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- _base_ = './mask-rcnn_r101_fpn_1x_coco.py'
- model = dict(
- # ResNeXt-101-32x8d model trained with Caffe2 at FB,
- # so the mean and std need to be changed.
- data_preprocessor=dict(
- mean=[103.530, 116.280, 123.675],
- std=[57.375, 57.120, 58.395],
- bgr_to_rgb=False),
- backbone=dict(
- type='ResNeXt',
- depth=101,
- groups=32,
- base_width=8,
- num_stages=4,
- out_indices=(0, 1, 2, 3),
- frozen_stages=1,
- norm_cfg=dict(type='BN', requires_grad=False),
- style='pytorch',
- init_cfg=dict(
- type='Pretrained',
- checkpoint='open-mmlab://detectron2/resnext101_32x8d')))
- train_pipeline = [
- dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
- dict(
- type='LoadAnnotations',
- with_bbox=True,
- with_mask=True,
- poly2mask=False),
- dict(
- type='RandomChoiceResize',
- scales=[(1333, 640), (1333, 672), (1333, 704), (1333, 736),
- (1333, 768), (1333, 800)],
- keep_ratio=True),
- dict(type='RandomFlip', prob=0.5),
- dict(type='PackDetInputs'),
- ]
- train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
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