From a2c1b973f7f4bb20bd043c127b03b29e97a65222 Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.anjos@idiap.ch>
Date: Wed, 27 May 2020 18:00:15 +0200
Subject: [PATCH] [models.driu_od] Fix copy-n-paste error on backbone layer
selection
---
bob/ip/binseg/models/driu_od.py | 10 +++++++---
1 file changed, 7 insertions(+), 3 deletions(-)
diff --git a/bob/ip/binseg/models/driu_od.py b/bob/ip/binseg/models/driu_od.py
index e45755af..5ba6a7e2 100644
--- a/bob/ip/binseg/models/driu_od.py
+++ b/bob/ip/binseg/models/driu_od.py
@@ -24,7 +24,9 @@ class DRIUOD(torch.nn.Module):
def __init__(self, in_channels_list=None):
super(DRIUOD, self).__init__()
- in_upsample2, in_upsample_4, in_upsample_8, in_upsample_16 = in_channels_list
+ in_upsample2, in_upsample_4, in_upsample_8, in_upsample_16 = (
+ in_channels_list
+ )
self.upsample2 = UpsampleCropBlock(in_upsample2, 16, 4, 2, 0)
# Upsample layers
@@ -83,14 +85,16 @@ def driu_od(pretrained_backbone=True, progress=True):
"""
backbone = vgg16_for_segmentation(
- pretrained=pretrained_backbone, progress=progress,
- return_features=[3, 8, 14, 22],
+ pretrained=pretrained_backbone,
+ progress=progress,
+ return_features=[8, 14, 22, 29],
)
head = DRIUOD([128, 256, 512, 512])
order = [("backbone", backbone), ("head", head)]
if pretrained_backbone:
from .normalizer import TorchVisionNormalizer
+
order = [("normalizer", TorchVisionNormalizer())] + order
model = torch.nn.Sequential(OrderedDict(order))
--
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