85 lines
3.2 KiB
Python
85 lines
3.2 KiB
Python
# ------------------------------------------------------------------------
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# Deformable DETR
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# Copyright (c) 2020 SenseTime. All Rights Reserved.
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# Licensed under the Apache License, Version 2.0 [see LICENSE for details]
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# ------------------------------------------------------------------------
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# Modified from torchvision
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# ------------------------------------------------------------------------
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"""
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Copy-Paste from torchvision, but add utility of caching images on memory
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"""
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from torchvision.datasets.vision import VisionDataset
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from PIL import Image
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import os
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import os.path
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import tqdm
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from io import BytesIO
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class CocoDetection(VisionDataset):
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"""`MS Coco Detection <http://mscoco.org/dataset/#detections-challenge2016>`_ Dataset.
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Args:
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root (string): Root directory where images are downloaded to.
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annFile (string): Path to json annotation file.
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transform (callable, optional): A function/transform that takes in an PIL image
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and returns a transformed version. E.g, ``transforms.ToTensor``
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target_transform (callable, optional): A function/transform that takes in the
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target and transforms it.
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transforms (callable, optional): A function/transform that takes input sample and its target as entry
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and returns a transformed version.
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"""
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def __init__(self, root, annFile, transform=None, target_transform=None, transforms=None,
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cache_mode=False, local_rank=0, local_size=1):
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super(CocoDetection, self).__init__(root, transforms, transform, target_transform)
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from pycocotools.coco import COCO
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self.coco = COCO(annFile)
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self.ids = list(sorted(self.coco.imgs.keys()))
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self.cache_mode = cache_mode
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self.local_rank = local_rank
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self.local_size = local_size
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if cache_mode:
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self.cache = {}
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self.cache_images()
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def cache_images(self):
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self.cache = {}
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for index, img_id in zip(tqdm.trange(len(self.ids)), self.ids):
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if index % self.local_size != self.local_rank:
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continue
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path = self.coco.loadImgs(img_id)[0]['file_name']
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with open(os.path.join(self.root, path), 'rb') as f:
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self.cache[path] = f.read()
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def get_image(self, path):
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if self.cache_mode:
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if path not in self.cache.keys():
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with open(os.path.join(self.root, path), 'rb') as f:
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self.cache[path] = f.read()
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return Image.open(BytesIO(self.cache[path])).convert('RGB')
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return Image.open(os.path.join(self.root, path)).convert('RGB')
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def __getitem__(self, index):
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"""
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Args:
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index (int): Index
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Returns:
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tuple: Tuple (image, target). target is the object returned by ``coco.loadAnns``.
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"""
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coco = self.coco
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img_id = self.ids[index]
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ann_ids = coco.getAnnIds(imgIds=img_id)
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target = coco.loadAnns(ann_ids)
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path = coco.loadImgs(img_id)[0]['file_name']
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img = self.get_image(path)
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if self.transforms is not None:
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img, target = self.transforms(img, target)
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return img, target
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def __len__(self):
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return len(self.ids)
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