From af51d0ecb51ad4d6c8ed086855bd3c411ebc4aa0 Mon Sep 17 00:00:00 2001
From: natanielruiz <nruiz9@gatech.edu>
Date: 星期一, 30 十月 2017 06:29:51 +0800
Subject: [PATCH] Fixed stuff
---
code/test_preangles.py | 24 ++++++++++++++----------
1 files changed, 14 insertions(+), 10 deletions(-)
diff --git a/code/test_preangles.py b/code/test_preangles.py
index 3d70bb0..05f621a 100644
--- a/code/test_preangles.py
+++ b/code/test_preangles.py
@@ -36,6 +36,13 @@
return args
+def load_filtered_state_dict(model, snapshot):
+ # By user apaszke from discuss.pytorch.org
+ model_dict = model.state_dict()
+ snapshot = {k: v for k, v in snapshot.items() if k in model_dict}
+ model_dict.update(snapshot)
+ model.load_state_dict(model_dict)
+
if __name__ == '__main__':
args = parse_args()
@@ -49,7 +56,7 @@
print 'Loading snapshot.'
# Load snapshot
saved_state_dict = torch.load(snapshot_path)
- model.load_state_dict(saved_state_dict)
+ load_filtered_state_dict(model, saved_state_dict)
print 'Loading data.'
@@ -63,6 +70,8 @@
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':
@@ -108,21 +117,16 @@
_, roll_bpred = torch.max(roll.data, 1)
# Continuous predictions
- 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
+ yaw_predicted = angles[:,0].data.cpu()
+ pitch_predicted = angles[:,1].data.cpu()
+ roll_predicted = angles[:,2].data.cpu()
# Mean absolute error
yaw_error += torch.sum(torch.abs(yaw_predicted - label_yaw))
pitch_error += torch.sum(torch.abs(pitch_predicted - label_pitch))
roll_error += torch.sum(torch.abs(roll_predicted - label_roll))
- # Save images with pose cube.
- # TODO: fix for larger batch size
+ # Save first image in batch with pose cube or axis.
if args.save_viz:
name = name[0]
if args.dataset == 'BIWI':
--
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