basic dataset

data/dataset.py

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+import os
+import sys
+
+import math
+import torch
+import torchvision as tv
+import numpy as np
+
+from torch.utils.data import Dataset
+
+class Dataset(Dataset):
+    def __init__(self, folder):
+        self.folder = folder
+        self.transforms = tv.transforms.ToTensor()
+        self.frames = os.listdir(os.path.join(folder, 'mesh_posed'))
+
+    def __len__(self):
+        return len(self.frames)
+
+    def __getitem__(self, idx):
+        img_path = os.path.join(self.folder, 'mesh_posed', self.frames[idx])
+        image = np.load(img_path)['mesh_posed']
+        # image = self.transforms(image)
+        return image
+
+
+if __name__ == '__main__':
+    from torch.utils.data import DataLoader
+
+    dataset = Dataset('/home/workspace/local-data/train')
+    train_dataloader = DataLoader(dataset, batch_size=4, drop_last=True, num_workers=2)
+
+    for batch in train_dataloader:
+        batch
+        pass
+
+    pass