| | |
| | | _, roll_bpred = torch.max(roll.data, 1) |
| | | |
| | | # Continuous predictions |
| | | yaw_predicted = utils.softmax_temperature(yaw.data, 0.85) |
| | | pitch_predicted = utils.softmax_temperature(pitch.data, 0.8) |
| | | roll_predicted = utils.softmax_temperature(roll.data, 0.8) |
| | | yaw_predicted = utils.softmax_temperature(yaw.data, 0.1) |
| | | 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 |