From 1480b09fa486a8f5252e9cd601bee165e9d0cd22 Mon Sep 17 00:00:00 2001 From: natanielruiz <nruiz9@gatech.edu> Date: 星期一, 30 十月 2017 07:08:04 +0800 Subject: [PATCH] next --- code/test_preangles.py | 20 +++++++++++++++++--- 1 files changed, 17 insertions(+), 3 deletions(-) diff --git a/code/test_preangles.py b/code/test_preangles.py index be9bfda..971e54b 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() @@ -50,6 +57,7 @@ # 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 +71,8 @@ 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': @@ -108,9 +118,13 @@ _, 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)) -- Gitblit v1.8.0