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55 changes: 55 additions & 0 deletions
55
SegFormer/local_configs/_base_/datasets/msd_lungs_balanced.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,55 @@ | ||
| # dataset settings | ||
| dataset_type = 'MSDLungsBalancedDataset' | ||
| data_root = 'data/MSD/Task06_Lungs_RGB_2D_512_Balanced' | ||
| img_norm_cfg = dict( | ||
| mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) | ||
| crop_size = (512, 512) | ||
| train_pipeline = [ | ||
| dict(type='LoadImageFromFile'), | ||
| dict(type='LoadAnnotations'), | ||
| dict(type='Resize', img_scale=(512, 512), ratio_range=(0.5, 2.0)), | ||
| dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75), | ||
| dict(type='RandomFlip', prob=0.5), | ||
| dict(type='PhotoMetricDistortion'), | ||
| dict(type='Normalize', **img_norm_cfg), | ||
| dict(type='Pad', size=crop_size, pad_val=0, seg_pad_val=255), | ||
| dict(type='DefaultFormatBundle'), | ||
| dict(type='Collect', keys=['img', 'gt_semantic_seg']), | ||
| ] | ||
| test_pipeline = [ | ||
| dict(type='LoadImageFromFile'), | ||
| dict( | ||
| type='MultiScaleFlipAug', | ||
| img_scale=(512, 512), | ||
| # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75], | ||
| flip=False, | ||
| transforms=[ | ||
| dict(type='Resize', keep_ratio=True), | ||
| dict(type='RandomFlip'), | ||
| dict(type='Normalize', **img_norm_cfg), | ||
| dict(type='ImageToTensor', keys=['img']), | ||
| dict(type='Collect', keys=['img']), | ||
| ]) | ||
| ] | ||
| data = dict( | ||
| samples_per_gpu=2, | ||
| workers_per_gpu=2, | ||
| train=dict( | ||
| type=dataset_type, | ||
| data_root='../../data/MSD/Task06_Lungs_RGB_2D_512_Balanced', | ||
| img_dir='images/training', | ||
| ann_dir='annotations/training', | ||
| pipeline=train_pipeline), | ||
| val=dict( | ||
| type=dataset_type, | ||
| data_root='../../data/MSD/Task06_Lungs_RGB_2D_512_Balanced', | ||
| img_dir='images/validation', | ||
| ann_dir='annotations/validation', | ||
| pipeline=test_pipeline), | ||
| test=dict( | ||
| type=dataset_type, | ||
| data_root='../../data/MSD/Task06_Lungs_RGB_2D_512_Balanced', | ||
| img_dir='images/training', | ||
| ann_dir='annotations/validation', | ||
| pipeline=test_pipeline) | ||
| ) |
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47
SegFormer/local_configs/segformer/MSD/segformer.512x512.msd_lungs_balanced.20k.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,47 @@ | ||
| _base_ = [ | ||
| '../../_base_/models/segformer.py', | ||
| '../../_base_/datasets/msd_lungs_balanced.py', | ||
| '../../_base_/default_runtime.py', | ||
| '../../_base_/schedules/schedule_20k.py' | ||
| ] | ||
|
|
||
| # model settings | ||
| norm_cfg = dict(type='SyncBN', requires_grad=True) | ||
| find_unused_parameters = True | ||
| model = dict( | ||
| type='EncoderDecoder', | ||
| pretrained='../../pretrained/ImageNet-1K/mit_b0.pth', | ||
| backbone=dict( | ||
| type='mit_b0', | ||
| style='pytorch'), | ||
| decode_head=dict( | ||
| type='SegFormerHead', | ||
| in_channels=[32, 64, 160, 256], | ||
| in_index=[0, 1, 2, 3], | ||
| feature_strides=[4, 8, 16, 32], | ||
| channels=128, | ||
| dropout_ratio=0.1, | ||
| num_classes=150, | ||
| norm_cfg=norm_cfg, | ||
| align_corners=False, | ||
| decoder_params=dict(embed_dim=256), | ||
| loss_decode=dict(type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), | ||
| # model training and testing settings | ||
| train_cfg=dict(), | ||
| test_cfg=dict(mode='whole')) | ||
|
|
||
| # optimizer | ||
| optimizer = dict(_delete_=True, type='AdamW', lr=0.00006, betas=(0.9, 0.999), weight_decay=0.01, | ||
| paramwise_cfg=dict(custom_keys={'pos_block': dict(decay_mult=0.), | ||
| 'norm': dict(decay_mult=0.), | ||
| 'head': dict(lr_mult=10.) | ||
| })) | ||
|
|
||
| lr_config = dict(_delete_=True, policy='poly', | ||
| warmup='linear', | ||
| warmup_iters=1500, | ||
| warmup_ratio=1e-6, | ||
| power=1.0, min_lr=0.0, by_epoch=False) | ||
|
|
||
| data = dict(samples_per_gpu=2) | ||
| evaluation = dict(interval=16000, metric='mIoU') |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,24 @@ | ||
| from .builder import DATASETS | ||
| from .custom import CustomDataset | ||
|
|
||
|
|
||
| @DATASETS.register_module() | ||
| class MSDLungsBalancedDataset(CustomDataset): | ||
| """ADE20K dataset. | ||
| In segmentation map annotation for ADE20K, 0 stands for background, which | ||
| is not included in 150 categories. ``reduce_zero_label`` is fixed to True. | ||
| The ``img_suffix`` is fixed to '.jpg' and ``seg_map_suffix`` is fixed to | ||
| '.png'. | ||
| """ | ||
| CLASSES = ( | ||
| "no ailment", "ailment") | ||
|
|
||
| PALETTE = [[120, 120, 120], [92, 0, 255]] | ||
|
|
||
| def __init__(self, **kwargs): | ||
| super(MSDLungsBalancedDataset, self).__init__( | ||
| img_suffix='.png', | ||
| seg_map_suffix='.png', | ||
| reduce_zero_label=True, | ||
| **kwargs) |