From 4b67b5c8ed5566ec3030d537536282e830d87e40 Mon Sep 17 00:00:00 2001
From: natanielruiz <nruiz9@gatech.edu>
Date: 星期一, 30 十月 2017 07:15:49 +0800
Subject: [PATCH] next
---
code/test_on_video.py | 15 ++++++++++-----
1 files changed, 10 insertions(+), 5 deletions(-)
diff --git a/code/test_on_video.py b/code/test_on_video.py
index c4172da..bbafbd8 100644
--- a/code/test_on_video.py
+++ b/code/test_on_video.py
@@ -47,7 +47,7 @@
if not os.path.exists(args.video_path):
sys.exit('Video does not exist')
- # ResNet50
+ # ResNet50 structure
model = hopenet.Hopenet(torchvision.models.resnet.Bottleneck, [3, 4, 6, 3], 66)
print 'Loading snapshot.'
@@ -154,11 +154,16 @@
img = img.view(1, img_shape[0], img_shape[1], img_shape[2])
img = Variable(img).cuda(gpu)
- yaw, pitch, roll, angles = model(img)
+ yaw, pitch, roll = model(img)
- yaw_predicted = angles[:,0].data[0].cpu()
- pitch_predicted = angles[:,1].data[0].cpu()
- roll_predicted = angles[:,2].data[0].cpu()
+ yaw_predicted = F.softmax(yaw)
+ pitch_predicted = F.softmax(pitch)
+ roll_predicted = F.softmax(roll)
+ # Get continuous predictions in degrees.
+ yaw_predicted = torch.sum(yaw_predicted.data[0] * idx_tensor) * 3 - 99
+ pitch_predicted = torch.sum(pitch_predicted.data[0] * idx_tensor) * 3 - 99
+ roll_predicted = torch.sum(roll_predicted.data[0] * idx_tensor) * 3 - 99
+
# Print new frame with cube and axis
txt_out.write(str(frame_num) + ' %f %f %f\n' % (yaw_predicted, pitch_predicted, roll_predicted))
# utils.plot_pose_cube(frame, yaw_predicted, pitch_predicted, roll_predicted, (x_min + x_max) / 2, (y_min + y_max) / 2, size = bbox_width)
--
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