You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi,
The code for generating training and validation files is basically similar to data_gen/ntu_gendata.py. You can make it suitable for pku dataset with the reference of 'https://github.com/Levigty/AimCLR/tree/main/tools'.
Hi, The code for generating training and validation files is basically similar to data_gen/ntu_gendata.py. You can make it suitable for pku dataset with the reference of 'https://github.com/Levigty/AimCLR/tree/main/tools'.
Hello, thank you for providing the link. According to the above link you provided, I generated "train_data. npy" and "train_num_frame. npy" for PKUMMD-I. However, when I trained according to the configuration in your paper, I was unable to train successfully and the recognition accuracy did not improve. May I ask if the sizes of these two files are "3.16GB" and "147KB" respectively? Is the learning rate of your experimental configuration 0.01 and the encoder k 8192?
Hello, could you please provide the training and validation files for the PKU dataset, or the code for generating the training and validation files?
The text was updated successfully, but these errors were encountered: