Issues about DataPreprocessor when running the code about diffgesture HOT 9 CLOSED

Hi, maybe it is due to the version of the package.
Is your lmdb version 0.96?

from diffgesture.

I find that maybe it is due to the version of python, I degrad the version of python to 3.7.12 and the problem is solved and the dataset can be loaded successfully, but another problem occured, when i load the dataloader:

train_dataset = SpeechMotionDataset(args.train_data_path[0],
                                        n_poses=args.n_poses,
                                        subdivision_stride=args.subdivision_stride,
                                        pose_resampling_fps=args.motion_resampling_framerate,
                                        mean_dir_vec=mean_dir_vec,
                                        mean_pose=args.mean_pose,
                                        remove_word_timing=(args.input_context == 'text')
                                        )
    train_loader = DataLoader(dataset=train_dataset, batch_size=args.batch_size,
                              shuffle=True, drop_last=True, num_workers=args.loader_workers, pin_memory=True,
                              collate_fn=collate_fn
                              )

ValueError: num_samples should be a positive integer value, but got num_samples=0

I think this seems no longer a version problem. Can you help me fix it? thx

from diffgesture.

I find that maybe it is due to the version of python, I degrad the version of python to 3.7.12 and the problem is solved and the dataset can be loaded successfully, but another problem occured, when i load the dataloader:

train_dataset = SpeechMotionDataset(args.train_data_path[0],
                                        n_poses=args.n_poses,
                                        subdivision_stride=args.subdivision_stride,
                                        pose_resampling_fps=args.motion_resampling_framerate,
                                        mean_dir_vec=mean_dir_vec,
                                        mean_pose=args.mean_pose,
                                        remove_word_timing=(args.input_context == 'text')
                                        )
    train_loader = DataLoader(dataset=train_dataset, batch_size=args.batch_size,
                              shuffle=True, drop_last=True, num_workers=args.loader_workers, pin_memory=True,
                              collate_fn=collate_fn
                              )

ValueError: num_samples should be a positive integer value, but got num_samples=0

I think this seems no longer a version problem. Can you help me fix it? thx

And I find that when turn the argument "shuffle" to false, the problem is solved, but it is right to set "shuffle" to false?

from diffgesture.

Hi, whether using the shuffle does not change the sample number.
It is due to the wrong path I guess. Can you check your path to the data? It is required to set the data as the readme or check it correct yourself.

from diffgesture.

Hi, whether using the shuffle does not change the sample number. It is due to the wrong path I guess. Can you check your path to the data? It is required to set the data as the readme or check it correct yourself.

Hi, I have checked the datapath and it is totally right, as shown in following log:

2024-03-11 18:32:48,213: Reading data 'data/ted_expressive_dataset/train'...
2024-03-11 18:32:48,214: Found the cache data/ted_expressive_dataset/train_cache

but if I set shuffle=True, this problem will still occure, so I a bit confused.

from diffgesture.

Hi, if the structure inside that directory is correct, maybe it is because the data file is damaged. Can you try the readme again?
And, you shall manually check the num of samples when you have the shuffle=False because it does not change the file number. Or the training cannot be normal.

from diffgesture.

Thanks a lot! I will re-download the data file and try again later.

from diffgesture.

Hi, sorry to bother again. It seems like my original data file has been broken, I re-download the ted-expressive dataset and I run into this warning when I start to create train data cache, as follows:

RuntimeWarning: invalid value encountered in true_divide 
v1_u = v1 / np.linalg.norm(v1)

I wonder if it is normal and whether it will cost harm to the training process? Thank you.

from diffgesture.

Hi, I have no idea of this, and I am not sure how the data break. Maybe finish the training and check the performance first?

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