# 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')