From d56f6823a2c3f945a1ac07fb7939065ebce94277 Mon Sep 17 00:00:00 2001 From: Junjun2016 <hejunjun@sjtu.edu.cn> Date: Mon, 11 Jan 2021 16:07:59 +0800 Subject: [PATCH] Add more UNet-based medical segmentation benchmark (#324) * Add UNet as backbone and FCN PSPNet DeepLabV3 as decode_head benchmark on 4 retinal vessel segmentation datasets * adjust README of UNet --- .../_base_/models/deeplabv3_unet_s5-d16.py | 50 +++++++++++++++++++ .../{unet_s5-d16.py => fcn_unet_s5-d16.py} | 0 configs/_base_/models/pspnet_unet_s5-d16.py | 50 +++++++++++++++++++ configs/unet/README.md | 37 +++++++++++--- ...labv3_unet_s5-d16_128x128_40k_chase_db1.py | 7 +++ ...deeplabv3_unet_s5-d16_128x128_40k_stare.py | 6 +++ .../deeplabv3_unet_s5-d16_256x256_40k_hrf.py | 6 +++ .../deeplabv3_unet_s5-d16_64x64_40k_drive.py | 6 +++ .../fcn_unet_s5-d16_128x128_40k_chase_db1.py | 6 +++ ...y => fcn_unet_s5-d16_128x128_40k_stare.py} | 2 +- ....py => fcn_unet_s5-d16_256x256_40k_hrf.py} | 2 +- ....py => fcn_unet_s5-d16_64x64_40k_drive.py} | 2 +- ...spnet_unet_s5-d16_128x128_40k_chase_db1.py | 7 +++ ...> pspnet_unet_s5-d16_128x128_40k_stare.py} | 2 +- .../pspnet_unet_s5-d16_256x256_40k_hrf.py | 6 +++ .../pspnet_unet_s5-d16_64x64_40k_drive.py | 6 +++ 16 files changed, 185 insertions(+), 10 deletions(-) create mode 100644 configs/_base_/models/deeplabv3_unet_s5-d16.py rename configs/_base_/models/{unet_s5-d16.py => fcn_unet_s5-d16.py} (100%) create mode 100644 configs/_base_/models/pspnet_unet_s5-d16.py create mode 100644 configs/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py create mode 100644 configs/unet/deeplabv3_unet_s5-d16_128x128_40k_stare.py create mode 100644 configs/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf.py create mode 100644 configs/unet/deeplabv3_unet_s5-d16_64x64_40k_drive.py create mode 100644 configs/unet/fcn_unet_s5-d16_128x128_40k_chase_db1.py rename configs/unet/{unet_s5-d16_128x128_40k_chase_db1.py => fcn_unet_s5-d16_128x128_40k_stare.py} (70%) rename configs/unet/{unet_s5-d16_256x256_40k_hrf.py => fcn_unet_s5-d16_256x256_40k_hrf.py} (71%) rename configs/unet/{unet_s5-d16_64x64_40k_drive.py => fcn_unet_s5-d16_64x64_40k_drive.py} (70%) create mode 100644 configs/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1.py rename configs/unet/{unet_s5-d16_128x128_40k_stare.py => pspnet_unet_s5-d16_128x128_40k_stare.py} (69%) create mode 100644 configs/unet/pspnet_unet_s5-d16_256x256_40k_hrf.py create mode 100644 configs/unet/pspnet_unet_s5-d16_64x64_40k_drive.py diff --git a/configs/_base_/models/deeplabv3_unet_s5-d16.py b/configs/_base_/models/deeplabv3_unet_s5-d16.py new file mode 100644 index 00000000..9fce4751 --- /dev/null +++ b/configs/_base_/models/deeplabv3_unet_s5-d16.py @@ -0,0 +1,50 @@ +# model settings +norm_cfg = dict(type='SyncBN', requires_grad=True) +model = dict( + type='EncoderDecoder', + pretrained=None, + backbone=dict( + type='UNet', + in_channels=3, + base_channels=64, + num_stages=5, + strides=(1, 1, 1, 1, 1), + enc_num_convs=(2, 2, 2, 2, 2), + dec_num_convs=(2, 2, 2, 2), + downsamples=(True, True, True, True), + enc_dilations=(1, 1, 1, 1, 1), + dec_dilations=(1, 1, 1, 1), + with_cp=False, + conv_cfg=None, + norm_cfg=norm_cfg, + act_cfg=dict(type='ReLU'), + upsample_cfg=dict(type='InterpConv'), + norm_eval=False), + decode_head=dict( + type='ASPPHead', + in_channels=64, + in_index=4, + channels=16, + dilations=(1, 12, 24, 36), + dropout_ratio=0.1, + num_classes=2, + norm_cfg=norm_cfg, + align_corners=False, + loss_decode=dict( + type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), + auxiliary_head=dict( + type='FCNHead', + in_channels=128, + in_index=3, + channels=64, + num_convs=1, + concat_input=False, + dropout_ratio=0.1, + num_classes=2, + norm_cfg=norm_cfg, + align_corners=False, + loss_decode=dict( + type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4))) +# model training and testing settings +train_cfg = dict() +test_cfg = dict(mode='slide', crop_size=256, stride=170) diff --git a/configs/_base_/models/unet_s5-d16.py b/configs/_base_/models/fcn_unet_s5-d16.py similarity index 100% rename from configs/_base_/models/unet_s5-d16.py rename to configs/_base_/models/fcn_unet_s5-d16.py diff --git a/configs/_base_/models/pspnet_unet_s5-d16.py b/configs/_base_/models/pspnet_unet_s5-d16.py new file mode 100644 index 00000000..3be98685 --- /dev/null +++ b/configs/_base_/models/pspnet_unet_s5-d16.py @@ -0,0 +1,50 @@ +# model settings +norm_cfg = dict(type='SyncBN', requires_grad=True) +model = dict( + type='EncoderDecoder', + pretrained=None, + backbone=dict( + type='UNet', + in_channels=3, + base_channels=64, + num_stages=5, + strides=(1, 1, 1, 1, 1), + enc_num_convs=(2, 2, 2, 2, 2), + dec_num_convs=(2, 2, 2, 2), + downsamples=(True, True, True, True), + enc_dilations=(1, 1, 1, 1, 1), + dec_dilations=(1, 1, 1, 1), + with_cp=False, + conv_cfg=None, + norm_cfg=norm_cfg, + act_cfg=dict(type='ReLU'), + upsample_cfg=dict(type='InterpConv'), + norm_eval=False), + decode_head=dict( + type='PSPHead', + in_channels=64, + in_index=4, + channels=16, + pool_scales=(1, 2, 3, 6), + dropout_ratio=0.1, + num_classes=2, + norm_cfg=norm_cfg, + align_corners=False, + loss_decode=dict( + type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), + auxiliary_head=dict( + type='FCNHead', + in_channels=128, + in_index=3, + channels=64, + num_convs=1, + concat_input=False, + dropout_ratio=0.1, + num_classes=2, + norm_cfg=norm_cfg, + align_corners=False, + loss_decode=dict( + type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4))) +# model training and testing settings +train_cfg = dict() +test_cfg = dict(mode='slide', crop_size=256, stride=170) diff --git a/configs/unet/README.md b/configs/unet/README.md index 760e0912..d815510a 100644 --- a/configs/unet/README.md +++ b/configs/unet/README.md @@ -17,9 +17,34 @@ ## Results and models -| Backbone | Head | Dataset | Image Size | Crop Size | Stride | Lr schd | Mem (GB) | Inf time (fps) | Dice | download | -|--------|----------|----------|----------|-----------|--------:|----------|----------------|------:|--------------:|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| UNet-S5-D16 | FCN | DRIVE | 584x565 | 64x64 | 42x42 | 40000 | 0.680 | - | 78.67 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_64x64_40k_drive/unet_s5-d16_64x64_40k_drive_20201223_191051-9cd163b8.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_64x64_40k_drive/unet_s5-d16_64x64_40k_drive-20201223_191051.log.json) | -| UNet-S5-D16 | FCN | STARE | 605x700 | 128x128 | 85x85 | 40000 | 0.968 | - | 81.02 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_128x128_40k_stare/unet_s5-d16_128x128_40k_stare_20201223_191051-e5439846.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_128x128_40k_stare/unet_s5-d16_128x128_40k_stare-20201223_191051.log.json) | -| UNet-S5-D16 | FCN | CHASE_DB1 | 960x999 | 128x128 | 85x85 | 40000 | 0.968 | - | 80.24 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_128x128_40k_chase_db1/unet_s5-d16_128x128_40k_chase_db1_20201223_191051-8b16ca0b.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_128x128_40k_chase_db1/unet_s5-d16_128x128_40k_chase_db1-20201223_191051.log.json) | -| UNet-S5-D16 | FCN | HRF | 2336x3504 | 256x256 | 170x170 | 40000 | 2.525 | - | 79.45 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_256x256_40k_hrf/unet_s5-d16_256x256_40k_hrf_20201223_173724-d89cf1ed.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/unet_s5-d16_256x256_40k_hrf/unet_s5-d16_256x256_40k_hrf-20201223_173724.log.json) | +### DRIVE + +| Backbone | Head | Image Size | Crop Size | Stride | Lr schd | Mem (GB) | Inf time (fps) | Dice | download | +|--------|----------|----------|-----------|--------:|----------|----------------|------:|--------------:|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| +| UNet-S5-D16 | FCN | 584x565 | 64x64 | 42x42 | 40000 | 0.680 | - | 78.67 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_64x64_40k_drive/fcn_unet_s5-d16_64x64_40k_drive_20201223_191051-26cee593.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_64x64_40k_drive/fcn_unet_s5-d16_64x64_40k_drive-20201223_191051.log.json) | +| UNet-S5-D16 | PSPNet | 584x565 | 64x64 | 42x42 | 40000 | 0.599 | - | 78.62 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_64x64_40k_drive/pspnet_unet_s5-d16_64x64_40k_drive_20201227_181818-aac73387.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_64x64_40k_drive/pspnet_unet_s5-d16_64x64_40k_drive-20201227_181818.log.json) | +| UNet-S5-D16 | DeepLabV3 | 584x565 | 64x64 | 42x42 | 40000 | 0.596 | - | 78.69 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_64x64_40k_drive/deeplabv3_unet_s5-d16_64x64_40k_drive_20201226_094047-0671ff20.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_64x64_40k_drive/deeplabv3_unet_s5-d16_64x64_40k_drive-20201226_094047.log.json) | + +### STARE + +| Backbone | Head | Image Size | Crop Size | Stride | Lr schd | Mem (GB) | Inf time (fps) | Dice | download | +|--------|----------|----------|-----------|--------:|----------|----------------|------:|--------------:|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| +| UNet-S5-D16 | FCN | 605x700 | 128x128 | 85x85 | 40000 | 0.968 | - | 81.02 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_128x128_40k_stare/fcn_unet_s5-d16_128x128_40k_stare_20201223_191051-6ea7cfda.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_128x128_40k_stare/fcn_unet_s5-d16_128x128_40k_stare-20201223_191051.log.json) | +| UNet-S5-D16 | PSPNet | 605x700 | 128x128 | 85x85 | 40000 | 0.982 | - | 81.22 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_128x128_40k_stare/pspnet_unet_s5-d16_128x128_40k_stare_20201227_181818-3c2923c4.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_128x128_40k_stare/pspnet_unet_s5-d16_128x128_40k_stare-20201227_181818.log.json) | +| UNet-S5-D16 | DeepLabV3 | 605x700 | 128x128 | 85x85 | 40000 | 0.999 | - | 80.93 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_128x128_40k_stare/deeplabv3_unet_s5-d16_128x128_40k_stare_20201226_094047-93dcb93c.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_128x128_40k_stare/deeplabv3_unet_s5-d16_128x128_40k_stare-20201226_094047.log.json) | + +### CHASE_DB1 + +| Backbone | Head | Image Size | Crop Size | Stride | Lr schd | Mem (GB) | Inf time (fps) | Dice | download | +|--------|----------|----------|-----------|--------:|----------|----------------|------:|--------------:|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| +| UNet-S5-D16 | FCN | 960x999 | 128x128 | 85x85 | 40000 | 0.968 | - | 80.24 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_128x128_40k_chase_db1/fcn_unet_s5-d16_128x128_40k_chase_db1_20201223_191051-95852f45.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_128x128_40k_chase_db1/fcn_unet_s5-d16_128x128_40k_chase_db1-20201223_191051.log.json) | +| UNet-S5-D16 | PSPNet | 960x999 | 128x128 | 85x85 | 40000 | 0.982 | - | 80.36 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1/pspnet_unet_s5-d16_128x128_40k_chase_db1_20201227_181818-68d4e609.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1/pspnet_unet_s5-d16_128x128_40k_chase_db1-20201227_181818.log.json) | +| UNet-S5-D16 | DeepLabV3 | 960x999 | 128x128 | 85x85 | 40000 | 0.999 | - | 80.47 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1/deeplabv3_unet_s5-d16_128x128_40k_chase_db1_20201226_094047-4c5aefa3.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1/deeplabv3_unet_s5-d16_128x128_40k_chase_db1-20201226_094047.log.json) | + +### HRF + +| Backbone | Head | Image Size | Crop Size | Stride | Lr schd | Mem (GB) | Inf time (fps) | Dice | download | +|--------|----------|----------|-----------|--------:|----------|----------------|------:|--------------:|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| +| UNet-S5-D16 | FCN | 2336x3504 | 256x256 | 170x170 | 40000 | 2.525 | - | 79.45 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_256x256_40k_hrf/fcn_unet_s5-d16_256x256_40k_hrf_20201223_173724-df3ec8c4.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/fcn_unet_s5-d16_256x256_40k_hrf/fcn_unet_s5-d16_256x256_40k_hrf-20201223_173724.log.json) | +| UNet-S5-D16 | PSPNet | 2336x3504 | 256x256 | 170x170 | 40000 | 2.588 | - | 80.07 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_256x256_40k_hrf/pspnet_unet_s5-d16_256x256_40k_hrf_20201227_181818-fdb7e29b.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/pspnet_unet_s5-d16_256x256_40k_hrf/pspnet_unet_s5-d16_256x256_40k_hrf-20201227_181818.log.json) | +| UNet-S5-D16 | DeepLabV3 | 2336x3504 | 256x256 | 170x170 | 40000 | 2.604 | - | 80.21 | [model](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf/deeplabv3_unet_s5-d16_256x256_40k_hrf_20201226_094047-3a1fdf85.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf/deeplabv3_unet_s5-d16_256x256_40k_hrf-20201226_094047.log.json) | diff --git a/configs/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py b/configs/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py new file mode 100644 index 00000000..615d241f --- /dev/null +++ b/configs/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py @@ -0,0 +1,7 @@ +_base_ = [ + '../_base_/models/deeplabv3_unet_s5-d16.py', + '../_base_/datasets/chase_db1.py', '../_base_/default_runtime.py', + '../_base_/schedules/schedule_40k.py' +] +test_cfg = dict(crop_size=(128, 128), stride=(85, 85)) +evaluation = dict(metric='mDice') diff --git a/configs/unet/deeplabv3_unet_s5-d16_128x128_40k_stare.py b/configs/unet/deeplabv3_unet_s5-d16_128x128_40k_stare.py new file mode 100644 index 00000000..286eebf4 --- /dev/null +++ b/configs/unet/deeplabv3_unet_s5-d16_128x128_40k_stare.py @@ -0,0 +1,6 @@ +_base_ = [ + '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/stare.py', + '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' +] +test_cfg = dict(crop_size=(128, 128), stride=(85, 85)) +evaluation = dict(metric='mDice') diff --git a/configs/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf.py b/configs/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf.py new file mode 100644 index 00000000..40a20537 --- /dev/null +++ b/configs/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf.py @@ -0,0 +1,6 @@ +_base_ = [ + '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/hrf.py', + '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' +] +test_cfg = dict(crop_size=(256, 256), stride=(170, 170)) +evaluation = dict(metric='mDice') diff --git a/configs/unet/deeplabv3_unet_s5-d16_64x64_40k_drive.py b/configs/unet/deeplabv3_unet_s5-d16_64x64_40k_drive.py new file mode 100644 index 00000000..1ad6fd68 --- /dev/null +++ b/configs/unet/deeplabv3_unet_s5-d16_64x64_40k_drive.py @@ -0,0 +1,6 @@ +_base_ = [ + '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/drive.py', + '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' +] +test_cfg = dict(crop_size=(64, 64), stride=(42, 42)) +evaluation = dict(metric='mDice') diff --git a/configs/unet/fcn_unet_s5-d16_128x128_40k_chase_db1.py b/configs/unet/fcn_unet_s5-d16_128x128_40k_chase_db1.py new file mode 100644 index 00000000..ff5b7bbc --- /dev/null +++ b/configs/unet/fcn_unet_s5-d16_128x128_40k_chase_db1.py @@ -0,0 +1,6 @@ +_base_ = [ + '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/chase_db1.py', + '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' +] +test_cfg = dict(crop_size=(128, 128), stride=(85, 85)) +evaluation = dict(metric='mDice') diff --git a/configs/unet/unet_s5-d16_128x128_40k_chase_db1.py b/configs/unet/fcn_unet_s5-d16_128x128_40k_stare.py similarity index 70% rename from configs/unet/unet_s5-d16_128x128_40k_chase_db1.py rename to configs/unet/fcn_unet_s5-d16_128x128_40k_stare.py index f67d5658..64070a32 100644 --- a/configs/unet/unet_s5-d16_128x128_40k_chase_db1.py +++ b/configs/unet/fcn_unet_s5-d16_128x128_40k_stare.py @@ -1,5 +1,5 @@ _base_ = [ - '../_base_/models/unet_s5-d16.py', '../_base_/datasets/chase_db1.py', + '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/stare.py', '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' ] test_cfg = dict(crop_size=(128, 128), stride=(85, 85)) diff --git a/configs/unet/unet_s5-d16_256x256_40k_hrf.py b/configs/unet/fcn_unet_s5-d16_256x256_40k_hrf.py similarity index 71% rename from configs/unet/unet_s5-d16_256x256_40k_hrf.py rename to configs/unet/fcn_unet_s5-d16_256x256_40k_hrf.py index 29a80345..8d74c081 100644 --- a/configs/unet/unet_s5-d16_256x256_40k_hrf.py +++ b/configs/unet/fcn_unet_s5-d16_256x256_40k_hrf.py @@ -1,5 +1,5 @@ _base_ = [ - '../_base_/models/unet_s5-d16.py', '../_base_/datasets/hrf.py', + '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/hrf.py', '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' ] test_cfg = dict(crop_size=(256, 256), stride=(170, 170)) diff --git a/configs/unet/unet_s5-d16_64x64_40k_drive.py b/configs/unet/fcn_unet_s5-d16_64x64_40k_drive.py similarity index 70% rename from configs/unet/unet_s5-d16_64x64_40k_drive.py rename to configs/unet/fcn_unet_s5-d16_64x64_40k_drive.py index 29e834a8..c59a408e 100644 --- a/configs/unet/unet_s5-d16_64x64_40k_drive.py +++ b/configs/unet/fcn_unet_s5-d16_64x64_40k_drive.py @@ -1,5 +1,5 @@ _base_ = [ - '../_base_/models/unet_s5-d16.py', '../_base_/datasets/drive.py', + '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/drive.py', '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' ] test_cfg = dict(crop_size=(64, 64), stride=(42, 42)) diff --git a/configs/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1.py b/configs/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1.py new file mode 100644 index 00000000..46500ae8 --- /dev/null +++ b/configs/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1.py @@ -0,0 +1,7 @@ +_base_ = [ + '../_base_/models/pspnet_unet_s5-d16.py', + '../_base_/datasets/chase_db1.py', '../_base_/default_runtime.py', + '../_base_/schedules/schedule_40k.py' +] +test_cfg = dict(crop_size=(128, 128), stride=(85, 85)) +evaluation = dict(metric='mDice') diff --git a/configs/unet/unet_s5-d16_128x128_40k_stare.py b/configs/unet/pspnet_unet_s5-d16_128x128_40k_stare.py similarity index 69% rename from configs/unet/unet_s5-d16_128x128_40k_stare.py rename to configs/unet/pspnet_unet_s5-d16_128x128_40k_stare.py index 756bbe73..4830b2fd 100644 --- a/configs/unet/unet_s5-d16_128x128_40k_stare.py +++ b/configs/unet/pspnet_unet_s5-d16_128x128_40k_stare.py @@ -1,5 +1,5 @@ _base_ = [ - '../_base_/models/unet_s5-d16.py', '../_base_/datasets/stare.py', + '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/stare.py', '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' ] test_cfg = dict(crop_size=(128, 128), stride=(85, 85)) diff --git a/configs/unet/pspnet_unet_s5-d16_256x256_40k_hrf.py b/configs/unet/pspnet_unet_s5-d16_256x256_40k_hrf.py new file mode 100644 index 00000000..dcfb7ec1 --- /dev/null +++ b/configs/unet/pspnet_unet_s5-d16_256x256_40k_hrf.py @@ -0,0 +1,6 @@ +_base_ = [ + '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/hrf.py', + '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' +] +test_cfg = dict(crop_size=(256, 256), stride=(170, 170)) +evaluation = dict(metric='mDice') diff --git a/configs/unet/pspnet_unet_s5-d16_64x64_40k_drive.py b/configs/unet/pspnet_unet_s5-d16_64x64_40k_drive.py new file mode 100644 index 00000000..bf0b0b04 --- /dev/null +++ b/configs/unet/pspnet_unet_s5-d16_64x64_40k_drive.py @@ -0,0 +1,6 @@ +_base_ = [ + '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/drive.py', + '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' +] +test_cfg = dict(crop_size=(64, 64), stride=(42, 42)) +evaluation = dict(metric='mDice') -- GitLab