mirrors/mmsegmentation
1
0
Fork 0
mirror of https://github.com/open-mmlab/mmsegmentation.git synced 2025-06-03 22:03:48 +08:00
Code Issues Projects Releases Wiki Activity

[Fix] Fix Segmenter-l readme (#1695)

Browse Source 
* [Fix] Fix Segmenter-l readme

* fix
This commit is contained in:
FangjianLin 2022-06-24 16:37:39 +08:00 committed by GitHub
parent e8dfa3f26b
commit 733ad9ef6e
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 11 additions and 11 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
configs/segmenter/README.md
View File

@ -71,7 +71,7 @@ In our default setting, pretrained models and their corresponding [ViT-AugReg](h
| Segmenter Linear | ViT-S_16 | 512x512 | 160000 | 1.78 | 28.07 | 45.75 | 46.82 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/segmenter/segmenter_vit-s_linear_8x1_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-s_linear_8x1_512x512_160k_ade20k/segmenter_vit-s_linear_8x1_512x512_160k_ade20k_20220105_151713-39658c46.pth) \| [log](https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-s_linear_8x1_512x512_160k_ade20k/segmenter_vit-s_linear_8x1_512x512_160k_ade20k_20220105_151713.log.json) |
| Segmenter Mask | ViT-S_16 | 512x512 | 160000 | 2.03 | 24.80 | 46.19 | 47.85 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/segmenter/segmenter_vit-s_mask_8x1_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-s_mask_8x1_512x512_160k_ade20k/segmenter_vit-s_mask_8x1_512x512_160k_ade20k_20220105_151706-511bb103.pth) \| [log](https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-s_mask_8x1_512x512_160k_ade20k/segmenter_vit-s_mask_8x1_512x512_160k_ade20k_20220105_151706.log.json) |
| Segmenter Mask | ViT-B_16 | 512x512 | 160000 | 4.20 | 13.20 | 49.60 | 51.07 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/segmenter/segmenter_vit-b_mask_8x1_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-b_mask_8x1_512x512_160k_ade20k/segmenter_vit-b_mask_8x1_512x512_160k_ade20k_20220105_151706-bc533b08.pth) \| [log](https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-b_mask_8x1_512x512_160k_ade20k/segmenter_vit-b_mask_8x1_512x512_160k_ade20k_20220105_151706.log.json) |
| Segmenter Mask | ViT-L_16 | 640x640 | 160000 | 16.56 | 2.62 | 52.16 | 53.65 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/segmenter/segmenter_vit-l_mask_8x1_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-l_mask_8x1_512x512_160k_ade20k/segmenter_vit-l_mask_8x1_512x512_160k_ade20k_20220105_162750-7ef345be.pth) \| [log](https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-l_mask_8x1_512x512_160k_ade20k/segmenter_vit-l_mask_8x1_512x512_160k_ade20k_20220105_162750.log.json) |
| Segmenter Mask | ViT-L_16 | 640x640 | 160000 | 16.99 | 3.03 | 51.65 | 53.58 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/segmenter/segmenter_vit-l_mask_8x1_640x640_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-l_mask_8x1_640x640_160k_ade20k/segmenter_vit-l_mask_8x1_640x640_160k_ade20k_20220614_024513-4783a347.pth) \| [log](https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-l_mask_8x1_640x640_160k_ade20k/segmenter_vit-l_mask_8x1_640x640_160k_ade20k_20220614_024513.log.json) |
Note:

14
configs/segmenter/segmenter.yml
View File

@ -101,25 +101,25 @@ Models:
mIoU(ms+flip): 51.07
Config: configs/segmenter/segmenter_vit-b_mask_8x1_512x512_160k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-b_mask_8x1_512x512_160k_ade20k/segmenter_vit-b_mask_8x1_512x512_160k_ade20k_20220105_151706-bc533b08.pth
- Name: segmenter_vit-l_mask_8x1_512x512_160k_ade20k
- Name: segmenter_vit-l_mask_8x1_640x640_160k_ade20k
In Collection: Segmenter
Metadata:
backbone: ViT-L_16
crop size: (640,640)
lr schd: 160000
inference time (ms/im):
- value: 381.68
- value: 330.03
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (640,640)
Training Memory (GB): 16.56
Training Memory (GB): 16.99
Results:
- Task: Semantic Segmentation
Dataset: ADE20K
Metrics:
mIoU: 52.16
mIoU(ms+flip): 53.65
Config: configs/segmenter/segmenter_vit-l_mask_8x1_512x512_160k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-l_mask_8x1_512x512_160k_ade20k/segmenter_vit-l_mask_8x1_512x512_160k_ade20k_20220105_162750-7ef345be.pth
mIoU: 51.65
mIoU(ms+flip): 53.58
Config: configs/segmenter/segmenter_vit-l_mask_8x1_640x640_160k_ade20k.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-l_mask_8x1_640x640_160k_ade20k/segmenter_vit-l_mask_8x1_640x640_160k_ade20k_20220614_024513-4783a347.pth

6
configs/segmenter/segmenter_vit-l_mask_8x1_512x512_160k_ade20k.py → configs/segmenter/segmenter_vit-l_mask_8x1_640x640_160k_ade20k.py
View File

@ -1,6 +1,6 @@
_base_ = [
'../_base_/models/segmenter_vit-b16_mask.py',
'../_base_/datasets/ade20k.py', '../_base_/default_runtime.py',
'../_base_/datasets/ade20k_640x640.py', '../_base_/default_runtime.py',
'../_base_/schedules/schedule_160k.py'
]
checkpoint = 'https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/segmenter/vit_large_p16_384_20220308-d4efb41d.pth' # noqa
@ -29,7 +29,7 @@ crop_size = (640, 640)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', reduce_zero_label=True),
dict(type='Resize', img_scale=(2048, 640), ratio_range=(0.5, 2.0)),
dict(type='Resize', img_scale=(2560, 640), 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'),
@ -42,7 +42,7 @@ test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(2048, 640),
img_scale=(2560, 640),
# img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
flip=False,
transforms=[