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')
--
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