From dd62d6fa4a85f18a29de009a972f5599b19ec946 Mon Sep 17 00:00:00 2001
From: natanielruiz <nataniel777@hotmail.com>
Date: 星期四, 14 九月 2017 00:51:53 +0800
Subject: [PATCH] Fixing hopenet
---
code/test.py | 22 +++++++++++++++++-----
1 files changed, 17 insertions(+), 5 deletions(-)
diff --git a/code/test.py b/code/test.py
index ca7a820..7f76714 100644
--- a/code/test.py
+++ b/code/test.py
@@ -34,6 +34,7 @@
parser.add_argument('--save_viz', dest='save_viz', help='Save images with pose cube.',
default=False, type=bool)
parser.add_argument('--iter_ref', dest='iter_ref', default=1, type=int)
+ parser.add_argument('--dataset', dest='dataset', help='Dataset type.', default='AFLW2000', type=str)
args = parser.parse_args()
@@ -61,11 +62,21 @@
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])])
- pose_dataset = datasets.AFLW2000(args.data_dir, args.filename_list,
+ if args.dataset == 'AFLW2000':
+ pose_dataset = datasets.AFLW2000(args.data_dir, args.filename_list,
transformations)
+ elif args.dataset == 'BIWI':
+ pose_dataset = datasets.BIWI(args.data_dir, args.filename_list, transformations)
+ elif args.dataset == 'AFLW':
+ pose_dataset = datasets.AFLW(args.data_dir, args.filename_list, transformations)
+ elif args.dataset == 'AFW':
+ pose_dataset = datasets.AFW(args.data_dir, args.filename_list, transformations)
+ else:
+ print 'Error: not a valid dataset name'
+ sys.exit()
test_loader = torch.utils.data.DataLoader(dataset=pose_dataset,
batch_size=args.batch_size,
num_workers=2)
@@ -99,11 +110,12 @@
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[args.iter_ref][:,0].cpu().data
+ pitch = angles[args.iter_ref][:,1].cpu().data
+ roll = angles[args.iter_ref][:,2].cpu().data
# Mean absolute error
+ print yaw.numpy(), label_yaw.numpy()
yaw_error += torch.sum(torch.abs(yaw - label_yaw) * 3)
pitch_error += torch.sum(torch.abs(pitch - label_pitch) * 3)
roll_error += torch.sum(torch.abs(roll - label_roll) * 3)
--
Gitblit v1.8.0