mirror of https://github.com/RE-OWOD/RE-OWOD
54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
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import logging
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import numpy as np
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from typing import Callable, List, Optional
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import torch
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from torch.utils.data.dataset import Dataset
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from detectron2.data.detection_utils import read_image
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ImageTransform = Callable[[torch.Tensor], torch.Tensor]
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class ImageListDataset(Dataset):
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"""
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Dataset that provides images from a list.
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"""
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_EMPTY_IMAGE = torch.empty((1, 1, 3))
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def __init__(self, image_list: List[str], transform: Optional[ImageTransform] = None):
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"""
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Args:
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image_list (List[str]): list of paths to image files
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"""
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self.image_list = image_list
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self.transform = transform
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def __getitem__(self, idx: int) -> torch.Tensor:
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"""
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Gets selected images from the list
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Args:
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idx (int): video index in the video list file
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Returns:
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image (torch.Tensor): tensor of size [H, W, 3]
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"""
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fpath = self.image_list[idx]
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try:
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image = torch.from_numpy(np.ascontiguousarray(read_image(fpath, format="BGR")))
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if self.transform is not None:
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image = self.transform(image.unsqueeze(0))[0] # Transforms are done on batches
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return image
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except (OSError, RuntimeError) as e:
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logger = logging.getLogger(__name__)
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logger.warning(f"Error opening image file container {fpath}: {e}")
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return self._EMPTY_IMAGE
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def __len__(self):
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return len(self.image_list)
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