Training AFLW

natanielruiz

2017-09-15 8e5d7dbfe49d194b7d0b616307663e9a88fbcd88

 code/batch_testing.py

@@ -123,9 +123,14 @@
            label_roll = labels[:,2].float()

            pre_yaw, pre_pitch, pre_roll, angles = model(images)
            yaw = angles[args.iter_ref-1][:,0].cpu().data
            pitch = angles[args.iter_ref-1][:,1].cpu().data
            roll = angles[args.iter_ref-1][:,2].cpu().data
            yaw = angles[0][:,0].cpu().data
            pitch = angles[0][:,1].cpu().data
            roll = angles[0][:,2].cpu().data

            for idx in xrange(1,args.iter_ref+1):
                yaw += angles[idx][:,0].cpu().data
                pitch += angles[idx][:,1].cpu().data
                roll += angles[idx][:,2].cpu().data

            # Mean absolute error
            yaw_error += torch.sum(torch.abs(yaw - label_yaw) * 3)