I am a little bit confused about the data augmentation performed in PyTorch. Now, as far as I know, when we are performing data augmentation, we are KEEPING our original dataset,... moreI am a little bit confused about the data augmentation performed in PyTorch. Now, as far as I know, when we are performing data augmentation, we are KEEPING our original dataset, and then adding other versions of it (Flipping, Cropping...etc). But that doesn't seem like happening in PyTorch. As far as I understood from the references, when we use data.transforms in PyTorch, then it applies them one by one. So for example:
data_transforms = {
'train': transforms.Compose([
transforms.RandomResizedCrop(224),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize(, ),
'val': transforms.Compose([
transforms.Resize(256),
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize(, ),
}
Here , for the training, we are first randomly cropping the image and resizing it to shape (224,224). Then we are taking these (224,224) images and horizontally flipping them. Therefore, our dataset is now... less
I'm working on a data viz project with a team of four. We're using the same merged data sets and regularly make modifications to them (e.g. delete invalid data, make data names... moreI'm working on a data viz project with a team of four. We're using the same merged data sets and regularly make modifications to them (e.g. delete invalid data, make data names consistent, and otherwise clean the data). Does anyone know a good way we effectively can work together remotely using the same data source?
If the answer isn't Tableau, that's fine too. We're using it now, but are open to other tools.
Thank you for your help!