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_preangles.py | 17 +++++++++++++----
1 files changed, 13 insertions(+), 4 deletions(-)
diff --git a/code/test_preangles.py b/code/test_preangles.py
index be9bfda..d4a9f5f 100644
--- a/code/test_preangles.py
+++ b/code/test_preangles.py
@@ -63,6 +63,8 @@
pose_dataset = datasets.Pose_300W_LP_random_ds(args.data_dir, args.filename_list, transformations)
elif args.dataset == 'AFLW2000':
pose_dataset = datasets.AFLW2000(args.data_dir, args.filename_list, transformations)
+ elif args.dataset == 'AFLW2000_ds':
+ pose_dataset = datasets.AFLW2000_ds(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':
@@ -86,6 +88,9 @@
model.eval() # Change model to 'eval' mode (BN uses moving mean/var).
total = 0
+ idx_tensor = [idx for idx in xrange(66)]
+ idx_tensor = torch.FloatTensor(idx_tensor).cuda(gpu)
+
yaw_error = .0
pitch_error = .0
roll_error = .0
@@ -100,7 +105,7 @@
label_pitch = cont_labels[:,1].float()
label_roll = cont_labels[:,2].float()
- yaw, pitch, roll, angles = model(images)
+ yaw, pitch, roll = model(images)
# Binned predictions
_, yaw_bpred = torch.max(yaw.data, 1)
@@ -108,9 +113,13 @@
_, roll_bpred = torch.max(roll.data, 1)
# Continuous predictions
- yaw_predicted = angles[:,0].data.cpu()
- pitch_predicted = angles[:,1].data.cpu()
- roll_predicted = angles[:,2].data.cpu()
+ yaw_predicted = utils.softmax_temperature(yaw.data, 1)
+ pitch_predicted = utils.softmax_temperature(pitch.data, 1)
+ roll_predicted = utils.softmax_temperature(roll.data, 1)
+
+ yaw_predicted = torch.sum(yaw_predicted * idx_tensor, 1).cpu() * 3 - 99
+ pitch_predicted = torch.sum(pitch_predicted * idx_tensor, 1).cpu() * 3 - 99
+ roll_predicted = torch.sum(roll_predicted * idx_tensor, 1).cpu() * 3 - 99
# Mean absolute error
yaw_error += torch.sum(torch.abs(yaw_predicted - label_yaw))
--
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