-only',
help='One of the datasets listed in your database')
parser.add_argument('--experimentId', type=int, help="Experiment id")
parser.add_argument('--imageSize',
type=int,
default=16,
help='the low resolution image size')
parser.add_argument('--upSampling',
type=int,
default=2,
help='low to high resolution scaling factor')