Spaces:
Runtime error
Runtime error
import logging | |
import torch | |
from os import path as osp | |
from basicsr.data import build_dataloader, build_dataset | |
from basicsr.models import build_model | |
from basicsr.utils import get_root_logger, get_time_str, make_exp_dirs | |
from basicsr.utils.options import dict2str, parse_options | |
def image_sr(args): | |
# parse options, set distributed setting, set ramdom seed | |
opt, _ = parse_options(args.root_path, is_train=False) | |
torch.backends.cudnn.benchmark = True | |
# torch.backends.cudnn.deterministic = True | |
# create test dataset and dataloader | |
test_loaders = [] | |
for _, dataset_opt in sorted(opt['datasets'].items()): | |
dataset_opt['dataroot_lq'] = osp.join(args.output_dir, f'temp_LR') | |
if args.SR == 'x4': | |
opt['upscale'] = opt['network_g']['upscale'] = 4 | |
opt['val']['suffix'] = 'x4' | |
opt['path']['pretrain_network_g'] = osp.join(args.root_path, f'experiments/pretrained_models/RGT_x4.pth') | |
if args.SR == 'x2': | |
opt['upscale'] = opt['network_g']['upscale'] = 2 | |
opt['val']['suffix'] = 'x2' | |
test_set = build_dataset(dataset_opt) | |
test_loader = build_dataloader( | |
test_set, dataset_opt, num_gpu=opt['num_gpu'], dist=opt['dist'], sampler=None, seed=opt['manual_seed']) | |
test_loaders.append(test_loader) | |
opt['path']['pretrain_network_g'] = args.ckpt_path | |
opt['val']['use_chop'] = args.use_chop | |
opt['path']['visualization'] = osp.join(args.output_dir, f'temp_results') | |
opt['path']['results_root'] = osp.join(args.output_dir, f'temp_results') | |
# create model | |
model = build_model(opt) | |
for test_loader in test_loaders: | |
test_set_name = test_loader.dataset.opt['name'] | |
model.validation(test_loader, current_iter=opt['name'], tb_logger=None, save_img=opt['val']['save_img']) | |
if __name__ == '__main__': | |
root_path = osp.abspath(osp.join(__file__, osp.pardir, osp.pardir)) | |
# print(root_path) | |
# image_sr(root_path) | |