From c06190713f89b8b8c2471ee5c566ff0a36dd1b01 Mon Sep 17 00:00:00 2001 From: MengzhangLI Date: Thu, 9 Dec 2021 15:01:14 +0800 Subject: [PATCH] fix ADE20K typo --- configs/mobilenet_v2/README.md | 2 +- configs/mobilenet_v2/mobilenet_v2.yml | 10 +++++----- configs/resnest/README.md | 2 +- configs/resnest/resnest.yml | 10 +++++----- configs/segformer/README.md | 2 +- configs/segformer/segformer.yml | 16 ++++++++-------- 6 files changed, 21 insertions(+), 21 deletions(-) diff --git a/configs/mobilenet_v2/README.md b/configs/mobilenet_v2/README.md index 89f4d76f91..8470b9254f 100644 --- a/configs/mobilenet_v2/README.md +++ b/configs/mobilenet_v2/README.md @@ -44,7 +44,7 @@ The MobileNetV2 architecture is based on an inverted residual structure where th | DeepLabV3 | M-V2-D8 | 512x1024 | 80000 | 3.9 | 8.4 | 73.84 | - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/mobilenet_v2/deeplabv3_m-v2-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3_m-v2-d8_512x1024_80k_cityscapes/deeplabv3_m-v2-d8_512x1024_80k_cityscapes_20200825_124836-bef03590.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3_m-v2-d8_512x1024_80k_cityscapes/deeplabv3_m-v2-d8_512x1024_80k_cityscapes-20200825_124836.log.json) | | DeepLabV3+ | M-V2-D8 | 512x1024 | 80000 | 5.1 | 8.4 | 75.20 | - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/mobilenet_v2/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes_20200825_124836-d256dd4b.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes-20200825_124836.log.json) | -### ADE20k +### ADE20K | Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download | | ---------- | -------- | --------- | ------: | -------: | -------------- | ----: | ------------- | ------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | diff --git a/configs/mobilenet_v2/mobilenet_v2.yml b/configs/mobilenet_v2/mobilenet_v2.yml index 57e0fe23f4..bb0ddd6d0d 100644 --- a/configs/mobilenet_v2/mobilenet_v2.yml +++ b/configs/mobilenet_v2/mobilenet_v2.yml @@ -3,7 +3,7 @@ Collections: Metadata: Training Data: - Cityscapes - - ADE20k + - ADE20K Paper: URL: https://arxiv.org/abs/1801.04381 Title: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks' @@ -114,7 +114,7 @@ Models: Training Memory (GB): 6.5 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 19.71 Config: configs/mobilenet_v2/fcn_m-v2-d8_512x512_160k_ade20k.py @@ -135,7 +135,7 @@ Models: Training Memory (GB): 6.5 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 29.68 Config: configs/mobilenet_v2/pspnet_m-v2-d8_512x512_160k_ade20k.py @@ -156,7 +156,7 @@ Models: Training Memory (GB): 6.8 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 34.08 Config: configs/mobilenet_v2/deeplabv3_m-v2-d8_512x512_160k_ade20k.py @@ -177,7 +177,7 @@ Models: Training Memory (GB): 8.2 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 34.02 Config: configs/mobilenet_v2/deeplabv3plus_m-v2-d8_512x512_160k_ade20k.py diff --git a/configs/resnest/README.md b/configs/resnest/README.md index 085cb4f22b..9e93a2d22d 100644 --- a/configs/resnest/README.md +++ b/configs/resnest/README.md @@ -42,7 +42,7 @@ year={2020} | DeepLabV3 | S-101-D8 | 512x1024 | 80000 | 11.9 | 1.88 | 79.67 | 80.51 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/resnest/deeplabv3_s101-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3_s101-d8_512x1024_80k_cityscapes/deeplabv3_s101-d8_512x1024_80k_cityscapes_20200807_144429-b73c4270.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3_s101-d8_512x1024_80k_cityscapes/deeplabv3_s101-d8_512x1024_80k_cityscapes-20200807_144429.log.json) | | DeepLabV3+ | S-101-D8 | 512x1024 | 80000 | 13.2 | 2.36 | 79.62 | 80.27 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/resnest/deeplabv3plus_s101-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3plus_s101-d8_512x1024_80k_cityscapes/deeplabv3plus_s101-d8_512x1024_80k_cityscapes_20200807_144429-1239eb43.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/resnest/deeplabv3plus_s101-d8_512x1024_80k_cityscapes/deeplabv3plus_s101-d8_512x1024_80k_cityscapes-20200807_144429.log.json) | -### ADE20k +### ADE20K | Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download | | ---------- | -------- | --------- | ------: | -------: | -------------- | ----: | ------------- | ------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | diff --git a/configs/resnest/resnest.yml b/configs/resnest/resnest.yml index 6a4fc5a45e..cd92409471 100644 --- a/configs/resnest/resnest.yml +++ b/configs/resnest/resnest.yml @@ -3,7 +3,7 @@ Collections: Metadata: Training Data: - Cityscapes - - ADE20k + - ADE20K Paper: URL: https://arxiv.org/abs/2004.08955 Title: 'ResNeSt: Split-Attention Networks' @@ -118,7 +118,7 @@ Models: Training Memory (GB): 14.2 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 45.62 mIoU(ms+flip): 46.16 @@ -140,7 +140,7 @@ Models: Training Memory (GB): 14.2 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 45.44 mIoU(ms+flip): 46.28 @@ -162,7 +162,7 @@ Models: Training Memory (GB): 14.6 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 45.71 mIoU(ms+flip): 46.59 @@ -184,7 +184,7 @@ Models: Training Memory (GB): 16.2 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 46.47 mIoU(ms+flip): 47.27 diff --git a/configs/segformer/README.md b/configs/segformer/README.md index 895f115708..e82be55a88 100644 --- a/configs/segformer/README.md +++ b/configs/segformer/README.md @@ -45,7 +45,7 @@ This script convert model from `PRETRAIN_PATH` and store the converted model in ## Results and models -### ADE20k +### ADE20K | Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download | | ------ | -------- | --------- | ------: | -------: | -------------- | ---: | ------------- | ------ | -------- | diff --git a/configs/segformer/segformer.yml b/configs/segformer/segformer.yml index d60db0065c..df46d5260c 100644 --- a/configs/segformer/segformer.yml +++ b/configs/segformer/segformer.yml @@ -2,7 +2,7 @@ Collections: - Name: segformer Metadata: Training Data: - - ADE20k + - ADE20K Paper: URL: https://arxiv.org/abs/2105.15203 Title: resize image to multiple of 32, improve SegFormer by 0.5-1.0 mIoU. @@ -29,7 +29,7 @@ Models: Training Memory (GB): 2.1 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 37.41 mIoU(ms+flip): 38.34 @@ -51,7 +51,7 @@ Models: Training Memory (GB): 2.6 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 40.97 mIoU(ms+flip): 42.54 @@ -73,7 +73,7 @@ Models: Training Memory (GB): 3.6 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 45.58 mIoU(ms+flip): 47.03 @@ -95,7 +95,7 @@ Models: Training Memory (GB): 4.8 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 47.82 mIoU(ms+flip): 48.81 @@ -117,7 +117,7 @@ Models: Training Memory (GB): 6.1 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 48.46 mIoU(ms+flip): 49.76 @@ -139,7 +139,7 @@ Models: Training Memory (GB): 7.2 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 49.13 mIoU(ms+flip): 50.22 @@ -161,7 +161,7 @@ Models: Training Memory (GB): 11.5 Results: - Task: Semantic Segmentation - Dataset: ADE20k + Dataset: ADE20K Metrics: mIoU: 49.62 mIoU(ms+flip): 50.36