From ec99c6649af6bdbd3c836f20cdc81170e7045cc8 Mon Sep 17 00:00:00 2001
From: natanielruiz <nataniel777@hotmail.com>
Date: 星期四, 14 九月 2017 10:06:48 +0800
Subject: [PATCH] Training hopenet and normal for different alpha values on AFLW
---
code/batch_testing_preangles.py | 4 ++--
1 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/code/batch_testing_preangles.py b/code/batch_testing_preangles.py
index 11390b0..bb2047f 100644
--- a/code/batch_testing_preangles.py
+++ b/code/batch_testing_preangles.py
@@ -50,7 +50,7 @@
# ResNet101 with 3 outputs.
# model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 23, 3], 66)
# ResNet50
- model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66)
+ model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66, 0)
# ResNet18
# model = hopenet.Hopenet(torchvision.models.resnet.BasicBlock, [2, 2, 2, 2], 66)
@@ -61,7 +61,7 @@
print 'Loading data.'
transformations = transforms.Compose([transforms.Scale(224),
- transforms.RandomCrop(224), transforms.ToTensor(),
+ transforms.CenterCrop(224), transforms.ToTensor(),
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])])
if args.dataset == 'AFLW2000':
--
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