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- _base_ = './queryinst_r50_fpn_ms-480-800-3x_coco.py'
- num_proposals = 300
- model = dict(
- rpn_head=dict(num_proposals=num_proposals),
- test_cfg=dict(
- _delete_=True,
- rpn=None,
- rcnn=dict(max_per_img=num_proposals, mask_thr_binary=0.5)))
- # augmentation strategy originates from DETR.
- train_pipeline = [
- dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
- dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
- dict(type='RandomFlip', prob=0.5),
- dict(
- type='RandomChoice',
- transforms=[[
- dict(
- type='RandomChoiceResize',
- scales=[(480, 1333), (512, 1333), (544, 1333), (576, 1333),
- (608, 1333), (640, 1333), (672, 1333), (704, 1333),
- (736, 1333), (768, 1333), (800, 1333)],
- keep_ratio=True)
- ],
- [
- dict(
- type='RandomChoiceResize',
- scales=[(400, 1333), (500, 1333), (600, 1333)],
- keep_ratio=True),
- dict(
- type='RandomCrop',
- crop_type='absolute_range',
- crop_size=(384, 600),
- allow_negative_crop=True),
- dict(
- type='RandomChoiceResize',
- scales=[(480, 1333), (512, 1333), (544, 1333),
- (576, 1333), (608, 1333), (640, 1333),
- (672, 1333), (704, 1333), (736, 1333),
- (768, 1333), (800, 1333)],
- keep_ratio=True)
- ]]),
- dict(type='PackDetInputs')
- ]
- train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
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