_base_ = [
    '../_base_/models/mask_rcnn_r50_fpn.py',
    '../_base_/datasets/nuim_instance.py',
    '../_base_/schedules/mmdet_schedule_1x.py', '../_base_/default_runtime.py'
]
model = dict(
    roi_head=dict(
        bbox_head=dict(num_classes=10), mask_head=dict(num_classes=10)))

file_client_args = dict(
    backend='petrel',
    path_mapping=dict({
        './data/nuscenes/': 's3://nuscenes/nuscenes/',
        'data/nuscenes/': 's3://nuscenes/nuscenes/'
    }))

test_pipeline = [
    dict(type='LoadImageFromFile'),
    dict(
        type='MultiScaleFlipAug',
        img_scale=(1600, 900),
        flip=False,
        transforms=[
            dict(type='Resize', keep_ratio=True),
            dict(type='RandomFlip'),
        ]),
    dict(
        type='PackDetInputs',
        meta_keys=('img_id', 'img_path', 'ori_shape', 'img_shape',
                   'scale_factor')),
]
data_root = 'data/nuimages/'
# data = dict(
#     val=dict(
#         ann_file=data_root + 'annotations/nuimages_v1.0-mini.json'),
#     test=dict(
#         ann_file=data_root + 'annotations/nuimages_v1.0-mini.json'))