LingoQA dataset for pytorch
from lingoqa_dataset.lingoqa_dataset import LingoQADataset, DatasetType
import torchvision.transforms as transforms
from torch.utils.data import DataLoader
dataset = LingoQADataset(
DatasetType.EVALUATION, transforms=transforms.Resize((256, 512))
)
dataloader = DataLoader(dataset=dataset, batch_size=3, shuffle=True)
for data, question, answer in dataloader:
pass
- type: torch.Tensor
- size : torch.Size([batch_size, 3 * number_of_images, height, width])
- description : Images in the target sequences.
- type: torch.Tuple(str)
- size: batch_size
- description : Questions in the batch.
- type: torch.Tuple(str)
- size: batch_size
- description : Answers in the batch.
LingoQA project from wayve.