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How to use custom_gt method in pandera
Best Python code snippet using pandera_python
basicvsr_reds4_custom_load_lr_small.py
Source:basicvsr_reds4_custom_load_lr_small.py 
1exp_name = 'basicvsr_reds4_custom_load_lr_small'2# model settings3model = dict(4 type='BasicVSR',5 generator=dict(6 type='BasicVSRNet',7 mid_channels=64,8 num_blocks=30,9 spynet_pretrained='https://download.openmmlab.com/mmediting/restorers/'10 'basicvsr/spynet_20210409-c6c1bd09.pth'),11 pixel_loss=dict(type='CharbonnierLoss', loss_weight=1.0, reduction='mean'))12# model training and testing settings13train_cfg = dict(fix_iter=5000)14test_cfg = dict(metrics=['PSNR', 'SSIM'], crop_border=0)15# dataset settings16train_dataset_type = 'SRREDSMultipleGTDataset_CUSTOM'17val_dataset_type = 'SRREDSMultipleGTDataset_CUSTOM'18train_pipeline = [19 dict(type='GenerateSegmentIndices', interval_list=[1]),20 dict(type='TemporalReverse', keys='lq_path', reverse_ratio=0),21 dict(22 type='LoadImageFromFileList',23 io_backend='disk',24 key='lq',25 channel_order='rgb'),26 dict(27 type='LoadImageFromFileList',28 io_backend='disk',29 key='gt',30 channel_order='rgb'),31 dict(type='RescaleToZeroOne', keys=['lq', 'gt']),32 dict(type='PairedRandomCrop', gt_patch_size=256),33 dict(34 type='Flip', keys=['lq', 'gt'], flip_ratio=0.5,35 direction='horizontal'),36 dict(type='Flip', keys=['lq', 'gt'], flip_ratio=0.5, direction='vertical'),37 dict(type='RandomTransposeHW', keys=['lq', 'gt'], transpose_ratio=0.5),38 dict(type='FramesToTensor', keys=['lq', 'gt']),39 dict(type='Collect', keys=['lq', 'gt'], meta_keys=['lq_path', 'gt_path'])40]41test_pipeline = [42 dict(type='GenerateSegmentIndices', interval_list=[1]),43 dict(44 type='LoadImageFromFileList',45 io_backend='disk',46 key='lq',47 channel_order='rgb'),48 dict(49 type='LoadImageFromFileList',50 io_backend='disk',51 key='gt',52 channel_order='rgb'),53 dict(type='RescaleToZeroOne', keys=['lq', 'gt']),54 dict(type='FramesToTensor', keys=['lq', 'gt']),55 dict(56 type='Collect',57 keys=['lq', 'gt'],58 meta_keys=['lq_path', 'gt_path', 'key'])59]60demo_pipeline = [61 dict(type='GenerateSegmentIndices', interval_list=[1]),62 dict(63 type='LoadImageFromFileList',64 io_backend='disk',65 key='lq',66 channel_order='rgb'),67 dict(type='RescaleToZeroOne', keys=['lq']),68 dict(type='FramesToTensor', keys=['lq']),69 dict(type='Collect', keys=['lq'], meta_keys=['lq_path', 'key'])70]71data = dict(72 workers_per_gpu=6,73 train_dataloader=dict(samples_per_gpu=16, drop_last=True), # 2 gpus74 val_dataloader=dict(samples_per_gpu=1),75 test_dataloader=dict(samples_per_gpu=1, workers_per_gpu=1),76 # train77 train=dict(78 type='RepeatDataset',79 times=1000,80 dataset=dict(81 type=train_dataset_type,82 lq_folder='/data/peiyuan/custom_train/custom_low_res',83 gt_folder='/data/peiyuan/custom_train/custom_gt',84 num_input_frames=15,85 pipeline=train_pipeline,86 scale=4,87 val_partition='REDS4',88 test_mode=False)),89 # val90 val=dict(91 type=val_dataset_type,92 lq_folder='/data/peiyuan/custom_train/custom_low_res',93 gt_folder='/data/peiyuan/custom_train/custom_gt',94 num_input_frames=100,95 pipeline=test_pipeline,96 scale=4,97 val_partition='REDS4',98 test_mode=True),99 # test100 test=dict(101 type=val_dataset_type,102 lq_folder='/data/peiyuan/custom_train/custom_low_res',103 gt_folder='/data/peiyuan/custom_train/custom_gt',104 num_input_frames=100,105 pipeline=test_pipeline,106 scale=4,107 val_partition='REDS4',108 test_mode=True),109)110# optimizer111optimizers = dict(112 generator=dict(113 type='Adam',114 lr=8e-5,115 betas=(0.9, 0.99),116 paramwise_cfg=dict(custom_keys={'spynet': dict(lr_mult=0.125)})))117# learning policy118total_iters = 150000119lr_config = dict(120 policy='CosineRestart',121 by_epoch=False,122 periods=[150000],123 restart_weights=[1],124 min_lr=1e-7)125checkpoint_config = dict(interval=2500, save_optimizer=True, by_epoch=False)126# remove gpu_collect=True in non distributed training127evaluation = dict(interval=2500, save_image=False, gpu_collect=True)128log_config = dict(129 interval=100,130 hooks=[131 dict(type='TextLoggerHook', by_epoch=False),132 # dict(type='TensorboardLoggerHook'),133 ])134visual_config = None135# runtime settings136dist_params = dict(backend='nccl')137log_level = 'INFO'138work_dir = f'./work_dirs/{exp_name}'139load_from = None140resume_from = None141workflow = [('train', 1)]...
basicvsr_reds4_custom_load.py
Source:basicvsr_reds4_custom_load.py
1exp_name = 'basicvsr_reds4_custom_load'2# model settings3model = dict(4 type='BasicVSR',5 generator=dict(6 type='BasicVSRNet',7 mid_channels=64,8 num_blocks=30,9 spynet_pretrained='https://download.openmmlab.com/mmediting/restorers/'10 'basicvsr/spynet_20210409-c6c1bd09.pth'),11 pixel_loss=dict(type='CharbonnierLoss', loss_weight=1.0, reduction='mean'))12# model training and testing settings13train_cfg = dict(fix_iter=5000)14test_cfg = dict(metrics=['PSNR', 'SSIM'], crop_border=0)15# dataset settings16train_dataset_type = 'SRREDSMultipleGTDataset_CUSTOM'17val_dataset_type = 'SRREDSMultipleGTDataset_CUSTOM'18train_pipeline = [19 dict(type='GenerateSegmentIndices', interval_list=[1]),20 dict(type='TemporalReverse', keys='lq_path', reverse_ratio=0),21 dict(22 type='LoadImageFromFileList',23 io_backend='disk',24 key='lq',25 channel_order='rgb'),26 dict(27 type='LoadImageFromFileList',28 io_backend='disk',29 key='gt',30 channel_order='rgb'),31 dict(type='RescaleToZeroOne', keys=['lq', 'gt']),32 dict(type='PairedRandomCrop', gt_patch_size=256),33 dict(34 type='Flip', keys=['lq', 'gt'], flip_ratio=0.5,35 direction='horizontal'),36 dict(type='Flip', keys=['lq', 'gt'], flip_ratio=0.5, direction='vertical'),37 dict(type='RandomTransposeHW', keys=['lq', 'gt'], transpose_ratio=0.5),38 dict(type='FramesToTensor', keys=['lq', 'gt']),39 dict(type='Collect', keys=['lq', 'gt'], meta_keys=['lq_path', 'gt_path'])40]41test_pipeline = [42 dict(type='GenerateSegmentIndices', interval_list=[1]),43 dict(44 type='LoadImageFromFileList',45 io_backend='disk',46 key='lq',47 channel_order='rgb'),48 dict(49 type='LoadImageFromFileList',50 io_backend='disk',51 key='gt',52 channel_order='rgb'),53 dict(type='RescaleToZeroOne', keys=['lq', 'gt']),54 dict(type='FramesToTensor', keys=['lq', 'gt']),55 dict(56 type='Collect',57 keys=['lq', 'gt'],58 meta_keys=['lq_path', 'gt_path', 'key'])59]60demo_pipeline = [61 dict(type='GenerateSegmentIndices', interval_list=[1]),62 dict(63 type='LoadImageFromFileList',64 io_backend='disk',65 key='lq',66 channel_order='rgb'),67 dict(type='RescaleToZeroOne', keys=['lq']),68 dict(type='FramesToTensor', keys=['lq']),69 dict(type='Collect', keys=['lq'], meta_keys=['lq_path', 'key'])70]71data = dict(72 workers_per_gpu=6,73 train_dataloader=dict(samples_per_gpu=16, drop_last=True), # 2 gpus74 val_dataloader=dict(samples_per_gpu=1),75 test_dataloader=dict(samples_per_gpu=1, workers_per_gpu=1),76 # train77 train=dict(78 type='RepeatDataset',79 times=1000,80 dataset=dict(81 type=train_dataset_type,82 lq_folder='/data/peiyuan/custom_train/custom_low_res',83 gt_folder='/data/peiyuan/custom_train/custom_gt',84 num_input_frames=15,85 pipeline=train_pipeline,86 scale=4,87 val_partition='REDS4',88 test_mode=False)),89 # val90 val=dict(91 type=val_dataset_type,92 lq_folder='/data/peiyuan/custom_train/custom_low_res',93 gt_folder='/data/peiyuan/custom_train/custom_gt',94 num_input_frames=100,95 pipeline=test_pipeline,96 scale=4,97 val_partition='REDS4',98 test_mode=True),99 # test100 test=dict(101 type=val_dataset_type,102 lq_folder='/data/peiyuan/custom_train/custom_low_res',103 gt_folder='/data/peiyuan/custom_train/custom_gt',104 num_input_frames=100,105 pipeline=test_pipeline,106 scale=4,107 val_partition='REDS4',108 test_mode=True),109)110# optimizer111optimizers = dict(112 generator=dict(113 type='Adam',114 lr=4e-4,115 betas=(0.9, 0.99),116 paramwise_cfg=dict(custom_keys={'spynet': dict(lr_mult=0.125)})))117# learning policy118total_iters = 150000119lr_config = dict(120 policy='CosineRestart',121 by_epoch=False,122 periods=[150000],123 restart_weights=[1],124 min_lr=1e-7)125checkpoint_config = dict(interval=1000, save_optimizer=True, by_epoch=False)126# remove gpu_collect=True in non distributed training127evaluation = dict(interval=1000, save_image=False, gpu_collect=True)128log_config = dict(129 interval=100,130 hooks=[131 dict(type='TextLoggerHook', by_epoch=False),132 # dict(type='TensorboardLoggerHook'),133 ])134visual_config = None135# runtime settings136dist_params = dict(backend='nccl')137log_level = 'INFO'138work_dir = f'./work_dirs/{exp_name}'139load_from = None140resume_from = None141workflow = [('train', 1)]...
basicvsr_reds4_custom.py
Source:basicvsr_reds4_custom.py
1exp_name = 'basicvsr_reds4_custom'2# model settings3model = dict(4 type='BasicVSR',5 generator=dict(6 type='BasicVSRNet',7 mid_channels=64,8 num_blocks=30,9 spynet_pretrained='https://download.openmmlab.com/mmediting/restorers/'10 'basicvsr/spynet_20210409-c6c1bd09.pth'),11 pixel_loss=dict(type='CharbonnierLoss', loss_weight=1.0, reduction='mean'))12# model training and testing settings13train_cfg = dict(fix_iter=5000)14test_cfg = dict(metrics=['PSNR', 'SSIM'], crop_border=0)15# dataset settings16train_dataset_type = 'SRREDSMultipleGTDataset_CUSTOM'17val_dataset_type = 'SRREDSMultipleGTDataset_CUSTOM'18train_pipeline = [19 dict(type='GenerateSegmentIndices', interval_list=[1]),20 dict(type='TemporalReverse', keys='lq_path', reverse_ratio=0),21 dict(22 type='LoadImageFromFileList',23 io_backend='disk',24 key='lq',25 channel_order='rgb'),26 dict(27 type='LoadImageFromFileList',28 io_backend='disk',29 key='gt',30 channel_order='rgb'),31 dict(type='RescaleToZeroOne', keys=['lq', 'gt']),32 dict(type='PairedRandomCrop', gt_patch_size=256),33 dict(34 type='Flip', keys=['lq', 'gt'], flip_ratio=0.5,35 direction='horizontal'),36 dict(type='Flip', keys=['lq', 'gt'], flip_ratio=0.5, direction='vertical'),37 dict(type='RandomTransposeHW', keys=['lq', 'gt'], transpose_ratio=0.5),38 dict(type='FramesToTensor', keys=['lq', 'gt']),39 dict(type='Collect', keys=['lq', 'gt'], meta_keys=['lq_path', 'gt_path'])40]41test_pipeline = [42 dict(type='GenerateSegmentIndices', interval_list=[1]),43 dict(44 type='LoadImageFromFileList',45 io_backend='disk',46 key='lq',47 channel_order='rgb'),48 dict(49 type='LoadImageFromFileList',50 io_backend='disk',51 key='gt',52 channel_order='rgb'),53 dict(type='RescaleToZeroOne', keys=['lq', 'gt']),54 dict(type='FramesToTensor', keys=['lq', 'gt']),55 dict(56 type='Collect',57 keys=['lq', 'gt'],58 meta_keys=['lq_path', 'gt_path', 'key'])59]60demo_pipeline = [61 dict(type='GenerateSegmentIndices', interval_list=[1]),62 dict(63 type='LoadImageFromFileList',64 io_backend='disk',65 key='lq',66 channel_order='rgb'),67 dict(type='RescaleToZeroOne', keys=['lq']),68 dict(type='FramesToTensor', keys=['lq']),69 dict(type='Collect', keys=['lq'], meta_keys=['lq_path', 'key'])70]71data = dict(72 workers_per_gpu=6,73 train_dataloader=dict(samples_per_gpu=16, drop_last=True), # 2 gpus74 val_dataloader=dict(samples_per_gpu=1),75 test_dataloader=dict(samples_per_gpu=1, workers_per_gpu=1),76 # train77 train=dict(78 type='RepeatDataset',79 times=1000,80 dataset=dict(81 type=train_dataset_type,82 lq_folder='/data/peiyuan/custom_train/custom_low_res',83 gt_folder='/data/peiyuan/custom_train/custom_gt',84 num_input_frames=15,85 pipeline=train_pipeline,86 scale=4,87 val_partition='REDS4',88 test_mode=False)),89 # val90 val=dict(91 type=val_dataset_type,92 lq_folder='/data/peiyuan/custom_train/custom_low_res',93 gt_folder='/data/peiyuan/custom_train/custom_gt',94 num_input_frames=100,95 pipeline=test_pipeline,96 scale=4,97 val_partition='REDS4',98 test_mode=True),99 # test100 test=dict(101 type=val_dataset_type,102 lq_folder='/data/peiyuan/custom_train/custom_low_res',103 gt_folder='/data/peiyuan/custom_train/custom_gt',104 num_input_frames=100,105 pipeline=test_pipeline,106 scale=4,107 val_partition='REDS4',108 test_mode=True),109)110# optimizer111optimizers = dict(112 generator=dict(113 type='Adam',114 lr=4e-4,115 betas=(0.9, 0.99),116 paramwise_cfg=dict(custom_keys={'spynet': dict(lr_mult=0.125)})))117# learning policy118total_iters = 150000119lr_config = dict(120 policy='CosineRestart',121 by_epoch=False,122 periods=[150000],123 restart_weights=[1],124 min_lr=1e-7)125checkpoint_config = dict(interval=1000, save_optimizer=True, by_epoch=False)126# remove gpu_collect=True in non distributed training127evaluation = dict(interval=1000, save_image=False, gpu_collect=True)128log_config = dict(129 interval=100,130 hooks=[131 dict(type='TextLoggerHook', by_epoch=False),132 # dict(type='TensorboardLoggerHook'),133 ])134visual_config = None135# runtime settings136dist_params = dict(backend='nccl')137log_level = 'INFO'138work_dir = f'./work_dirs/{exp_name}'139load_from = None140resume_from = None141workflow = [('train', 1)]...
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