Chiaraplizz

Hi :) The window size is set to 300 and temporal pooling is performed, until the final temporal dimension over the last layers is 75. What do you mean by...

Hi, You can delete the following instruction: if self.mirroring and bool(torch.bernoulli((0.5) * torch.ones(1))): since we are not using the self.mirroring attribute. Chiara

Hi :) Did you correctly set all paths? For error 2. it seems it cannot find the data you just created. As far as samples_with_missing_skeletons.txt, I am sorry I did...

Hi Zhou, Did you try to load the pre-trained models to check if everything match? Chiara

Dear Zhou, This is the configuration I used to obtain 87.3 on T-TR with X-Sub: # feeder feeder: st_gcn.feeder.Feeder feeder_augmented: st_gcn.feeder.FeederAugmented train_feeder_args: data_path: ./Output_skeletons_without_missing_skeletons/xsub/train_data_joint_bones.npy label_path: ./Output_skeletons_without_missing_skeletons/xsub/train_label_filtered.pkl random_choose: False random_shift: False...

> I also found out that even for your provided ntu60_xsub_bones_temporal.pt, there are weights of tcns included, but the sizes of the tcns do not match with your provided configuration...

> > Dear Zhou, > > This is the configuration I used to obtain 87.3 on T-TR with X-Sub: > > # feeder > > feeder: st_gcn.feeder.Feeder > > feeder_augmented:...

> when I run without bones on NTU-RGB-D, this problem has occurred as the follow picture. > Looking forward to your early reply. > >  Hi! Can you send...

Hi 😊 Which model are you loading? I noticed that you set double_channels: True. Please notice that models using joint information only have been trained with double_channels: False. Chiara