add configs for vit backbone plus decode_heads by xiexinch · Pull Request #520 · open-mmlab/mmsegmentation

xiexinch · 2021-04-26T06:17:56Z

No description provided.

…into vit_plus_heads

codecov · 2021-04-26T06:58:01Z

Codecov Report

Merging #520 (8db5cdd) into master (98067be) will increase coverage by 0.05%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master     #520      +/-   ##
==========================================
+ Coverage   85.77%   85.83%   +0.05%     
==========================================
  Files         103      103              
  Lines        5307     5308       +1     
  Branches      857      858       +1     
==========================================
+ Hits         4552     4556       +4     
+ Misses        583      581       -2     
+ Partials      172      171       -1

Flag	Coverage Δ
unittests	`85.81% <100.00%> (+0.04%)`	⬆️

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Impacted Files	Coverage Δ
mmseg/models/necks/multilevel_neck.py	`100.00% <100.00%> (ø)`
mmseg/datasets/builder.py	`89.33% <0.00%> (+3.43%)`	⬆️

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xvjiarui · 2021-04-26T16:57:16Z

configs/_base_/models/upernet_vit-d16.py

+        norm_cfg=dict(type='LN'),
+        act_cfg=dict(type='GELU'),
+        norm_eval=False),
+    neck=dict(type='MultiLevelNeck', in_channels=[768], out_channels=768),


We may use [0.5, 1, 2, 4] scale.

xvjiarui · 2021-04-26T21:43:44Z

configs/_base_/models/deeplabv3_vit-d16.py

+    pretrained='https://github.com/rwightman/pytorch-image-models/releases/\
+download/v0.1-vitjx/jx_vit_base_p16_224-80ecf9dd.pth',


We may also add deit-s and deit-b

xvjiarui · 2021-04-27T05:56:28Z

configs/_base_/models/upernet_vit-d16.py

@@ -0,0 +1,54 @@
+# model settings


The config needs to be renamed.

xvjiarui · 2021-04-29T06:33:26Z

configs/_base_/models/deeplabv3_vit-d16.py

+        qk_scale=None,
+        drop_rate=0.0,
+        attn_drop_rate=0.0,
+        norm_cfg=dict(type='LN'),


In #524，eps=1e-6.

xvjiarui · 2021-04-30T07:46:08Z

configs/vit/upernet_deitS-d16-512x512_80k_ade20k.py

+            'absolute_pos_embed': dict(decay_mult=0.),
+            'relative_position_bias_table': dict(decay_mult=0.),


These keys are not in the ViT. They should be pos_embed and cls_token.

xvjiarui · 2021-04-30T07:46:58Z

configs/vit/upernet_deitS-d16-512x512_80k_ade20k.py

+# By default, models are trained on 8 GPUs with 2 images per GPU
+data = dict(samples_per_gpu=2)
+
+find_unused_parameters = True


We may remove these since it will slow down the training and make bugs hard to be found.

…into vit_plus_heads

xvjiarui · 2021-05-06T04:05:27Z

configs/vit/README.md

+
+| Method  | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) |  mIoU | mIoU(ms+flip) | config                                                                                                                     | download                                                                                                                                                                                                                                                                                                                                               |
+| ------- | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | -------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| UPerNet | Vit     | 512x1024  |   40000 |       |           | |          | |


xvjiarui · 2021-05-06T04:05:35Z

configs/vit/README.md

+| Method  | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) |  mIoU | mIoU(ms+flip) | config                                                                                                                     | download                                                                                                                                                                                                                                                                                                                                               |
+| ------- | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | -------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| UPerNet | Vit     | 512x1024  |   40000 |       |           | |          | |
+| UPerNet | Deit-S  | 512x1024  |   40000 |       |           | |          | |


xvjiarui · 2021-05-12T02:36:40Z

configs/vit/README.md

+| UPerNet | Vit     | 512x512  |   80000 |       |           | |          | |
+| UPerNet | Deit-S  | 512x512  |   80000 |       |           | |          | |
+| UPerNet | Deit-B  | 512x512  |   80000 |       |           | |          | |


We may also add 160k.

xvjiarui · 2021-05-12T02:38:43Z

configs/_base_/models/fcn_vit-d16.py

+    pretrained='https://github.com/rwightman/pytorch-image-models/releases/\
+download/v0.1-vitjx/jx_vit_base_p16_224-80ecf9dd.pth',


We may use # noqa to bypass the line breaking.

xvjiarui · 2021-05-18T06:07:48Z

configs/_base_/models/deeplabv3_vit-d16.py

@@ -0,0 +1,55 @@
+# model settings


Rename to ***_vit-b16.py

xvjiarui · 2021-05-18T06:08:30Z

configs/vit/deeplabv3_deitB-d16-512x1024_40k_cityscapes.py

@@ -0,0 +1,36 @@
+_base_ = [


Rename to ***_deit-b16.py

xvjiarui · 2021-05-18T06:08:43Z

configs/vit/deeplabv3_deitB-d16-512x512_80k_ade20k.py

+]
+
+model = dict(
+    pretrained='https://dl.fbaipublicfiles.com/deit/\


…tation into vit_plus_heads

xvjiarui · 2021-06-21T03:27:23Z

Are results updated?

xiexinch · 2021-06-21T03:37:10Z

Are results updated?

Not yet, these configs are not correct for the latest vit, I need some time to modify them and test the checkpoints.
I will update soo...

…into vit_plus_heads

Junjun2016 · 2021-06-28T13:05:05Z

configs/_base_/models/upernet_vit-b16.py

@@ -0,0 +1,58 @@
+# model settings


Rename the config.
There is MultiLevelNeck (MLN) in this config.

Junjun2016 · 2021-06-28T13:29:22Z

mmseg/models/necks/multilevel_neck.py

+        for m in self.modules():
+            if isinstance(m, nn.Conv2d):
+                xavier_init(m, distribution='uniform')
+


Why use xavier_init for Conv2d?
kaiming_init for ConvModule is used in MMCV.

Followed FPN

Junjun2016 · 2021-06-28T14:29:33Z

configs/vit/upernet_vit-b16_neck_512x512_80k_ade20k.py

+
+model = dict(
+    decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
+


drop_path_rate?

ViT doesn't use drop path.

Junjun2016 · 2021-06-28T14:29:49Z

configs/vit/upernet_vit-b16_neck_512x512_160k_ade20k.py

+
+model = dict(
+    decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
+


drop_path_rate?

ViT doesn't use drop path.

configs/vit/upernet_deit-s16_neck_512x512_160k_ade20k.py

Junjun2016 · 2021-06-28T14:33:27Z

configs/vit/upernet_deit-s16_neck_ln-backbone_512x512_160k_ade20k.py

+
+model = dict(
+    pretrained='https://dl.fbaipublicfiles.com/deit/deit_small_patch16_224-cd65a155.pth',  # noqa
+    backbone=dict(num_heads=6, embed_dims=384, drop_path_rate=0.1, final_norm=True), # noqa


Is the # noqa necessary?

xvjiarui · 2021-06-28T14:43:02Z

configs/vit/upernet_deit-s16_neck_ln-backbone_512x512_160k_ade20k.py

+
+model = dict(
+    pretrained='https://dl.fbaipublicfiles.com/deit/deit_small_patch16_224-cd65a155.pth',  # noqa
+    backbone=dict(num_heads=6, embed_dims=384, drop_path_rate=0.1, final_norm=True), # noqa


Suggested change

backbone=dict(num_heads=6, embed_dims=384, drop_path_rate=0.1, final_norm=True), # noqa

backbone=dict(num_heads=6, embed_dims=384, drop_path_rate=0.1, final_norm=True),

xvjiarui · 2021-06-28T14:56:51Z

configs/vit/README.md

+| ------- | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | ---------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| UPerNet | ViT-B + neck  | 512x512  | 80000  | 9.20 | 6.94  | 47.71 | 49.51 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_vit-b16_neck_512x512_80k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_neck_512x512_80k_ade20k-0403cee1.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/20210624_130547.log.json) |
+| UPerNet | ViT-B + neck  | 512x512  | 160000 | 9.20 | 7.58  | 46.75 | 48.46 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_vit-b16_neck_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_neck_512x512_160k_ade20k-852fa768.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/20210623_192432.log.json) |
+| UPerNet | ViT-B + norm  | 512x512  | 160000 | 9.21 | 6.82  | 47.73 | 49.95 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_vit-b16_neck_ln-backbone_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_neck_ln-backbone_512x512_160k_ade20k-f444c077.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/20210621_172828.log.json) |


Suggested change

| UPerNet | ViT-B + norm | 512x512 | 160000 | 9.21 | 6.82 | 47.73 | 49.95 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_vit-b16_neck_ln-backbone_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_neck_ln-backbone_512x512_160k_ade20k-f444c077.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/20210621_172828.log.json) |

| UPerNet | ViT-B + LN +MLN | 512x512 | 160000 | 9.21 | 6.82 | 47.73 | 49.95 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_neck_ln-backbone_512x512_160k_ade20k-f444c077.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/20210621_172828.log.json) |

xvjiarui · 2021-07-01T05:35:34Z

configs/vit/README.md

+
+| Method  | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) |  mIoU | mIoU(ms+flip) | config                                                                                                                 | download                                                                                                                                                                                                                                                                                                                               |
+| ------- | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | ---------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| UPerNet | ViT-B + neck  | 512x512  | 80000  | 9.20 | 6.94  | 47.71 | 49.51 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_vit-b16_neck_512x512_80k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_neck_512x512_80k_ade20k/upernet_vit-b16_neck_512x512_80k_ade20k-0403cee1.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_neck_512x512_80k_ade20k/20210624_130547.log.json) |


Suggested change

| UPerNet | ViT-B + neck | 512x512 | 80000 | 9.20 | 6.94 | 47.71 | 49.51 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_vit-b16_neck_512x512_80k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_neck_512x512_80k_ade20k/upernet_vit-b16_neck_512x512_80k_ade20k-0403cee1.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_neck_512x512_80k_ade20k/20210624_130547.log.json) |

| UPerNet | ViT-B + MLN | 512x512 | 80000 | 9.20 | 6.94 | 47.71 | 49.51 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_vit-b16_neck_512x512_80k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_neck_512x512_80k_ade20k/upernet_vit-b16_neck_512x512_80k_ade20k-0403cee1.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_neck_512x512_80k_ade20k/20210624_130547.log.json) |

xvjiarui · 2021-07-01T05:36:17Z

configs/vit/README.md

+| UPerNet | ViT-B +  LN +MLN  | 512x512  | 160000 | 9.21 | 6.82  | 47.73 | 49.95 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k/upernet_vit-b16_ln_mln_512x512_160k_ade20k-f444c077.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k/20210621_172828.log.json) |
+| UPerNet | DeiT-S        | 512x512  | 80000  | 4.68 | 29.85 | 42.96 | 43.79 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_deit-s16_512x512_80k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_deit-s16_512x512_80k_ade20k/upernet_deit-s16_512x512_80k_ade20k-afc93ec2.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_deit-s16_512x512_80k_ade20k/20210624_095228.log.json) |
+| UPerNet | DeiT-S        | 512x512  | 160000 | 4.68 | 29.19 | 42.87 | 43.79 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_deit-s16_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_deit-s16_512x512_160k_ade20k/upernet_deit-s16_512x512_160k_ade20k-5110d916.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_deit-s16_512x512_160k_ade20k/20210621_160903.log.json) |
+| UPerNet | DeiT-S + neck | 512x512  | 160000 | 5.69 | 11.18 | 43.82 | 45.07 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_deit-s16_neck_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_deit-s16_neck_512x512_160k_ade20k/upernet_deit-s16_neck_512x512_160k_ade20k-fb9a5dfb.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_deit-s16_neck_512x512_160k_ade20k/20210621_161021.log.json) |


Suggested change

| UPerNet | DeiT-S + neck | 512x512 | 160000 | 5.69 | 11.18 | 43.82 | 45.07 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_deit-s16_neck_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_deit-s16_neck_512x512_160k_ade20k/upernet_deit-s16_neck_512x512_160k_ade20k-fb9a5dfb.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_deit-s16_neck_512x512_160k_ade20k/20210621_161021.log.json) |

| UPerNet | DeiT-S + MLN | 512x512 | 160000 | 5.69 | 11.18 | 43.82 | 45.07 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/vit/upernet_deit-s16_neck_512x512_160k_ade20k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_deit-s16_neck_512x512_160k_ade20k/upernet_deit-s16_neck_512x512_160k_ade20k-fb9a5dfb.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/vit/upernet_deit-s16_neck_512x512_160k_ade20k/20210621_161021.log.json) |

xvjiarui · 2021-07-01T05:36:39Z

configs/vit/upernet_deit-b16_512x512_160k_ade20k.py

@@ -0,0 +1,6 @@
+_base_ = './upernet_vit-b16_neck_512x512_160k_ade20k.py'


Suggested change

_base_ = './upernet_vit-b16_neck_512x512_160k_ade20k.py'

_base_ = './upernet_vit-b16_mln_512x512_160k_ade20k.py'

* add config * add cityscapes config * add default value to docstring * fix lint * add deit-s and deit-b * add readme * add eps at norm_cfg * add drop_path_rate experiment * add deit case at init_weight * add upernet result * update result and add upernet 160k config * update upernet result and fix settings * Update iters number * update result and delete some configs * fix import error * fix drop_path_rate * update result and restore config * update benchmark result * remove cityscapes exp * remove neck * neck exp * add more configs * fix init error * fix ffn setting * update result * update results * update result * update results and fill table * delete or rename configs * fix link delimiter * rename configs and fix link * rename neck to mln

fix typo

xiexinch added 4 commits April 26, 2021 12:05

add config

1c66609

add cityscapes config

a439a40

add default value to docstring

b7aa7ee

Merge branch 'master' of https://github.com/open-mmlab/mmsegmentation …

4e8383c

…into vit_plus_heads

fix lint

e7d6243

xvjiarui reviewed Apr 26, 2021

View reviewed changes

add deit-s and deit-b

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xvjiarui reviewed Apr 27, 2021

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configs/_base_/models/upernet_vit-d16.py

@@ -0,0 +1,54 @@

# model settings

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xvjiarui Apr 27, 2021

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The config needs to be renamed.

add readme

6b40465

xvjiarui reviewed Apr 29, 2021

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add eps at norm_cfg

6d0ab21

xvjiarui reviewed Apr 30, 2021

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xiexinch added 4 commits May 6, 2021 10:27

Merge branch 'master' of https://github.com/open-mmlab/mmsegmentation …

c9c6596

…into vit_plus_heads

add drop_path_rate experiment

f7b8c18

add deit case at init_weight

d605af6

add upernet result

425cac7

xvjiarui reviewed May 12, 2021

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xiexinch added 3 commits May 12, 2021 12:53

update result and add upernet 160k config

dd6856e

update upernet result and fix settings

bd86b64

Update iters number

3f8db05

xvjiarui reviewed May 18, 2021

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clownrat6 mentioned this pull request May 18, 2021

How can I use ViT? #525

Closed

xiexinch added 4 commits May 18, 2021 15:20

update result and delete some configs

4d77761

fix import error

656c167

fix drop_path_rate

7d13836

update result and restore config

8931d7f

Merge branch 'vit_plus_heads' of https://github.com/xiexinch/mmsegmen…

e7a6637

…tation into vit_plus_heads

xiexinch added 9 commits June 21, 2021 15:03

fix init error

319f56e

fix ffn setting

c4aa7b6

update result

8457e67

update results

b0f9e29

update result

74424aa

update results and fill table

8c11f62

Merge branch 'master' of https://github.com/open-mmlab/mmsegmentation …

637356d

…into vit_plus_heads

delete or rename configs

31ba78d

fix link delimiter

53ae35c

Junjun2016 self-requested a review June 28, 2021 09:42

Junjun2016 reviewed Jun 28, 2021

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configs/vit/upernet_deit-s16_neck_512x512_160k_ade20k.py Outdated Show resolved Hide resolved

Junjun2016 reviewed Jun 28, 2021

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xvjiarui reviewed Jun 28, 2021

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rename configs and fix link

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xvjiarui reviewed Jul 1, 2021

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rename neck to mln

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Junjun2016 approved these changes Jul 1, 2021

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Junjun2016 merged commit 737544f into open-mmlab:master Jul 1, 2021

michaelzhang-ai pushed a commit to michaelzhang-ai/mmsegmentation that referenced this pull request Mar 22, 2024

Update README.md (open-mmlab#520)

b769492

fix typo

		pretrained='https://github.com/rwightman/pytorch-image-models/releases/\
		download/v0.1-vitjx/jx_vit_base_p16_224-80ecf9dd.pth',

		'absolute_pos_embed': dict(decay_mult=0.),
		'relative_position_bias_table': dict(decay_mult=0.),


		model = dict(
		decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))

	backbone=dict(num_heads=6, embed_dims=384, drop_path_rate=0.1, final_norm=True), # noqa
	backbone=dict(num_heads=6, embed_dims=384, drop_path_rate=0.1, final_norm=True),

		@@ -0,0 +1,6 @@
		_base_ = './upernet_vit-b16_neck_512x512_160k_ade20k.py'

	_base_ = './upernet_vit-b16_neck_512x512_160k_ade20k.py'
	_base_ = './upernet_vit-b16_mln_512x512_160k_ade20k.py'

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xvjiarui commented Jun 21, 2021

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codecov bot commented Apr 26, 2021 •

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