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# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
# dataset settings
dataset_type = 'CocoSegDataset'
data_root = 'data/coco/'
# Example to use different file client
# Method 1: simply set the data root and let the file I/O module
# automatically infer from prefix (not support LMDB and Memcache yet)
# data_root = 's3://openmmlab/datasets/detection/coco/'
# Method 2: Use `backend_args`, `file_client_args` in versions before 3.0.0rc6
# backend_args = dict(
# backend='petrel',
# path_mapping=dict({
# './data/': 's3://openmmlab/datasets/detection/',
# 'data/': 's3://openmmlab/datasets/detection/'
# }))
backend_args = None
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(
type='LoadAnnotations',
with_bbox=False,
with_label=False,
with_seg=True),
dict(type='Resize', scale=(1333, 800), keep_ratio=True),
dict(type='RandomFlip', prob=0.5),
dict(type='PackDetInputs')
]
test_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='Resize', scale=(1333, 800), keep_ratio=True),
dict(
type='LoadAnnotations',
with_bbox=False,
with_label=False,
with_seg=True),
dict(
type='PackDetInputs',
meta_keys=('img_path', 'ori_shape', 'img_shape', 'scale_factor'))
]
# For stuffthingmaps_semseg, please refer to
# `docs/en/user_guides/dataset_prepare.md`
train_dataloader = dict(
batch_size=2,
num_workers=2,
persistent_workers=True,
sampler=dict(type='DefaultSampler', shuffle=True),
batch_sampler=dict(type='AspectRatioBatchSampler'),
dataset=dict(
type=dataset_type,
data_root=data_root,
data_prefix=dict(
img_path='train2017/',
seg_map_path='stuffthingmaps_semseg/train2017/'),
pipeline=train_pipeline))
val_dataloader = dict(
batch_size=1,
num_workers=2,
persistent_workers=True,
drop_last=False,
sampler=dict(type='DefaultSampler', shuffle=False),
dataset=dict(
type=dataset_type,
data_root=data_root,
data_prefix=dict(
img_path='val2017/',
seg_map_path='stuffthingmaps_semseg/val2017/'),
pipeline=test_pipeline))
test_dataloader = val_dataloader
val_evaluator = dict(type='SemSegMetric', iou_metrics=['mIoU'])
test_evaluator = val_evaluator
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