Closed young169 closed 1 year ago
Hi,
Yeah, you have to change local/classes_dict
too.
I agree it's not very intuitive we should probably change the code to make it appear in the configuration file since the dataset is there too :)
Hi, Yeah, you have to change
local/classes_dict
too. I agree it's not very intuitive we should probably change the code to make it appear in the configuration file since the dataset is there too :)
It works! But ooops, within sed_trainer/validation_step function, it gives a new error:
audio, labels, padded_indxs, filenames = batch ValueError: not enough values to unpack (expected 4, got 3)
after debug, batch is a list contains three tensors. And the filenames meaning what? Or it is because of the lack of files? I just want to classify wav files to 3 class, and only strong labeled data is available. I split the whole data to train/test set. Can this repo be used for such classification regardless the lack of unlabeled sythesised and weak labeled data?
If you don't have the filenames, it is probably because in train_sed.py you changed the validation set and forgot to mention "return_filename=True" like here: https://github.com/DCASE-REPO/DESED_task/blob/f0161eb2a6766e3479494ca5e13a208d82a9c168/recipes/dcase2022_task4_baseline/train_sed.py#L156
From
Yeah this repo can be used for that, you can change quite a lot of things because many things will be overkill for your problem. But otherwise the approach stands. I'm myself using this repo for a 4 classes problem actually.
It seems you got part of your answers @young169 , can we close this issue ?
It gives me an error like:
ValueError: Using a target size (torch.Size([24, 10, 156])) that is different to the input size (torch.Size([24, 3, 156])) is deprecated. Please ensure they have the same size.
I already change the confs/default.yaml's nclass to 3.But the target size still seems to be 10, What else I should do?