| dataset_type = 'GrassDataset' |
| data_root = 'data/grass' |
|
|
| crop_size = (256, 256) |
| train_pipeline = [ |
| dict(type='LoadImageFromFile'), |
| dict(type='LoadAnnotations'), |
| dict(type='RandomCrop', crop_size=crop_size), |
| dict(type='RandomFlip', prob=0.5), |
| dict(type='PhotoMetricDistortion'), |
| dict(type='PackSegInputs') |
| ] |
| test_pipeline = [ |
| dict(type='LoadImageFromFile'), |
| dict(type='Resize', scale=crop_size), |
| |
| |
| dict(type='LoadAnnotations'), |
| dict(type='PackSegInputs') |
| ] |
|
|
| train_dataloader = dict( |
| batch_size=4, |
| num_workers=4, |
| persistent_workers=True, |
| sampler=dict(type='InfiniteSampler', shuffle=True), |
| dataset=dict( |
| type=dataset_type, |
| data_root=data_root, |
| data_prefix=dict( |
| img_path='img_dir/train', |
| seg_map_path='ann_dir/train'), |
| pipeline=train_pipeline)) |
| val_dataloader = dict( |
| batch_size=4, |
| num_workers=4, |
| persistent_workers=True, |
| sampler=dict(type='DefaultSampler', shuffle=False), |
| dataset=dict( |
| type=dataset_type, |
| data_root=data_root, |
| data_prefix=dict( |
| img_path='img_dir/val', |
| seg_map_path='ann_dir/val'), |
| pipeline=test_pipeline)) |
|
|
| test_dataloader = val_dataloader |
|
|
| val_evaluator = dict(type='IoUMetric', iou_metrics=["mIoU", "mDice", "mFscore"],) |
| test_evaluator = val_evaluator |
