41 lines
1.0 KiB
Python
41 lines
1.0 KiB
Python
import os
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import sys
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os.environ["CUDA_VISIBLE_DEVICES"] = '1'
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import math
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import torch
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import torchvision as tv
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import numpy as np
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from torch.utils.data import Dataset
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class Dataset(Dataset):
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def __init__(self, folder):
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self.folder = folder
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self.transforms = tv.transforms.ToTensor()
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self.frames = os.listdir(os.path.join(folder, 'mesh_posed'))
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def __len__(self):
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return len(self.frames)
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def __getitem__(self, idx):
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path = os.path.join(self.folder, 'mesh_posed', self.frames[idx])
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mesh_posed = np.load(path)['mesh_posed']
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# image = self.transforms(image)
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return { 'mesh_posed': mesh_posed }
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if __name__ == '__main__':
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from torch.utils.data import DataLoader
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device = "cuda" if torch.cuda.is_available() else "cpu"
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dataset = Dataset('/home/workspace/local-data/train')
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train_dataloader = DataLoader(dataset, batch_size=4, drop_last=True, num_workers=2)
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for batch in train_dataloader:
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batch
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pass
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pass |