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Group Internal Merge ACDC Dataset.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,65 @@ | ||
| # dataset settings | ||
| dataset_type = 'ACDCDataset' | ||
| data_root = 'data/acdc/' | ||
| crop_size = (512, 1024) | ||
| train_pipeline = [ | ||
| dict(type='LoadImageFromFile'), | ||
| dict(type='LoadAnnotations'), | ||
| dict( | ||
| type='RandomResize', | ||
| scale=(2048, 1024), | ||
| ratio_range=(0.5, 2.0), | ||
| keep_ratio=True), | ||
| dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75), | ||
| dict(type='RandomFlip', prob=0.5), | ||
| dict(type='PhotoMetricDistortion'), | ||
| dict(type='PackSegInputs') | ||
| ] | ||
| test_pipeline = [ | ||
| dict(type='LoadImageFromFile'), | ||
| dict(type='Resize', scale=(2048, 1024), keep_ratio=True), | ||
| # add loading annotation after ``Resize`` because ground truth | ||
| # does not need to do resize data transform | ||
| dict(type='LoadAnnotations'), | ||
| dict(type='PackSegInputs') | ||
| ] | ||
| img_ratios = [0.5, 0.75, 1.0, 1.25, 1.5, 1.75] | ||
| tta_pipeline = [ | ||
| dict(type='LoadImageFromFile', backend_args=None), | ||
| dict( | ||
| type='TestTimeAug', | ||
| transforms=[ | ||
| [ | ||
| dict(type='Resize', scale_factor=r, keep_ratio=True) | ||
| for r in img_ratios | ||
| ], | ||
| [ | ||
| dict(type='RandomFlip', prob=0., direction='horizontal'), | ||
| dict(type='RandomFlip', prob=1., direction='horizontal') | ||
| ], [dict(type='LoadAnnotations')], [dict(type='PackSegInputs')] | ||
| ]) | ||
| ] | ||
| train_dataloader = dict( | ||
| batch_size=2, | ||
| num_workers=2, | ||
| persistent_workers=True, | ||
| sampler=dict(type='InfiniteSampler', shuffle=True), | ||
| dataset=dict( | ||
| type=dataset_type, | ||
| data_root=data_root, | ||
| data_prefix=dict(img_path='rgb_anno/train', seg_map_path='gt/train'), | ||
| pipeline=train_pipeline)) | ||
| val_dataloader = dict( | ||
| batch_size=1, | ||
| 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='rgb_anno/test', seg_map_path='gt/test'), | ||
| pipeline=test_pipeline)) | ||
| test_dataloader = val_dataloader | ||
|
|
||
| val_evaluator = dict(type='IoUMetric', iou_metrics=['mIoU']) | ||
| test_evaluator = val_evaluator |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,7 @@ | ||
| _base_ = [ | ||
| '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/acdc.py', | ||
| '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' | ||
| ] | ||
| crop_size = (512, 1024) | ||
| data_preprocessor = dict(size=crop_size) | ||
| model = dict(data_preprocessor=data_preprocessor) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,15 @@ | ||
| # Copyright (c) OpenMMLab. All rights reserved. | ||
| from mmseg.registry import DATASETS | ||
| from .cityscapes import CityscapesDataset | ||
|
|
||
|
|
||
| @DATASETS.register_module() | ||
| class ACDCDataset(CityscapesDataset): | ||
| """ACDCDataset dataset.""" | ||
|
|
||
| def __init__(self, | ||
| img_suffix='_rgb_anon.png', | ||
| seg_map_suffix='_gt_labelTrainIds.png', | ||
| **kwargs) -> None: | ||
| super().__init__( | ||
| img_suffix=img_suffix, seg_map_suffix=seg_map_suffix, **kwargs) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,78 @@ | ||
| # Copyright (c) OpenMMLab. All rights reserved. | ||
| import argparse | ||
| import os | ||
| import os.path as osp | ||
| import shutil | ||
|
|
||
| from mmengine.utils import mkdir_or_exist | ||
|
|
||
|
|
||
| def parse_args(): | ||
| parser = argparse.ArgumentParser( | ||
| description='Convert ACDC dataset to mmsegmentation format') | ||
| parser.add_argument('raw_data', help='the path of raw data') | ||
| parser.add_argument( | ||
| '-o', '--out_dir', help='output path', default='./data/acdc') | ||
| parser.add_argument( | ||
| '--split', | ||
| choices=['fog', 'night', 'rain', 'snow', 'all'], | ||
| default='night') | ||
| args = parser.parse_args() | ||
| return args | ||
|
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|
|
||
| def main(): | ||
| args = parse_args() | ||
|
|
||
| try: | ||
| shutil.rmtree(args.out_dir) | ||
| print('Directory removed successfully') | ||
| except OSError as e: | ||
| print(f'Error: {e.strerror}') | ||
|
|
||
| print('Making directories...') | ||
| mkdir_or_exist(args.out_dir) | ||
| for subdir in ['gt/test', 'rgb_anno/test', 'gt/train', 'rgb_anno/train']: | ||
| mkdir_or_exist(osp.join(args.out_dir, subdir)) | ||
|
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| print('Moving images and annotations...') | ||
|
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| if args.split == 'all': | ||
| anno_str_test = '/val/' | ||
| gt_str_test = '/val/' | ||
| anno_str_train = '/train/' | ||
| gt_str_train = '/train/' | ||
| else: | ||
| anno_str_test = f'rgb_anon/{args.split}/val/' | ||
| gt_str_test = f'gt/{args.split}/val/' | ||
| anno_str_train = f'rgb_anon/{args.split}/train/' | ||
| gt_str_train = f'gt/{args.split}/train/' | ||
|
|
||
| for dirpath, _, filenames in os.walk(args.raw_data): | ||
| for filename in filenames: | ||
| full_path = os.path.join(dirpath, filename) | ||
|
|
||
| if anno_str_test in full_path: | ||
| if full_path.endswith('_rgb_anon.png'): | ||
| new_path = os.path.join(args.out_dir, 'rgb_anno/test', | ||
| filename) | ||
| shutil.copy(full_path, new_path) | ||
| elif gt_str_test in full_path: | ||
| if full_path.endswith('_gt_labelTrainIds.png'): | ||
| new_path = os.path.join(args.out_dir, 'gt/test', filename) | ||
| shutil.copy(full_path, new_path) | ||
| if anno_str_train in full_path: | ||
| if full_path.endswith('_rgb_anon.png'): | ||
| new_path = os.path.join(args.out_dir, 'rgb_anno/train', | ||
| filename) | ||
| shutil.copy(full_path, new_path) | ||
| elif gt_str_train in full_path: | ||
| if full_path.endswith('_gt_labelTrainIds.png'): | ||
| new_path = os.path.join(args.out_dir, 'gt/train', filename) | ||
| shutil.copy(full_path, new_path) | ||
|
|
||
| print('Done!') | ||
|
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|
|
||
| if __name__ == '__main__': | ||
| main() |