forked from mrq/DL-Art-School
Add doResizeLoss to dataset
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.
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@ -146,6 +146,12 @@ class LQGTDataset(data.Dataset):
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img_GT = cv2.resize(img_GT, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR)
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img_PIX = cv2.resize(img_PIX, (GT_size, GT_size), interpolation=cv2.INTER_LINEAR)
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if self.opt['doResizeLoss']:
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r = random.randrange(0, 10)
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if r > 5:
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img_LQ = cv2.resize(img_LQ, (int(LQ_size/2), int(LQ_size/2)), interpolation=cv2.INTER_LINEAR)
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img_LQ = cv2.resize(img_LQ, (LQ_size, LQ_size), interpolation=cv2.INTER_LINEAR)
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# augmentation - flip, rotate
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img_LQ, img_GT, img_PIX = util.augment([img_LQ, img_GT, img_PIX], self.opt['use_flip'],
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self.opt['use_rot'])
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@ -30,7 +30,7 @@ def init_dist(backend='nccl', **kwargs):
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def main():
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#### options
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parser = argparse.ArgumentParser()
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parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_imgset_rrdb_xl_wideres.yml')
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parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_imgset_switched_rrdb_small.yml')
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parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none',
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help='job launcher')
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parser.add_argument('--local_rank', type=int, default=0)
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@ -187,7 +187,7 @@ def main():
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#### log
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if current_step % opt['logger']['print_freq'] == 0:
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logs = model.get_current_log()
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logs = model.get_current_log(current_step)
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message = '[epoch:{:3d}, iter:{:8,d}, lr:('.format(epoch, current_step)
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for v in model.get_current_learning_rate():
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message += '{:.3e},'.format(v)
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