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mit-han-lab / data-efficient-gans

[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
https://arxiv.org/abs/2006.10738
BSD 2-Clause "Simplified" License
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The difference between the generated image and the training image is too large #99

Open tdf1995 opened 2 years ago

tdf1995 commented 2 years ago

train_set: image generated images: image

@click.option('--outdir',default='/work/ai_lab/miner/data-efficient-gans/output', help='Where to save the results', required=True, metavar='DIR') @click.option('--gpus',default=2, help='Number of GPUs to use [default: 1]', type=int, metavar='INT') @click.option('--snap',default=10, help='Snapshot interval [default: 50 ticks]', type=int, metavar='INT') @click.option('--metrics', help='Comma-separated list or "none" [default: fid50k_full]', type=CommaSeparatedList()) @click.option('--seed', help='Random seed [default: 0]', type=int, metavar='INT') @click.option('-n', '--dry-run', help='Print training options and exit', is_flag=True)

Dataset.

@click.option('--data',default=r'/work/ai_lab/miner/data-efficient-gans/bicycle', help='Training data (directory or zip)', metavar='PATH', required=True) @click.option('--cond', help='Train conditional model based on dataset labels [default: false]', type=bool, metavar='BOOL') @click.option('--subset', help='Train with only N images [default: all]', type=int, metavar='INT') @click.option('--mirror',default=True, help='Enable dataset x-flips [default: false]', type=bool, metavar='BOOL')

Base config.

@click.option('--cfg', help='Base config [default: low_shot]', type=click.Choice(['low_shot', 'auto', 'stylegan2', 'paper256', 'paper512', 'paper1024', 'cifar'])) @click.option('--gamma', help='Override R1 gamma', type=float) @click.option('--kimg', help='Override training duration', type=int, metavar='INT') @click.option('--batch',default=8, help='Override batch size', type=int, metavar='INT')

Discriminator augmentation.

@click.option('--DiffAugment', help='Comma-separated list of DiffAugment policy [default: color,translation,cutout]', type=str) @click.option('--aug', help='Augmentation mode [default: ada]', type=click.Choice(['noaug', 'ada', 'fixed'])) @click.option('--p', help='Augmentation probability for --aug=fixed', type=float) @click.option('--target', help='ADA target value for --aug=ada', type=float) @click.option('--augpipe', help='Augmentation pipeline [default: bgc]', type=click.Choice(['blit', 'geom', 'color', 'filter', 'noise', 'cutout', 'bg', 'bgc', 'bgcf', 'bgcfn', 'bgcfnc']))

Transfer learning.

@click.option('--resume', help='Resume training [default: noresume]', metavar='PKL') @click.option('--freezed', help='Freeze-D [default: 0 layers]', type=int, metavar='INT')

Performance options.

@click.option('--fp32', help='Disable mixed-precision training', type=bool, metavar='BOOL') @click.option('--nhwc', help='Use NHWC memory format with FP16', type=bool, metavar='BOOL') @click.option('--nobench', help='Disable cuDNN benchmarking', type=bool, metavar='BOOL') @click.option('--allow-tf32', help='Allow PyTorch to use TF32 internally', type=bool, metavar='BOOL') @click.option('--workers',default=4, help='Override number of DataLoader workers', type=int, metavar='INT')

could you give me some advice to make the results better?Thanks