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Add doResizeLoss to dataset

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doResizeLoss has a 50% chance to resize the LQ image to 50% size,
then back to original size. This is useful to training a generator to
recover these lost pixel values while also being able to do
repairs on higher resolution images during training.
This commit is contained in:
James Betker 2020-06-08 11:27:06 -06:00
parent 786a4288d6
commit 296135ec18
2 changed files with 8 additions and 2 deletions
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6
codes/data/LQGT_dataset.py
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@ -146,6 +146,12 @@ class LQGTDataset(data.Dataset):
img_GT = cv2.resize(img_GT, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR) img_GT = cv2.resize(img_GT, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR)
img_PIX = cv2.resize(img_PIX, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR) img_PIX = cv2.resize(img_PIX, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR)
if self.opt['doResizeLoss']:
r = random.randrange(0, 10)
if r > 5:
img_LQ = cv2.resize(img_LQ, (int(LQ_size/2), int(LQ_size/2)), interpolation=cv2.INTER_LINEAR)
img_LQ = cv2.resize(img_LQ, (LQ_size, LQ_size), interpolation=cv2.INTER_LINEAR)
# augmentation - flip, rotate # augmentation - flip, rotate
img_LQ, img_GT, img_PIX = util.augment([img_LQ, img_GT, img_PIX], self.opt['use_flip'], img_LQ, img_GT, img_PIX = util.augment([img_LQ, img_GT, img_PIX], self.opt['use_flip'],
self.opt['use_rot']) self.opt['use_rot'])

4
codes/train.py
View File

@ -30,7 +30,7 @@ def init_dist(backend='nccl', **kwargs):
def main(): def main():
#### options #### options
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_imgset_rrdb_xl_wideres.yml') parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_imgset_switched_rrdb_small.yml')
parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none', parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none',
help='job launcher') help='job launcher')
parser.add_argument('--local_rank', type=int, default=0) parser.add_argument('--local_rank', type=int, default=0)
@ -187,7 +187,7 @@ def main():
#### log #### log
if current_step % opt['logger']['print_freq'] == 0: if current_step % opt['logger']['print_freq'] == 0:
logs = model.get_current_log() logs = model.get_current_log(current_step)
message = '[epoch:{:3d}, iter:{:8,d}, lr:('.format(epoch, current_step) message = '[epoch:{:3d}, iter:{:8,d}, lr:('.format(epoch, current_step)
for v in model.get_current_learning_rate(): for v in model.get_current_learning_rate():
message += '{:.3e},'.format(v) message += '{:.3e},'.format(v)