From 008856a84c7f952ccb94fa85da2f27a999a20d8d Mon Sep 17 00:00:00 2001 From: MengzhangLI Date: Mon, 15 Nov 2021 19:14:57 +0800 Subject: [PATCH] [Fix] Remove `fp16` folder in `configs`. (#1031) * remove fp16 folder * remove fp16 in docs * fix some typos * fix some typos * fix fp16 in yml --- .dev/batch_test_list.py | 4 +- .dev/batch_train_list.txt | 2 +- .dev/benchmark_evaluation.sh | 4 +- .dev/benchmark_train.sh | 4 +- .dev/md2yml.py | 2 +- README.md | 1 - README_zh-CN.md | 1 - configs/bisenetv2/bisenetv2.yml | 2 +- configs/deeplabv3/README.md | 5 + configs/deeplabv3/deeplabv3.yml | 21 ++++ ...3_r101-d8_fp16_512x1024_80k_cityscapes.py} | 2 +- configs/deeplabv3plus/README.md | 5 + configs/deeplabv3plus/deeplabv3plus.yml | 21 ++++ ...s_r101-d8_fp16_512x1024_80k_cityscapes.py} | 2 +- configs/fcn/README.md | 5 + configs/fcn/fcn.yml | 21 ++++ ...n_r101-d8_fp16_512x1024_80k_cityscapes.py} | 2 +- configs/fp16/README.md | 34 ------- configs/fp16/fp16.yml | 99 ------------------- configs/pspnet/README.md | 5 + configs/pspnet/pspnet.yml | 21 ++++ ...t_r101-d8_fp16_512x1024_80k_cityscapes.py} | 2 +- docs/model_zoo.md | 2 +- docs_zh-CN/model_zoo.md | 2 +- model-index.yml | 1 - 25 files changed, 119 insertions(+), 151 deletions(-) rename configs/{fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py => deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py} (64%) rename configs/{fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py => deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py} (62%) rename configs/{fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py => fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py} (67%) delete mode 100644 configs/fp16/README.md delete mode 100644 configs/fp16/fp16.yml rename configs/{fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py => pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py} (60%) diff --git a/.dev/batch_test_list.py b/.dev/batch_test_list.py index 690615058..c4fd8f97e 100644 --- a/.dev/batch_test_list.py +++ b/.dev/batch_test_list.py @@ -116,8 +116,8 @@ vit = [ ] fp16 = [ dict( - config='configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py', # noqa - checkpoint='deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes-cc58bc8d.pth', # noqa + config='configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py', # noqa + checkpoint='deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-f1104f4b.pth', # noqa eval='mIoU', metric=dict(mIoU=80.46), ) diff --git a/.dev/batch_train_list.txt b/.dev/batch_train_list.txt index 3f406a5f4..17d19932e 100644 --- a/.dev/batch_train_list.txt +++ b/.dev/batch_train_list.txt @@ -15,5 +15,5 @@ configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes.py configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py configs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k.py -configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py +configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py diff --git a/.dev/benchmark_evaluation.sh b/.dev/benchmark_evaluation.sh index b4901fe99..687e6cc3e 100755 --- a/.dev/benchmark_evaluation.sh +++ b/.dev/benchmark_evaluation.sh @@ -35,7 +35,7 @@ echo 'configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py' & GPUS=4 GPUS_PER_NODE=4 CPUS_PER_TASK=2 tools/slurm_test.sh $PARTITION upernet_vit-b16_ln_mln_512x512_160k_ade20k configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py $CHECKPOINT_DIR/upernet_vit-b16_ln_mln_512x512_160k_ade20k-f444c077.pth --eval mIoU --work-dir work_dirs/benchmark_evaluation/upernet_vit-b16_ln_mln_512x512_160k_ade20k --options dist_params.port=28186 & echo 'configs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k.py' & GPUS=4 GPUS_PER_NODE=4 CPUS_PER_TASK=2 tools/slurm_test.sh $PARTITION upernet_deit-s16_ln_mln_512x512_160k_ade20k configs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k.py $CHECKPOINT_DIR/upernet_deit-s16_ln_mln_512x512_160k_ade20k-c0cd652f.pth --eval mIoU --work-dir work_dirs/benchmark_evaluation/upernet_deit-s16_ln_mln_512x512_160k_ade20k --options dist_params.port=28187 & -echo 'configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py' & -GPUS=4 GPUS_PER_NODE=4 CPUS_PER_TASK=2 tools/slurm_test.sh $PARTITION deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py $CHECKPOINT_DIR/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes-cc58bc8d.pth --eval mIoU --work-dir work_dirs/benchmark_evaluation/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes --options dist_params.port=28188 & +echo 'configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py' & +GPUS=4 GPUS_PER_NODE=4 CPUS_PER_TASK=2 tools/slurm_test.sh $PARTITION deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py $CHECKPOINT_DIR/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes-cc58bc8d.pth --eval mIoU --work-dir work_dirs/benchmark_evaluation/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes --options dist_params.port=28188 & echo 'configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py' & GPUS=4 GPUS_PER_NODE=4 CPUS_PER_TASK=2 tools/slurm_test.sh $PARTITION upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py $CHECKPOINT_DIR/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K_20210531_112542-e380ad3e.pth --eval mIoU --work-dir work_dirs/benchmark_evaluation/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K --options dist_params.port=28189 & diff --git a/.dev/benchmark_train.sh b/.dev/benchmark_train.sh index d3db89776..048bb526b 100755 --- a/.dev/benchmark_train.sh +++ b/.dev/benchmark_train.sh @@ -34,7 +34,7 @@ echo 'configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py' & GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=2 ./tools/slurm_train.sh $PARTITION upernet_vit-b16_ln_mln_512x512_160k_ade20k configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py --options checkpoint_config.max_keep_ckpts=1 dist_params.port=24742 --work-dir work_dirs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k >/dev/null & echo 'configs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k.py' & GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=2 ./tools/slurm_train.sh $PARTITION upernet_deit-s16_ln_mln_512x512_160k_ade20k configs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k.py --options checkpoint_config.max_keep_ckpts=1 dist_params.port=24743 --work-dir work_dirs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k >/dev/null & -echo 'configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py' & -GPUS=4 GPUS_PER_NODE=4 CPUS_PER_TASK=2 ./tools/slurm_train.sh $PARTITION deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py --options checkpoint_config.max_keep_ckpts=1 dist_params.port=24744 --work-dir work_dirs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes >/dev/null & +echo 'configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py' & +GPUS=4 GPUS_PER_NODE=4 CPUS_PER_TASK=2 ./tools/slurm_train.sh $PARTITION deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py --options checkpoint_config.max_keep_ckpts=1 dist_params.port=24744 --work-dir work_dirs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes >/dev/null & echo 'configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py' & GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=2 ./tools/slurm_train.sh $PARTITION upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py --options checkpoint_config.max_keep_ckpts=1 dist_params.port=24745 --work-dir work_dirs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K >/dev/null & diff --git a/.dev/md2yml.py b/.dev/md2yml.py index 82368df9d..6bb1349d6 100755 --- a/.dev/md2yml.py +++ b/.dev/md2yml.py @@ -201,7 +201,7 @@ def parse_md(md_file): 'batch size': 1, 'mode': - 'FP32', + 'FP32' if 'fp16' not in config else 'FP16', 'resolution': f'({crop_size[0]},{crop_size[1]})' }] diff --git a/README.md b/README.md index c8d9027f9..18317e01e 100644 --- a/README.md +++ b/README.md @@ -73,7 +73,6 @@ Supported methods: - [x] [UNet (MICCAI'2016/Nat. Methods'2019)](configs/unet) - [x] [PSPNet (CVPR'2017)](configs/pspnet) - [x] [DeepLabV3 (ArXiv'2017)](configs/deeplabv3) -- [x] [Mixed Precision (FP16) Training (ArXiv'2017)](configs/fp16) - [x] [BiSeNetV1 (ECCV'2018)](configs/bisenetv1) - [x] [PSANet (ECCV'2018)](configs/psanet) - [x] [DeepLabV3+ (CVPR'2018)](configs/deeplabv3plus) diff --git a/README_zh-CN.md b/README_zh-CN.md index 563233f3d..d7cf65ce6 100644 --- a/README_zh-CN.md +++ b/README_zh-CN.md @@ -72,7 +72,6 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O - [x] [UNet (MICCAI'2016/Nat. Methods'2019)](configs/unet) - [x] [PSPNet (CVPR'2017)](configs/pspnet) - [x] [DeepLabV3 (ArXiv'2017)](configs/deeplabv3) -- [x] [Mixed Precision (FP16) Training (ArXiv'2017)](configs/fp16) - [x] [BiSeNetV1 (ECCV'2018)](configs/bisenetv1) - [x] [PSANet (ECCV'2018)](configs/psanet) - [x] [DeepLabV3+ (CVPR'2018)](configs/deeplabv3plus) diff --git a/configs/bisenetv2/bisenetv2.yml b/configs/bisenetv2/bisenetv2.yml index 373edb99c..d9e11be67 100644 --- a/configs/bisenetv2/bisenetv2.yml +++ b/configs/bisenetv2/bisenetv2.yml @@ -75,7 +75,7 @@ Models: hardware: V100 backend: PyTorch batch size: 1 - mode: FP32 + mode: FP16 resolution: (1024,1024) memory (GB): 5.77 Results: diff --git a/configs/deeplabv3/README.md b/configs/deeplabv3/README.md index 28bdbb906..655efd763 100644 --- a/configs/deeplabv3/README.md +++ b/configs/deeplabv3/README.md @@ -39,6 +39,7 @@ | DeepLabV3 | R-18-D8 | 512x1024 | 80000 | 1.7 | 13.78 | 76.70 | 78.27 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r18-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_512x1024_80k_cityscapes/deeplabv3_r18-d8_512x1024_80k_cityscapes_20201225_021506-23dffbe2.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_512x1024_80k_cityscapes/deeplabv3_r18-d8_512x1024_80k_cityscapes-20201225_021506.log.json) | | DeepLabV3 | R-50-D8 | 512x1024 | 80000 | - | - | 79.32 | 80.57 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r50-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x1024_80k_cityscapes/deeplabv3_r50-d8_512x1024_80k_cityscapes_20200606_113404-b92cfdd4.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x1024_80k_cityscapes/deeplabv3_r50-d8_512x1024_80k_cityscapes_20200606_113404.log.json) | | DeepLabV3 | R-101-D8 | 512x1024 | 80000 | - | - | 80.20 | 81.21 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes/deeplabv3_r101-d8_512x1024_80k_cityscapes_20200606_113503-9e428899.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes/deeplabv3_r101-d8_512x1024_80k_cityscapes_20200606_113503.log.json) | +| DeepLabV3 (FP16) | R-101-D8 | 512x1024 | 80000 | 5.75 | 3.86 | 80.48 | - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-774d9cec.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920.log.json) | | DeepLabV3 | R-18-D8 | 769x769 | 80000 | 1.9 | 5.55 | 76.60 | 78.26 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r18-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_769x769_80k_cityscapes/deeplabv3_r18-d8_769x769_80k_cityscapes_20201225_021506-6452126a.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_769x769_80k_cityscapes/deeplabv3_r18-d8_769x769_80k_cityscapes-20201225_021506.log.json) | | DeepLabV3 | R-50-D8 | 769x769 | 80000 | - | - | 79.89 | 81.06 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r50-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_769x769_80k_cityscapes/deeplabv3_r50-d8_769x769_80k_cityscapes_20200606_221338-788d6228.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_769x769_80k_cityscapes/deeplabv3_r50-d8_769x769_80k_cityscapes_20200606_221338.log.json) | | DeepLabV3 | R-101-D8 | 769x769 | 80000 | - | - | 79.67 | 80.81 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r101-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_769x769_80k_cityscapes/deeplabv3_r101-d8_769x769_80k_cityscapes_20200607_013353-60e95418.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_769x769_80k_cityscapes/deeplabv3_r101-d8_769x769_80k_cityscapes_20200607_013353.log.json) | @@ -102,3 +103,7 @@ | DeepLabV3 | R-101-D8 | 512x512 | 160000 | - | - | 41.82 | 42.49 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k_20210709_155402-f035acfd.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k_20210709_155402.log.json) | | DeepLabV3 | R-50-D8 | 512x512 | 320000 | - | - | 41.37 | 42.22 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k_20210709_155403-51b21115.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k_20210709_155403.log.json) | | DeepLabV3 | R-101-D8 | 512x512 | 320000 | - | - | 42.61 | 43.42 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k_20210709_155402-3cbca14d.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k_20210709_155402.log.json) | + +Note: + +- `FP16` means Mixed Precision (FP16) is adopted in training. diff --git a/configs/deeplabv3/deeplabv3.yml b/configs/deeplabv3/deeplabv3.yml index 94acb5958..cd5c8d0cd 100644 --- a/configs/deeplabv3/deeplabv3.yml +++ b/configs/deeplabv3/deeplabv3.yml @@ -157,6 +157,27 @@ Models: mIoU(ms+flip): 81.21 Config: configs/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes/deeplabv3_r101-d8_512x1024_80k_cityscapes_20200606_113503-9e428899.pth +- Name: deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes + In Collection: deeplabv3 + Metadata: + backbone: R-101-D8 + crop size: (512,1024) + lr schd: 80000 + inference time (ms/im): + - value: 259.07 + hardware: V100 + backend: PyTorch + batch size: 1 + mode: FP16 + resolution: (512,1024) + memory (GB): 5.75 + Results: + - Task: Semantic Segmentation + Dataset: Cityscapes + Metrics: + mIoU: 80.48 + Config: configs/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py + Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-774d9cec.pth - Name: deeplabv3_r18-d8_769x769_80k_cityscapes In Collection: deeplabv3 Metadata: diff --git a/configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py b/configs/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py similarity index 64% rename from configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py rename to configs/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py index cb2c27e44..e32610966 100644 --- a/configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py +++ b/configs/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py @@ -1,4 +1,4 @@ -_base_ = '../pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py' +_base_ = './deeplabv3_r101-d8_512x1024_80k_cityscapes.py' # fp16 settings optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) # fp16 placeholder diff --git a/configs/deeplabv3plus/README.md b/configs/deeplabv3plus/README.md index bf6c5d50a..c3e434091 100644 --- a/configs/deeplabv3plus/README.md +++ b/configs/deeplabv3plus/README.md @@ -40,6 +40,7 @@ | DeepLabV3+ | R-18-D8 | 512x1024 | 80000 | 2.2 | 14.27 | 76.89 | 78.76 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r18-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_512x1024_80k_cityscapes/deeplabv3plus_r18-d8_512x1024_80k_cityscapes_20201226_080942-cff257fe.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_512x1024_80k_cityscapes/deeplabv3plus_r18-d8_512x1024_80k_cityscapes-20201226_080942.log.json) | | DeepLabV3+ | R-50-D8 | 512x1024 | 80000 | - | - | 80.09 | 81.13 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes/deeplabv3plus_r50-d8_512x1024_80k_cityscapes_20200606_114049-f9fb496d.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes/deeplabv3plus_r50-d8_512x1024_80k_cityscapes_20200606_114049.log.json) | | DeepLabV3+ | R-101-D8 | 512x1024 | 80000 | - | - | 80.97 | 82.03 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_cityscapes_20200606_114143-068fcfe9.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_cityscapes_20200606_114143.log.json) | +| DeepLabV3+ (FP16)| R-101-D8 | 512x1024 | 80000 | 6.35 | 7.87 | 80.46 | - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-f1104f4b.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920.log.json) | | DeepLabV3+ | R-18-D8 | 769x769 | 80000 | 2.5 | 5.74 | 76.26 | 77.91 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r18-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_769x769_80k_cityscapes/deeplabv3plus_r18-d8_769x769_80k_cityscapes_20201226_083346-f326e06a.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_769x769_80k_cityscapes/deeplabv3plus_r18-d8_769x769_80k_cityscapes-20201226_083346.log.json) | | DeepLabV3+ | R-50-D8 | 769x769 | 80000 | - | - | 79.83 | 81.48 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes/deeplabv3plus_r50-d8_769x769_80k_cityscapes_20200606_210233-0e9dfdc4.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes/deeplabv3plus_r50-d8_769x769_80k_cityscapes_20200606_210233.log.json) | | DeepLabV3+ | R-101-D8 | 769x769 | 80000 | - | - | 80.98 | 82.18 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes/deeplabv3plus_r101-d8_769x769_80k_cityscapes_20200607_000405-a7573d20.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes/deeplabv3plus_r101-d8_769x769_80k_cityscapes_20200607_000405.log.json) | @@ -83,3 +84,7 @@ | ---------- | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | -------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | DeepLabV3+ | R-101-D8 | 480x480 | 40000 | - | - | 52.86 | 54.54 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59_20210416_111233-ed937f15.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59-20210416_111233.log.json) | | DeepLabV3+ | R-101-D8 | 480x480 | 80000 | - | - | 53.2 | 54.67 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59_20210416_111127-7ca0331d.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59-20210416_111127.log.json) | + +Note: + +- `FP16` means Mixed Precision (FP16) is adopted in training. diff --git a/configs/deeplabv3plus/deeplabv3plus.yml b/configs/deeplabv3plus/deeplabv3plus.yml index ff78da378..7b54f5003 100644 --- a/configs/deeplabv3plus/deeplabv3plus.yml +++ b/configs/deeplabv3plus/deeplabv3plus.yml @@ -152,6 +152,27 @@ Models: mIoU(ms+flip): 82.03 Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_cityscapes_20200606_114143-068fcfe9.pth +- Name: deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes + In Collection: deeplabv3plus + Metadata: + backbone: R-101-D8 + crop size: (512,1024) + lr schd: 80000 + inference time (ms/im): + - value: 127.06 + hardware: V100 + backend: PyTorch + batch size: 1 + mode: FP16 + resolution: (512,1024) + memory (GB): 6.35 + Results: + - Task: Semantic Segmentation + Dataset: Cityscapes + Metrics: + mIoU: 80.46 + Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py + Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-f1104f4b.pth - Name: deeplabv3plus_r18-d8_769x769_80k_cityscapes In Collection: deeplabv3plus Metadata: diff --git a/configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py b/configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py similarity index 62% rename from configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py rename to configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py index 1d7e1bef6..fc369405d 100644 --- a/configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py +++ b/configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py @@ -1,4 +1,4 @@ -_base_ = '../deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py' +_base_ = './deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py' # fp16 settings optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) # fp16 placeholder diff --git a/configs/fcn/README.md b/configs/fcn/README.md index d33f402ea..3a2712abf 100644 --- a/configs/fcn/README.md +++ b/configs/fcn/README.md @@ -39,6 +39,7 @@ | FCN | R-18-D8 | 512x1024 | 80000 | 1.7 | 14.65 | 71.11 | 72.91 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r18-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r18-d8_512x1024_80k_cityscapes/fcn_r18-d8_512x1024_80k_cityscapes_20201225_021327-6c50f8b4.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r18-d8_512x1024_80k_cityscapes/fcn_r18-d8_512x1024_80k_cityscapes-20201225_021327.log.json) | | FCN | R-50-D8 | 512x1024 | 80000 | - | | 73.61 | 74.24 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r50-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r50-d8_512x1024_80k_cityscapes/fcn_r50-d8_512x1024_80k_cityscapes_20200606_113019-03aa804d.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r50-d8_512x1024_80k_cityscapes/fcn_r50-d8_512x1024_80k_cityscapes_20200606_113019.log.json) | | FCN | R-101-D8 | 512x1024 | 80000 | - | - | 75.13 | 75.94 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r101-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_512x1024_80k_cityscapes/fcn_r101-d8_512x1024_80k_cityscapes_20200606_113038-3fb937eb.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_512x1024_80k_cityscapes/fcn_r101-d8_512x1024_80k_cityscapes_20200606_113038.log.json) | +| FCN (FP16)| R-101-D8 | 512x1024 | 80000 | 5.37 | 8.64 | 76.80 | - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes/fcn_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230921-fb13e883.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes/fcn_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230921.log.json) | | FCN | R-18-D8 | 769x769 | 80000 | 1.9 | 6.40 | 70.80 | 73.16 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r18-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r18-d8_769x769_80k_cityscapes/fcn_r18-d8_769x769_80k_cityscapes_20201225_021451-9739d1b8.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r18-d8_769x769_80k_cityscapes/fcn_r18-d8_769x769_80k_cityscapes-20201225_021451.log.json) | | FCN | R-50-D8 | 769x769 | 80000 | - | - | 72.64 | 73.32 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r50-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r50-d8_769x769_80k_cityscapes/fcn_r50-d8_769x769_80k_cityscapes_20200606_195749-f5caeabc.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r50-d8_769x769_80k_cityscapes/fcn_r50-d8_769x769_80k_cityscapes_20200606_195749.log.json) | | FCN | R-101-D8 | 769x769 | 80000 | - | - | 75.52 | 76.61 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r101-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_769x769_80k_cityscapes/fcn_r101-d8_769x769_80k_cityscapes_20200606_214354-45cbac68.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_769x769_80k_cityscapes/fcn_r101-d8_769x769_80k_cityscapes_20200606_214354.log.json) | @@ -92,3 +93,7 @@ | ------ | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | ------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | FCN | R-101-D8 | 480x480 | 40000 | - | - | 48.42 | 50.4 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r101-d8_480x480_40k_pascal_context_59.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_480x480_40k_pascal_context_59/fcn_r101-d8_480x480_40k_pascal_context_59_20210415_230724-8cf83682.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_480x480_40k_pascal_context_59/fcn_r101-d8_480x480_40k_pascal_context_59-20210415_230724.log.json) | | FCN | R-101-D8 | 480x480 | 80000 | - | - | 49.35 | 51.38 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r101-d8_480x480_80k_pascal_context_59.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_480x480_80k_pascal_context_59/fcn_r101-d8_480x480_80k_pascal_context_59_20210416_110804-9a6f2c94.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_480x480_80k_pascal_context_59/fcn_r101-d8_480x480_80k_pascal_context_59-20210416_110804.log.json) | + +Note: + +- `FP16` means Mixed Precision (FP16) is adopted in training. diff --git a/configs/fcn/fcn.yml b/configs/fcn/fcn.yml index 3f889c48d..fa6e576d4 100644 --- a/configs/fcn/fcn.yml +++ b/configs/fcn/fcn.yml @@ -155,6 +155,27 @@ Models: mIoU(ms+flip): 75.94 Config: configs/fcn/fcn_r101-d8_512x1024_80k_cityscapes.py Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_512x1024_80k_cityscapes/fcn_r101-d8_512x1024_80k_cityscapes_20200606_113038-3fb937eb.pth +- Name: fcn_r101-d8_fp16_512x1024_80k_cityscapes + In Collection: fcn + Metadata: + backbone: R-101-D8 + crop size: (512,1024) + lr schd: 80000 + inference time (ms/im): + - value: 115.74 + hardware: V100 + backend: PyTorch + batch size: 1 + mode: FP16 + resolution: (512,1024) + memory (GB): 5.37 + Results: + - Task: Semantic Segmentation + Dataset: Cityscapes + Metrics: + mIoU: 76.8 + Config: configs/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py + Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes/fcn_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230921-fb13e883.pth - Name: fcn_r18-d8_769x769_80k_cityscapes In Collection: fcn Metadata: diff --git a/configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py b/configs/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py similarity index 67% rename from configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py rename to configs/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py index 8e85e56bd..c6739d952 100644 --- a/configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py +++ b/configs/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py @@ -1,4 +1,4 @@ -_base_ = '../fcn/fcn_r101-d8_512x1024_80k_cityscapes.py' +_base_ = './fcn_r101-d8_512x1024_80k_cityscapes.py' # fp16 settings optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) # fp16 placeholder diff --git a/configs/fp16/README.md b/configs/fp16/README.md deleted file mode 100644 index bbc73cc5a..000000000 --- a/configs/fp16/README.md +++ /dev/null @@ -1,34 +0,0 @@ -# Mixed Precision Training - -## Introduction - - - -Official Repo - -Code Snippet - -
-Mixed Precision (FP16) Training (ArXiv'2017) - -```latex -@article{micikevicius2017mixed, - title={Mixed precision training}, - author={Micikevicius, Paulius and Narang, Sharan and Alben, Jonah and Diamos, Gregory and Elsen, Erich and Garcia, David and Ginsburg, Boris and Houston, Michael and Kuchaiev, Oleksii and Venkatesh, Ganesh and others}, - journal={arXiv preprint arXiv:1710.03740}, - year={2017} -} -``` - -
- -## Results and models - -### Cityscapes - -| Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download | -| ---------- | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | ------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| FCN | R-101-D8 | 512x1024 | 80000 | 5.37 | 8.64 | 76.80 | - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes/fcn_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230921-50245227.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes/fcn_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230921.log.json) | -| PSPNet | R-101-D8 | 512x1024 | 80000 | 5.34 | 8.77 | 79.46 | - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes/pspnet_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230919-ade37931.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes/pspnet_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230919.log.json) | -| DeepLabV3 | R-101-D8 | 512x1024 | 80000 | 5.75 | 3.86 | 80.48 | - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920-bc86dc84.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920.log.json) | -| DeepLabV3+ | R-101-D8 | 512x1024 | 80000 | 6.35 | 7.87 | 80.46 | - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920-cc58bc8d.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920.log.json) | diff --git a/configs/fp16/fp16.yml b/configs/fp16/fp16.yml deleted file mode 100644 index 755642e7b..000000000 --- a/configs/fp16/fp16.yml +++ /dev/null @@ -1,99 +0,0 @@ -Collections: -- Name: fp16 - Metadata: - Training Data: - - Cityscapes - Paper: - URL: https://arxiv.org/abs/1710.03740 - Title: Mixed Precision Training - README: configs/fp16/README.md - Code: - URL: https://github.com/open-mmlab/mmcv/blob/v1.3.14/mmcv/runner/hooks/optimizer.py#L134 - Version: v1.3.14 - Converted From: - Code: https://github.com/baidu-research/DeepBench -Models: -- Name: fcn_r101-d8_512x1024_80k_fp16_cityscapes - In Collection: fp16 - Metadata: - backbone: R-101-D8 - crop size: (512,1024) - lr schd: 80000 - inference time (ms/im): - - value: 115.74 - hardware: V100 - backend: PyTorch - batch size: 1 - mode: FP32 - resolution: (512,1024) - memory (GB): 5.37 - Results: - - Task: Semantic Segmentation - Dataset: Cityscapes - Metrics: - mIoU: 76.8 - Config: configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py - Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes/fcn_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230921-50245227.pth -- Name: pspnet_r101-d8_512x1024_80k_fp16_cityscapes - In Collection: fp16 - Metadata: - backbone: R-101-D8 - crop size: (512,1024) - lr schd: 80000 - inference time (ms/im): - - value: 114.03 - hardware: V100 - backend: PyTorch - batch size: 1 - mode: FP32 - resolution: (512,1024) - memory (GB): 5.34 - Results: - - Task: Semantic Segmentation - Dataset: Cityscapes - Metrics: - mIoU: 79.46 - Config: configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py - Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes/pspnet_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230919-ade37931.pth -- Name: deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes - In Collection: fp16 - Metadata: - backbone: R-101-D8 - crop size: (512,1024) - lr schd: 80000 - inference time (ms/im): - - value: 259.07 - hardware: V100 - backend: PyTorch - batch size: 1 - mode: FP32 - resolution: (512,1024) - memory (GB): 5.75 - Results: - - Task: Semantic Segmentation - Dataset: Cityscapes - Metrics: - mIoU: 80.48 - Config: configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py - Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920-bc86dc84.pth -- Name: deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes - In Collection: fp16 - Metadata: - backbone: R-101-D8 - crop size: (512,1024) - lr schd: 80000 - inference time (ms/im): - - value: 127.06 - hardware: V100 - backend: PyTorch - batch size: 1 - mode: FP32 - resolution: (512,1024) - memory (GB): 6.35 - Results: - - Task: Semantic Segmentation - Dataset: Cityscapes - Metrics: - mIoU: 80.46 - Config: configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py - Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920-cc58bc8d.pth diff --git a/configs/pspnet/README.md b/configs/pspnet/README.md index 72b280ada..ad7fcdf4c 100644 --- a/configs/pspnet/README.md +++ b/configs/pspnet/README.md @@ -35,6 +35,7 @@ | PSPNet | R-18-D8 | 512x1024 | 80000 | 1.7 | 15.71 | 74.87 | 76.04 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r18-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r18-d8_512x1024_80k_cityscapes/pspnet_r18-d8_512x1024_80k_cityscapes_20201225_021458-09ffa746.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r18-d8_512x1024_80k_cityscapes/pspnet_r18-d8_512x1024_80k_cityscapes-20201225_021458.log.json) | | PSPNet | R-50-D8 | 512x1024 | 80000 | - | - | 78.55 | 79.79 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r50-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x1024_80k_cityscapes/pspnet_r50-d8_512x1024_80k_cityscapes_20200606_112131-2376f12b.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x1024_80k_cityscapes/pspnet_r50-d8_512x1024_80k_cityscapes_20200606_112131.log.json) | | PSPNet | R-101-D8 | 512x1024 | 80000 | - | - | 79.76 | 81.01 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes/pspnet_r101-d8_512x1024_80k_cityscapes_20200606_112211-e1e1100f.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes/pspnet_r101-d8_512x1024_80k_cityscapes_20200606_112211.log.json) | +| PSPNet (FP16) | R-101-D8 | 512x1024 | 80000 | 5.34 | 8.77 | 79.46 | - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes/pspnet_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230919-a0875e5c.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes/pspnet_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230919.log.json) | | PSPNet | R-18-D8 | 769x769 | 80000 | 1.9 | 6.20 | 75.90 | 77.86 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r18-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r18-d8_769x769_80k_cityscapes/pspnet_r18-d8_769x769_80k_cityscapes_20201225_021458-3deefc62.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r18-d8_769x769_80k_cityscapes/pspnet_r18-d8_769x769_80k_cityscapes-20201225_021458.log.json) | | PSPNet | R-50-D8 | 769x769 | 80000 | - | - | 79.59 | 80.69 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r50-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_769x769_80k_cityscapes/pspnet_r50-d8_769x769_80k_cityscapes_20200606_210121-5ccf03dd.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_769x769_80k_cityscapes/pspnet_r50-d8_769x769_80k_cityscapes_20200606_210121.log.json) | | PSPNet | R-101-D8 | 769x769 | 80000 | - | - | 79.77 | 81.06 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_769x769_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_769x769_80k_cityscapes/pspnet_r101-d8_769x769_80k_cityscapes_20200606_225055-dba412fa.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_769x769_80k_cityscapes/pspnet_r101-d8_769x769_80k_cityscapes_20200606_225055.log.json) | @@ -112,3 +113,7 @@ We support evaluation results on these two datasets using models above trained o | PSPNet | R-101-D8 | 512x512 | 160000 | - | - | 41.28 | 41.66 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet_r101-d8_512x512_4x4_160k_coco-stuff164k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x512_4x4_160k_coco-stuff164k/pspnet_r101-d8_512x512_4x4_160k_coco-stuff164k_20210707_152004-4af9621b.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x512_4x4_160k_coco-stuff164k/pspnet_r101-d8_512x512_4x4_160k_coco-stuff164k_20210707_152004.log.json) | | PSPNet | R-50-D8 | 512x512 | 320000 | - | - | 40.53 | 40.75 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k/pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k_20210707_152004-be9610cc.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k/pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k_20210707_152004.log.json) | | PSPNet | R-101-D8 | 512x512 | 320000 | - | - | 41.95 | 42.42 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k/pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k_20210707_152004-72220c60.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k/pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k_20210707_152004.log.json) | + +Note: + +- `FP16` means Mixed Precision (FP16) is adopted in training. diff --git a/configs/pspnet/pspnet.yml b/configs/pspnet/pspnet.yml index 4b3cd1f41..1a46b4632 100644 --- a/configs/pspnet/pspnet.yml +++ b/configs/pspnet/pspnet.yml @@ -158,6 +158,27 @@ Models: mIoU(ms+flip): 81.01 Config: configs/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py Weights: https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes/pspnet_r101-d8_512x1024_80k_cityscapes_20200606_112211-e1e1100f.pth +- Name: pspnet_r101-d8_fp16_512x1024_80k_cityscapes + In Collection: pspnet + Metadata: + backbone: R-101-D8 + crop size: (512,1024) + lr schd: 80000 + inference time (ms/im): + - value: 114.03 + hardware: V100 + backend: PyTorch + batch size: 1 + mode: FP16 + resolution: (512,1024) + memory (GB): 5.34 + Results: + - Task: Semantic Segmentation + Dataset: Cityscapes + Metrics: + mIoU: 79.46 + Config: configs/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py + Weights: https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes/pspnet_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230919-a0875e5c.pth - Name: pspnet_r18-d8_769x769_80k_cityscapes In Collection: pspnet Metadata: diff --git a/configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py b/configs/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py similarity index 60% rename from configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py rename to configs/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py index eaf569d4d..c71b7f638 100644 --- a/configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py +++ b/configs/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py @@ -1,4 +1,4 @@ -_base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py' +_base_ = './pspnet_r101-d8_512x1024_80k_cityscapes.py' # fp16 settings optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.) # fp16 placeholder diff --git a/docs/model_zoo.md b/docs/model_zoo.md index 7babd2e5b..ce23b5367 100644 --- a/docs/model_zoo.md +++ b/docs/model_zoo.md @@ -129,7 +129,7 @@ Please refer to [CGNet](https://github.com/open-mmlab/mmsegmentation/blob/master ### Mixed Precision (FP16) Training -Please refer [Mixed Precision (FP16) Training](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16) for details. +Please refer [Mixed Precision (FP16) Training] on BiSeNetV2 (https://github.com/open-mmlab/mmsegmentation/blob/master/configs/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py) for details. ### U-Net diff --git a/docs_zh-CN/model_zoo.md b/docs_zh-CN/model_zoo.md index a7f6ead5d..a165865c8 100644 --- a/docs_zh-CN/model_zoo.md +++ b/docs_zh-CN/model_zoo.md @@ -119,7 +119,7 @@ ### Mixed Precision (FP16) Training -Please refer [Mixed Precision (FP16) Training](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16/README.md) for details. +请参考 [Mixed Precision (FP16) Training] 在 BiSeNetV2 训练的样例 (https://github.com/open-mmlab/mmsegmentation/blob/master/configs/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py) for details. ## 速度标定 diff --git a/model-index.yml b/model-index.yml index 00da8d6a2..487bafdba 100644 --- a/model-index.yml +++ b/model-index.yml @@ -16,7 +16,6 @@ Import: - configs/fastfcn/fastfcn.yml - configs/fastscnn/fastscnn.yml - configs/fcn/fcn.yml -- configs/fp16/fp16.yml - configs/gcnet/gcnet.yml - configs/hrnet/hrnet.yml - configs/icnet/icnet.yml