configs/_base_/det_pipelines/maskrcnn_pipeline.py

img_norm_cfg = dict(
    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)

train_pipeline = [
    dict(type='LoadImageFromFile', color_type='color_ignore_orientation'),
    dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
    dict(
        type='ScaleAspectJitter',
        img_scale=None,
        keep_ratio=False,
        resize_type='indep_sample_in_range',
        scale_range=(640, 2560)),
    dict(type='RandomFlip', flip_ratio=0.5),
    dict(type='Normalize', **img_norm_cfg),
    dict(
        type='RandomCropInstances',
        target_size=(640, 640),
        mask_type='union_all',
        instance_key='gt_masks'),
    dict(type='Pad', size_divisor=32),
    dict(type='DefaultFormatBundle'),
    dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels', 'gt_masks']),
]

# for ctw1500
img_scale_ctw1500 = (1600, 1600)
test_pipeline_ctw1500 = [
    dict(type='LoadImageFromFile', color_type='color_ignore_orientation'),
    dict(
        type='MultiScaleFlipAug',
        img_scale=img_scale_ctw1500,  # used by Resize
        flip=False,
        transforms=[
            dict(type='Resize', keep_ratio=True),
            dict(type='RandomFlip'),
            dict(type='Normalize', **img_norm_cfg),
            dict(type='ImageToTensor', keys=['img']),
            dict(type='Collect', keys=['img']),
        ])
]

# for icdar2015
img_scale_icdar2015 = (1920, 1920)
test_pipeline_icdar2015 = [
    dict(type='LoadImageFromFile', color_type='color_ignore_orientation'),
    dict(
        type='MultiScaleFlipAug',
        img_scale=img_scale_icdar2015,  # used by Resize
        flip=False,
        transforms=[
            dict(type='Resize', keep_ratio=True),
            dict(type='RandomFlip'),
            dict(type='Normalize', **img_norm_cfg),
            dict(type='ImageToTensor', keys=['img']),
            dict(type='Collect', keys=['img']),
        ])
]