68 lines
1.9 KiB
Python
68 lines
1.9 KiB
Python
# Copyright (c) Facebook, Inc. and its affiliates.
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# All rights reserved.
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# This source code is licensed under the license found in the
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# LICENSE file in the root directory of this source tree.
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from PIL import Image
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from typing import Any, Callable, Optional, Tuple
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import numpy as np
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import os
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import os.path
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import pickle
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import scipy.io
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from torchvision.datasets.vision import VisionDataset
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class Pets(VisionDataset):
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def __init__(
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self,
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root: str,
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train: bool = True,
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transform: Optional[Callable] = None,
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target_transform: Optional[Callable] = None,
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download: bool = False,
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) -> None:
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super(Pets, self).__init__(root, transform=transform,
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target_transform=target_transform)
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base_folder = root
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self.train = train
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annotations_path_dir = os.path.join(base_folder, "annotations")
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self.image_path_dir = os.path.join(base_folder, "images")
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if self.train:
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split_file = os.path.join(annotations_path_dir, "trainval.txt")
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with open(split_file) as f:
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self.images_list = f.readlines()
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else:
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split_file = os.path.join(annotations_path_dir, "test.txt")
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with open(split_file) as f:
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self.images_list = f.readlines()
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def __getitem__(self, index: int) -> Tuple[Any, Any]:
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img_name, label, species, _ = self.images_list[index].strip().split(" ")
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img_name += ".jpg"
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target = int(label) - 1
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img = Image.open(os.path.join(self.image_path_dir, img_name))
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img = img.convert('RGB')
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if self.transform is not None:
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img = self.transform(img)
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if self.target_transform is not None:
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target = self.target_transform(target)
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return img, target
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def __len__(self) -> int:
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return len(self.images_list)
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