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| # dataset settings | |
| from mmcv.transforms import LoadImageFromFile, RandomResize | |
| from mmengine.dataset import DefaultSampler | |
| from mmdet.datasets import AspectRatioBatchSampler | |
| from mmdet.datasets.transforms import RandomFlip, RandomCrop, PackDetInputs, Resize | |
| from seg.datasets.pipeliens.loading import LoadPanopticAnnotationsHB | |
| from seg.datasets.cityscapes import CityscapesPanopticDataset | |
| from seg.evaluation.metrics.cityscapes_panoptic_metric import CityscapesPanopticMetric | |
| data_root = 'data/cityscapes/' | |
| backend_args = None | |
| image_size = (1024, 1024) | |
| train_pipeline = [ | |
| dict( | |
| type=LoadImageFromFile, | |
| to_float32=True, | |
| backend_args=backend_args), | |
| dict( | |
| type=LoadPanopticAnnotationsHB, | |
| with_bbox=True, | |
| with_mask=True, | |
| with_seg=True, | |
| backend_args=backend_args), | |
| dict(type=RandomFlip, prob=0.5), | |
| dict( | |
| type=RandomResize, | |
| resize_type=Resize, | |
| scale=image_size, | |
| ratio_range=(.8, 1.5), | |
| keep_ratio=True, | |
| ), | |
| dict( | |
| type=RandomCrop, | |
| crop_size=image_size, | |
| crop_type='absolute', | |
| recompute_bbox=True, | |
| allow_negative_crop=True), | |
| dict(type=PackDetInputs) | |
| ] | |
| train_dataloader = dict( | |
| batch_size=2, | |
| num_workers=2, | |
| persistent_workers=True, | |
| sampler=dict(type=DefaultSampler, shuffle=True), | |
| batch_sampler=dict(type=AspectRatioBatchSampler), | |
| dataset=dict( | |
| type=CityscapesPanopticDataset, | |
| data_root=data_root, | |
| ann_file='annotations/cityscapes_panoptic_train_trainId.json', | |
| data_prefix=dict(img='leftImg8bit/train/', | |
| seg='annotations/cityscapes_panoptic_train_trainId/'), | |
| filter_cfg=dict(filter_empty_gt=True, min_size=32), | |
| pipeline=train_pipeline, | |
| backend_args=backend_args | |
| ) | |
| ) | |
| test_pipeline = [ | |
| dict(type=LoadImageFromFile, backend_args=backend_args), | |
| dict(type=Resize, scale=(2048, 1024), keep_ratio=True), | |
| dict(type=LoadPanopticAnnotationsHB, backend_args=backend_args), | |
| dict( | |
| type=PackDetInputs, | |
| meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape', 'scale_factor', 'instances') | |
| ) | |
| ] | |
| val_dataloader = dict( | |
| batch_size=2, | |
| num_workers=2, | |
| persistent_workers=True, | |
| drop_last=False, | |
| sampler=dict(type=DefaultSampler, shuffle=False), | |
| dataset=dict( | |
| type=CityscapesPanopticDataset, | |
| data_root=data_root, | |
| ann_file='annotations/cityscapes_panoptic_val_trainId.json', | |
| data_prefix=dict(img='leftImg8bit/val/', | |
| seg='annotations/cityscapes_panoptic_val_trainId/'), | |
| test_mode=True, | |
| pipeline=test_pipeline, | |
| backend_args=backend_args | |
| ) | |
| ) | |
| test_dataloader = val_dataloader | |
| val_evaluator = dict( | |
| type=CityscapesPanopticMetric, | |
| ann_file=data_root + 'annotations/cityscapes_panoptic_val_trainId.json', | |
| seg_prefix=data_root + 'annotations/cityscapes_panoptic_val_trainId/', | |
| backend_args=backend_args | |
| ) | |
| test_evaluator = val_evaluator | |