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.py | 8 ++++----
1 files changed, 4 insertions(+), 4 deletions(-)
diff --git a/code/batch_testing.py b/code/batch_testing.py
index 74ad58b..58d3b30 100644
--- a/code/batch_testing.py
+++ b/code/batch_testing.py
@@ -62,7 +62,7 @@
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':
@@ -123,9 +123,9 @@
label_roll = labels[:,2].float()
pre_yaw, pre_pitch, pre_roll, angles = model(images)
- yaw = angles[args.iter_ref-1][:,0].cpu().data
- pitch = angles[args.iter_ref-1][:,1].cpu().data
- roll = angles[args.iter_ref-1][:,2].cpu().data
+ yaw = angles[-1][:,0].cpu().data
+ pitch = angles[-1][:,1].cpu().data
+ roll = angles[-1][:,2].cpu().data
# Mean absolute error
yaw_error += torch.sum(torch.abs(yaw - label_yaw) * 3)
--
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