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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 | |