From 0be0ecf0a8fc6df1f9e354f8aea12b7008f658f1 Mon Sep 17 00:00:00 2001
From: natanielruiz <nataniel777@hotmail.com>
Date: 星期三, 27 九月 2017 06:21:54 +0800
Subject: [PATCH] hopenet experiments
---
code/train_finetune.py | 17 ++++++++++-------
1 files changed, 10 insertions(+), 7 deletions(-)
diff --git a/code/train_finetune.py b/code/train_finetune.py
index 0081d2a..10eb6ad 100644
--- a/code/train_finetune.py
+++ b/code/train_finetune.py
@@ -150,6 +150,7 @@
softmax = nn.Softmax()
criterion = nn.CrossEntropyLoss().cuda()
reg_criterion = nn.MSELoss().cuda()
+ smooth_l1_loss = nn.SmoothL1Loss().cuda()
# Regression loss coefficient
alpha = args.alpha
@@ -165,12 +166,10 @@
print 'Second phase of training (finetuning layer).'
for epoch in range(num_epochs_ft):
- for i, (images, labels, name) in enumerate(train_loader):
+ for i, (images, labels, cont_labels, name) in enumerate(train_loader):
images = Variable(images.cuda(gpu))
- label_yaw = Variable(labels[:,0].cuda(gpu))
- label_pitch = Variable(labels[:,1].cuda(gpu))
- label_roll = Variable(labels[:,2].cuda(gpu))
- label_angles = Variable(labels[:,:3].cuda(gpu))
+
+ label_angles = Variable(cont_labels[:,:3].cuda(gpu))
optimizer.zero_grad()
model.zero_grad()
@@ -180,9 +179,13 @@
# Finetuning loss
loss_seq = []
for idx in xrange(1,len(angles)):
- label_angles_residuals = label_angles.float() - angles[0]
+ label_angles_residuals = label_angles - (angles[0] * 3 - 99)
+ # for idy in xrange(1,idx):
+ # label_angles_residuals += angles[idy] * 3 - 99
label_angles_residuals = label_angles_residuals.detach()
- loss_angles = reg_criterion(angles[idx], label_angles_residuals)
+ # Reconvert to other unit
+ label_angles_residuals = label_angles_residuals / 3.0 + 33
+ loss_angles = smooth_l1_loss(angles[idx], label_angles_residuals)
loss_seq.append(loss_angles)
grad_seq = [torch.Tensor(1).cuda(gpu) for _ in range(len(loss_seq))]
--
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