diff --git a/configs/_base_/datasets/kn_cityscapes.py b/configs/_base_/datasets/kn_cityscapes.py new file mode 100644 index 0000000..e15ad34 --- /dev/null +++ b/configs/_base_/datasets/kn_cityscapes.py @@ -0,0 +1,54 @@ +# dataset settings +dataset_type = 'CityscapesDataset' +data_root = 'data/cityscapes/' +img_norm_cfg = dict( + mean=[128., 128., 128.], std=[256., 256., 256.], to_rgb=True) +crop_size = (512, 1024) +train_pipeline = [ + dict(type='LoadImageFromFile'), + dict(type='LoadAnnotations'), + dict(type='Resize', img_scale=(2048, 1024), ratio_range=(0.5, 2.0)), + dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75), + dict(type='RandomFlip', prob=0.5), + dict(type='PhotoMetricDistortion'), + dict(type='Normalize', **img_norm_cfg), + dict(type='Pad', size=crop_size, pad_val=0, seg_pad_val=255), + dict(type='DefaultFormatBundle'), + dict(type='Collect', keys=['img', 'gt_semantic_seg']), +] +test_pipeline = [ + dict(type='LoadImageFromFile'), + dict( + type='MultiScaleFlipAug', + # img_scale=(2048, 1024), + img_scale=(1024, 512), + 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']), + ]) +] +data = dict( + samples_per_gpu=2, + workers_per_gpu=2, + train=dict( + type=dataset_type, + data_root=data_root, + img_dir='leftImg8bit/train', + ann_dir='gtFine/train', + pipeline=train_pipeline), + val=dict( + type=dataset_type, + data_root=data_root, + img_dir='leftImg8bit/val', + ann_dir='gtFine/val', + pipeline=test_pipeline), + test=dict( + type=dataset_type, + data_root=data_root, + img_dir='leftImg8bit/val', + ann_dir='gtFine/val', + pipeline=test_pipeline)) diff --git a/configs/stdc/kn_stdc1_in1k-pre_512x1024_80k_cityscapes.py b/configs/stdc/kn_stdc1_in1k-pre_512x1024_80k_cityscapes.py new file mode 100644 index 0000000..9d12e27 --- /dev/null +++ b/configs/stdc/kn_stdc1_in1k-pre_512x1024_80k_cityscapes.py @@ -0,0 +1,14 @@ +checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/stdc/stdc1_20220308-5368626c.pth' # noqa +_base_ = [ + '../_base_/models/stdc.py', '../_base_/datasets/kn_cityscapes.py', + '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' +] +lr_config = dict(warmup='linear', warmup_iters=1000) +data = dict( + samples_per_gpu=12, + workers_per_gpu=4, +) +model = dict( + backbone=dict( + backbone_cfg=dict( + init_cfg=dict(type='Pretrained', checkpoint=checkpoint))))