166 lines
3.5 KiB
YAML
166 lines
3.5 KiB
YAML
name: huawei-TSIT-1
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engine: GauGAN
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result_dir: ./result
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max_pairs: 1000000
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misc:
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random_seed: 324
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handler:
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clear_cuda_cache: True
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set_epoch_for_dist_sampler: True
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checkpoint:
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epoch_interval: 1 # checkpoint once per `epoch_interval` epoch
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n_saved: 2
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tensorboard:
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scalar: 100 # log scalar `scalar` times per epoch
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image: 4 # log image `image` times per epoch
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test:
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random: True
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images: 10
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model:
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generator:
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_type: TSIT-Generator
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_add_spectral_norm: True
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in_channels: 3
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out_channels: 3
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num_blocks: 7
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# discriminator:
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# _type: MultiScaleDiscriminator
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# _add_spectral_norm: True
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# num_scale: 2
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# down_sample_method: "bilinear"
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# discriminator_cfg:
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# _type: PatchDiscriminator
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# in_channels: 3
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# base_channels: 64
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# num_conv: 4
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# need_intermediate_feature: True
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discriminator:
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_type: PatchDiscriminator
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_add_spectral_norm: True
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in_channels: 3
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base_channels: 64
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num_conv: 4
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need_intermediate_feature: True
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loss:
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gan:
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loss_type: hinge
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weight: 1.0
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real_label_val: 1
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fake_label_val: 0.0
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perceptual:
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layer_weights:
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"1": 0.03125
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"6": 0.0625
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"11": 0.125
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"20": 0.25
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"29": 1
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criterion: 'L1'
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style_loss: False
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perceptual_loss: True
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weight: 1
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mgc:
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weight: 5
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fm:
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weight: 1
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edge:
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weight: 0
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hed_pretrained_model_path: ./network-bsds500.pytorch
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optimizers:
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generator:
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_type: Adam
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lr: 1e-4
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betas: [ 0, 0.9 ]
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weight_decay: 0.0001
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discriminator:
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_type: Adam
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lr: 4e-4
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betas: [ 0, 0.9 ]
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weight_decay: 0.0001
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data:
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train:
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scheduler:
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start_proportion: 0.5
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target_lr: 0
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buffer_size: 0
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dataloader:
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batch_size: 1
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shuffle: True
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num_workers: 2
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pin_memory: True
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drop_last: True
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dataset:
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_type: GenerationUnpairedDataset
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root_a: "/data/face2cartoon/all_face"
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root_b: "/data/selfie2anime/trainB/"
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random_pair: True
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pipeline_a:
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- Load
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- RandomCrop:
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size: [ 178, 178 ]
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- Resize:
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size: [ 256, 256 ]
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- RandomHorizontalFlip
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- ToTensor
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- Normalize:
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mean: [ 0.5, 0.5, 0.5 ]
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std: [ 0.5, 0.5, 0.5 ]
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pipeline_b:
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- Load
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- Resize:
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size: [ 286, 286 ]
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- RandomCrop:
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size: [ 256, 256 ]
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- RandomHorizontalFlip
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- ToTensor
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- Normalize:
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mean: [ 0.5, 0.5, 0.5 ]
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std: [ 0.5, 0.5, 0.5 ]
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test:
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which: video_dataset
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dataloader:
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batch_size: 1
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shuffle: False
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num_workers: 1
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pin_memory: False
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drop_last: False
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dataset:
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_type: GenerationUnpairedDataset
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root_a: "/data/face2cartoon/test/human"
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root_b: "/data/face2cartoon/test/anime"
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random_pair: True
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pipeline_a:
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- Load
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- Resize:
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size: [ 256, 256 ]
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- ToTensor
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- Normalize:
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mean: [ 0.5, 0.5, 0.5 ]
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std: [ 0.5, 0.5, 0.5 ]
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pipeline_b:
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- Load
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- Resize:
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size: [ 256, 256 ]
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- ToTensor
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- Normalize:
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mean: [ 0.5, 0.5, 0.5 ]
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std: [ 0.5, 0.5, 0.5 ]
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video_dataset:
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_type: SingleFolderDataset
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root: "/data/i2i/VoxCeleb2Anime/test_video_frames/"
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with_path: True
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pipeline:
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- Load
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- Resize:
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size: [ 256, 256 ]
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- ToTensor
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- Normalize:
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mean: [ 0.5, 0.5, 0.5 ]
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std: [ 0.5, 0.5, 0.5 ]
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