From 4db9f0a7dabc350101351479623956bc963fe6c2 Mon Sep 17 00:00:00 2001
From: dcarron <daniel.carron@idiap.ch>
Date: Thu, 13 Jun 2024 17:08:23 +0200
Subject: [PATCH] [segmentation.models] Remove resnet model
ResNet was ununsed and non functional in deepdraw, there is no need to
port it over.
---
pyproject.toml | 1 -
.../segmentation/models/backbones/resnet.py | 87 -------------------
2 files changed, 88 deletions(-)
delete mode 100644 src/mednet/libs/segmentation/models/backbones/resnet.py
diff --git a/pyproject.toml b/pyproject.toml
index 432ecb6b..a5680a15 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -429,7 +429,6 @@ driu-pix = "mednet.libs.segmentation.config.models.driu_pix"
hed = "mednet.libs.segmentation.config.models.hed"
lwnet = "mednet.libs.segmentation.config.models.lwnet"
m2unet = "mednet.libs.segmentation.config.models.m2unet"
-#resunet = "mednet.libs.segmentation.config.models.resunet"
unet = "mednet.libs.segmentation.config.models.unet"
# chase-db1 - retinography
diff --git a/src/mednet/libs/segmentation/models/backbones/resnet.py b/src/mednet/libs/segmentation/models/backbones/resnet.py
deleted file mode 100644
index 3bd2b3f3..00000000
--- a/src/mednet/libs/segmentation/models/backbones/resnet.py
+++ /dev/null
@@ -1,87 +0,0 @@
-# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
-#
-# SPDX-License-Identifier: GPL-3.0-or-later
-
-import torchvision.models
-
-try:
- # pytorch >= 1.12
- from torch.hub import load_state_dict_from_url
-except ImportError:
- # pytorch < 1.12
- from torchvision.models.utils import load_state_dict_from_url
-
-
-class ResNet4Segmentation(torchvision.models.resnet.ResNet):
- """Adaptation of base ResNet functionality to U-Net style segmentation.
-
- This version of ResNet is slightly modified so it can be used through
- torchvision's API. It outputs intermediate features which are normally not
- output by the base ResNet implementation, but are required for segmentation
- operations.
-
- Parameters
- ----------
- *args
- Arguments to be passed to the parent ResNet model.
- **kwargs
- Keyword arguments to be passed to the parent ResNet model.
- return_features : :py:class:`list`, Optional
- A list of integers indicating the feature layers to be returned from
- the original module.
- """
-
- def __init__(self, *args, **kwargs):
- self._return_features = kwargs.pop("return_features")
- super().__init__(*args, **kwargs)
-
- def forward(self, x):
- outputs = []
- # hardwiring of input
- outputs.append(x.shape[2:4])
- for index, m in enumerate(self.features):
- x = m(x)
- # extract layers
- if index in self.return_features:
- outputs.append(x)
- return outputs
-
-
-def resnet50_for_segmentation(pretrained=False, progress=True, **kwargs):
- """Create ResNet for segmentation task.
-
- Parameters
- ----------
- pretrained
- If True, uses ResNet50 pretrained weights.
- progress
- If True, shows a progress bar when downloading the pretrained weights.
- **kwargs
- Keyword arguments to be passed to the parent ResNet model.
- return_features : :py:class:`list`, Optional
- A list of integers indicating the feature layers to be returned from
- the original module.
-
- Returns
- -------
- Instance of the ResNet model for segmentation.
- """
- model = ResNet4Segmentation(
- torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], **kwargs
- )
-
- if pretrained:
- state_dict = load_state_dict_from_url(
- torchvision.models.resnet.ResNet50_Weights.DEFAULT.url,
- progress=progress,
- )
- model.load_state_dict(state_dict)
-
- # erase ResNet head (for classification), not used for segmentation
- delattr(model, "avgpool")
- delattr(model, "fc")
-
- return model
-
-
-resnet50_for_segmentation.__doc__ = torchvision.models.resnet50.__doc__
--
GitLab