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42 lines
1.3 KiB
Python
42 lines
1.3 KiB
Python
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from PIL import Image
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import os
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from torch.utils.data import Dataset
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import numpy as np
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class HorseZebraDataset(Dataset):
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def __init__(self, root_zebra, root_horse, transform=None):
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self.root_zebra = root_zebra
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self.root_horse = root_horse
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self.transform = transform
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self.zebra_images = os.listdir(root_zebra)
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self.horse_images = os.listdir(root_horse)
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self.length_dataset = max(len(self.zebra_images), len(self.horse_images)) # 1000, 1500
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self.zebra_len = len(self.zebra_images)
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self.horse_len = len(self.horse_images)
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def __len__(self):
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return self.length_dataset
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def __getitem__(self, index):
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zebra_img = self.zebra_images[index % self.zebra_len]
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horse_img = self.horse_images[index % self.horse_len]
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zebra_path = os.path.join(self.root_zebra, zebra_img)
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horse_path = os.path.join(self.root_horse, horse_img)
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zebra_img = np.array(Image.open(zebra_path).convert("RGB"))
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horse_img = np.array(Image.open(horse_path).convert("RGB"))
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if self.transform:
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augmentations = self.transform(image=zebra_img, image0=horse_img)
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zebra_img = augmentations["image"]
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horse_img = augmentations["image0"]
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return zebra_img, horse_img
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