64 lines
1.7 KiB
YAML
64 lines
1.7 KiB
YAML
dataset:
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target: dataset.realesrgan.RealESRGANDataset
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params:
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# Path to the file list.
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file_list: preset/train_datasets/val.list
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out_size: 512
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crop_type: center
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use_hflip: true
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use_rot: false
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blur_kernel_size: 21
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kernel_list: ['iso', 'aniso', 'generalized_iso', 'generalized_aniso', 'plateau_iso', 'plateau_aniso']
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kernel_prob: [0.45, 0.25, 0.12, 0.03, 0.12, 0.03]
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sinc_prob: 0.1
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blur_sigma: [0.2, 1.5]
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betag_range: [0.5, 2.0]
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betap_range: [1, 1.5]
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blur_kernel_size2: 11
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kernel_list2: ['iso', 'aniso', 'generalized_iso', 'generalized_aniso', 'plateau_iso', 'plateau_aniso']
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kernel_prob2: [0.45, 0.25, 0.12, 0.03, 0.12, 0.03]
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sinc_prob2: 0.1
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blur_sigma2: [0.2, 1.0]
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betag_range2: [0.5, 2.0]
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betap_range2: [1, 1.5]
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final_sinc_prob: 0.8
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data_loader:
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batch_size: 1
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shuffle: false
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num_workers: 16
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prefetch_factor: 2
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drop_last: true
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batch_transform:
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target: dataset.batch_transform.RealESRGANBatchTransform
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params:
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use_sharpener: false
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resize_hq: false
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# Queue size of training pool, this should be multiples of batch_size.
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queue_size: 256
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# the first degradation process
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resize_prob: [0.2, 0.7, 0.1] # up, down, keep
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resize_range: [0.3, 1.5]
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gaussian_noise_prob: 0.5
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noise_range: [1, 15]
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poisson_scale_range: [0.05, 2.0]
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gray_noise_prob: 0.4
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jpeg_range: [60, 95]
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# the second degradation process
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stage2_scale: 4
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second_blur_prob: 0.5
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resize_prob2: [0.3, 0.4, 0.3] # up, down, keep
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resize_range2: [0.6, 1.2]
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gaussian_noise_prob2: 0.5
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noise_range2: [1, 12]
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poisson_scale_range2: [0.05, 1.0]
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gray_noise_prob2: 0.4
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jpeg_range2: [60, 100] |