_base_ = [
    '../common/ms-poly_3x_coco-instance.py',
    '../_base_/models/mask-rcnn_r50_fpn.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')))

_base_ = [
    '../common/mstrain-poly_3x_coco_instance.py',
    '../_base_/models/mask_rcnn_r50_fpn.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')))
