forked from mrq/DL-Art-School
Misc
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@ -21,8 +21,8 @@ def main():
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# compression time. If read raw images during training, use 0 for faster IO speed.
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if mode == 'single':
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full_multiplier = .25
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opt['input_folder'] = 'F:\\4k6k\\datasets\\images\\goodeats\\hq\\new_season\\lr_hr_enc\\lr\\images'
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opt['save_folder'] = 'F:\\4k6k\\datasets\\images\\goodeats\\hq\\new_season\\lr_hr_enc\\lr\\images_tiled'
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opt['input_folder'] = 'F:\\4k6k\\datasets\\images\\fullvideo\\full_images'
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opt['save_folder'] = 'F:\\4k6k\\datasets\\images\\fullvideo\\256_tiled'
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opt['crop_sz'] = int(256 * full_multiplier) # the size of each sub-image
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opt['step'] = int(128 * full_multiplier) # step of the sliding crop window
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opt['thres_sz'] = int(64 * full_multiplier) # size threshold
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@ -21,12 +21,12 @@ def main():
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if mode == 'single':
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opt['dest'] = 'file'
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opt['input_folder'] = 'F:\\4k6k\\datasets\\ns_images\\vixen\\full_video_segments'
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opt['save_folder'] = 'F:\\4k6k\\datasets\\ns_images\\vixen\\full_video_256_tiled_with_ref'
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opt['crop_sz'] = [256, 512, 1024] # the size of each sub-image
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opt['step'] = [256, 512, 1024] # step of the sliding crop window
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opt['input_folder'] = 'F:\\4k6k\\datasets\\images\\fullvideo\\full_images'
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opt['save_folder'] = 'F:\\4k6k\\datasets\\images\\fullvideo\\256_tiled'
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opt['crop_sz'] = [512, 1024] # the size of each sub-image
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opt['step'] = [512, 1024] # step of the sliding crop window
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opt['thres_sz'] = 128 # size threshold
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opt['resize_final_img'] = [1, .5, .25]
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opt['resize_final_img'] = [.5, .25]
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opt['only_resize'] = False
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save_folder = opt['save_folder']
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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_exd_imgset_spsr7.yml')
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parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_exd_imgset_chained_structured_trans_invariance.yml')
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parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none', help='job launcher')
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parser.add_argument('--local_rank', type=int, default=0)
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args = parser.parse_args()
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