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/hopenet.py | 18 ++----------------
1 files changed, 2 insertions(+), 16 deletions(-)
diff --git a/code/hopenet.py b/code/hopenet.py
index 0a98a66..c9e0b74 100644
--- a/code/hopenet.py
+++ b/code/hopenet.py
@@ -24,11 +24,8 @@
self.fc_pitch = nn.Linear(512 * block.expansion, num_bins)
self.fc_roll = nn.Linear(512 * block.expansion, num_bins)
+ # Vestigial layer from previous experiments
self.fc_finetune = nn.Linear(512 * block.expansion + 3, 3)
-
- # Used to get the expected value of angle from bins
- self.softmax = nn.Softmax()
- self.idx_tensor = Variable(torch.FloatTensor(range(66))).cuda()
for m in self.modules():
if isinstance(m, nn.Conv2d):
@@ -72,18 +69,7 @@
pre_pitch = self.fc_pitch(x)
pre_roll = self.fc_roll(x)
- yaw = self.softmax(pre_yaw)
- yaw = Variable(torch.sum(yaw.data * self.idx_tensor.data, 1), requires_grad=True)
- pitch = self.softmax(pre_pitch)
- pitch = Variable(torch.sum(pitch.data * self.idx_tensor.data, 1), requires_grad=True)
- roll = self.softmax(pre_roll)
- roll = Variable(torch.sum(roll.data * self.idx_tensor.data, 1), requires_grad=True)
- yaw = yaw.view(yaw.size(0), 1)
- pitch = pitch.view(pitch.size(0), 1)
- roll = roll.view(roll.size(0), 1)
- preangles = torch.cat([yaw, pitch, roll], 1)
-
- return pre_yaw, pre_pitch, pre_roll, preangles
+ return pre_yaw, pre_pitch, pre_roll
class ResNet(nn.Module):
# ResNet for regression of 3 Euler angles.
--
Gitblit v1.8.0