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- _base_ = [
- '../_base_/models/mask-rcnn_r50_fpn.py',
- '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py',
- '../_base_/datasets/dsdl.py'
- ]
- # dsdl dataset settings.
- # please visit our platform [OpenDataLab](https://opendatalab.com/)
- # to downloaded dsdl dataset.
- data_root = 'data/COCO2017'
- img_prefix = 'original'
- train_ann = 'dsdl/set-train/train.yaml'
- val_ann = 'dsdl/set-val/val.yaml'
- specific_key_path = dict(ignore_flag='./annotations/*/iscrowd')
- backend_args = None
- train_pipeline = [
- dict(type='LoadImageFromFile', backend_args=backend_args),
- dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
- dict(type='Resize', scale=(1333, 800), keep_ratio=True),
- dict(type='RandomFlip', prob=0.5),
- dict(type='PackDetInputs')
- ]
- test_pipeline = [
- dict(type='LoadImageFromFile', backend_args=backend_args),
- dict(type='Resize', scale=(1333, 800), keep_ratio=True),
- dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
- dict(
- type='PackDetInputs',
- meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
- 'scale_factor', 'instances'))
- ]
- train_dataloader = dict(
- dataset=dict(
- with_polygon=True,
- specific_key_path=specific_key_path,
- data_root=data_root,
- ann_file=train_ann,
- data_prefix=dict(img_path=img_prefix),
- filter_cfg=dict(filter_empty_gt=True, min_size=32, bbox_min_size=32),
- pipeline=train_pipeline,
- ))
- val_dataloader = dict(
- dataset=dict(
- with_polygon=True,
- specific_key_path=specific_key_path,
- data_root=data_root,
- ann_file=val_ann,
- data_prefix=dict(img_path=img_prefix),
- pipeline=test_pipeline,
- ))
- test_dataloader = val_dataloader
- val_evaluator = dict(
- type='CocoMetric', metric=['bbox', 'segm'], format_only=False)
- test_evaluator = val_evaluator
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