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## Motivation Based on the ImageNet dataset, we propose the ImageNet-S dataset has 1.2 million training images and 50k high-quality semantic segmentation annotations to support unsupervised/semi-supervised semantic segmentation on the ImageNet dataset. paper: Large-scale Unsupervised Semantic Segmentation (TPAMI 2022) [Paper link](https://arxiv.org/abs/2106.03149) ## Modification 1. Support imagenet-s dataset and its' configuration 2. Add the dataset preparation in the documentation
1005 lines
44 KiB
Python
1005 lines
44 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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import os.path as osp
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import mmcv
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import numpy as np
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from PIL import Image
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from mmseg.core import intersect_and_union
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from mmseg.datasets.pipelines import LoadAnnotations, LoadImageFromFile
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from .builder import DATASETS, PIPELINES
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from .custom import CustomDataset
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@PIPELINES.register_module()
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class LoadImageNetSImageFromFile(LoadImageFromFile):
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"""Load an image from the ImageNetS dataset.
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To avoid out of memory, images that are too large will
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be downsampled to the scale of 1000.
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Args:
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downsample_large_image (bool): Whether to downsample the large images.
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False may cause out of memory.
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Defaults to True.
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"""
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def __init__(self, downsample_large_image=True, **kwargs):
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super().__init__(**kwargs)
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self.downsample_large_image = downsample_large_image
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def __call__(self, results):
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"""Call functions to load image and get image meta information.
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Args:
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results (dict): Result dict from :obj:`mmseg.CustomDataset`.
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Returns:
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dict: The dict contains loaded image and meta information.
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"""
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results = super().__call__(results)
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if not self.downsample_large_image:
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return results
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# Images that are too large
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# (H * W > 1000 * 100,
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# these images are included in ImageNetSDataset.LARGES)
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# will be downsampled to 1000 along the longer side.
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H, W = results['img_shape'][:2]
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if H * W > pow(1000, 2):
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if H > W:
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target_size = (int(1000 * W / H), 1000)
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else:
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target_size = (1000, int(1000 * H / W))
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results['img'] = mmcv.imresize(
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results['img'], size=target_size, interpolation='bilinear')
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if self.to_float32:
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results['img'] = results['img'].astype(np.float32)
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results['img_shape'] = results['img'].shape
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results['ori_shape'] = results['img'].shape
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# Set initial values for default meta_keys
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results['pad_shape'] = results['img'].shape
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return results
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@PIPELINES.register_module()
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class LoadImageNetSAnnotations(LoadAnnotations):
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"""Load annotations for the ImageNetS dataset. The annotations in
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ImageNet-S are saved as RGB images.
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The annotations with format of RGB should be
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converted to the format of Gray as R + G * 256.
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"""
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def __call__(self, results):
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"""Call function to load multiple types annotations.
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Args:
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results (dict): Result dict from :obj:`mmseg.CustomDataset`.
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Returns:
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dict: The dict contains loaded semantic segmentation annotations.
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"""
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results = super().__call__(results)
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# The annotations in ImageNet-S are saved as RGB images,
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# due to 919 > 255 (upper bound of gray images).
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# For training,
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# the annotations with format of RGB should be
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# converted to the format of Gray as R + G * 256.
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results['gt_semantic_seg'] = \
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results['gt_semantic_seg'][:, :, 1] * 256 + \
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results['gt_semantic_seg'][:, :, 2]
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results['gt_semantic_seg'] = results['gt_semantic_seg'].astype(
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np.int32)
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return results
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@DATASETS.register_module()
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class ImageNetSDataset(CustomDataset):
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"""ImageNet-S dataset.
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In segmentation map annotation for ImageNet-S, 0 stands for others, which
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is not included in 50/300/919 categories. ``ignore_index`` is fixed to
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1000. The ``img_suffix`` is fixed to '.JPEG' and ``seg_map_suffix`` is
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fixed to '.png'.
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"""
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CLASSES50 = ('others', 'goldfish', 'tiger shark', 'goldfinch', 'tree frog',
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'kuvasz', 'red fox', 'siamese cat', 'american black bear',
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'ladybug', 'sulphur butterfly', 'wood rabbit', 'hamster',
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'wild boar', 'gibbon', 'african elephant', 'giant panda',
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'airliner', 'ashcan', 'ballpoint', 'beach wagon', 'boathouse',
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'bullet train', 'cellular telephone', 'chest', 'clog',
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'container ship', 'digital watch', 'dining table',
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'golf ball', 'grand piano', 'iron', 'lab coat', 'mixing bowl',
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'motor scooter', 'padlock', 'park bench', 'purse',
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'streetcar', 'table lamp', 'television', 'toilet seat',
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'umbrella', 'vase', 'water bottle', 'water tower', 'yawl',
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'street sign', 'lemon', 'carbonara', 'agaric')
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CLASSES300 = (
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'others', 'tench', 'goldfish', 'tiger shark', 'hammerhead',
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'electric ray', 'ostrich', 'goldfinch', 'house finch',
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'indigo bunting', 'kite', 'common newt', 'axolotl', 'tree frog',
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'tailed frog', 'mud turtle', 'banded gecko', 'american chameleon',
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'whiptail', 'african chameleon', 'komodo dragon', 'american alligator',
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'triceratops', 'thunder snake', 'ringneck snake', 'king snake',
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'rock python', 'horned viper', 'harvestman', 'scorpion',
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'garden spider', 'tick', 'african grey', 'lorikeet',
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'red-breasted merganser', 'wallaby', 'koala', 'jellyfish',
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'sea anemone', 'conch', 'fiddler crab', 'american lobster',
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'spiny lobster', 'isopod', 'bittern', 'crane', 'limpkin', 'bustard',
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'albatross', 'toy terrier', 'afghan hound', 'bluetick', 'borzoi',
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'irish wolfhound', 'whippet', 'ibizan hound', 'staffordshire '
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'bullterrier', 'border terrier', 'yorkshire terrier',
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'lakeland terrier', 'giant schnauzer', 'standard schnauzer',
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'scotch terrier', 'lhasa', 'english setter', 'clumber',
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'english springer', 'welsh springer spaniel', 'kuvasz', 'kelpie',
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'doberman', 'miniature pinscher', 'malamute', 'pug', 'leonberg',
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'great pyrenees', 'samoyed', 'brabancon griffon', 'cardigan', 'coyote',
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'red fox', 'kit fox', 'grey fox', 'persian cat', 'siamese cat',
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'cougar', 'lynx', 'tiger', 'american black bear', 'sloth bear',
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'ladybug', 'leaf beetle', 'weevil', 'bee', 'cicada', 'leafhopper',
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'damselfly', 'ringlet', 'cabbage butterfly', 'sulphur butterfly',
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'sea cucumber', 'wood rabbit', 'hare', 'hamster', 'wild boar',
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'hippopotamus', 'bighorn', 'ibex', 'badger', 'three-toed sloth',
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'orangutan', 'gibbon', 'colobus', 'spider monkey', 'squirrel monkey',
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'madagascar cat', 'indian elephant', 'african elephant', 'giant panda',
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'barracouta', 'eel', 'coho', 'academic gown', 'accordion', 'airliner',
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'ambulance', 'analog clock', 'ashcan', 'backpack', 'balloon',
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'ballpoint', 'barbell', 'barn', 'bassoon', 'bath towel', 'beach wagon',
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'bicycle-built-for-two', 'binoculars', 'boathouse', 'bonnet',
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'bookcase', 'bow', 'brass', 'breastplate', 'bullet train', 'cannon',
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'can opener', "carpenter's kit", 'cassette', 'cellular telephone',
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'chain saw', 'chest', 'china cabinet', 'clog', 'combination lock',
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'container ship', 'corkscrew', 'crate', 'crock pot', 'digital watch',
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'dining table', 'dishwasher', 'doormat', 'dutch oven', 'electric fan',
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'electric locomotive', 'envelope', 'file', 'folding chair',
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'football helmet', 'freight car', 'french horn', 'fur coat',
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'garbage truck', 'goblet', 'golf ball', 'grand piano', 'half track',
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'hamper', 'hard disc', 'harmonica', 'harvester', 'hook',
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'horizontal bar', 'horse cart', 'iron', "jack-o'-lantern", 'lab coat',
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'ladle', 'letter opener', 'liner', 'mailbox', 'megalith',
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'military uniform', 'milk can', 'mixing bowl', 'monastery', 'mortar',
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'mosquito net', 'motor scooter', 'mountain bike', 'mountain tent',
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'mousetrap', 'necklace', 'nipple', 'ocarina', 'padlock', 'palace',
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'parallel bars', 'park bench', 'pedestal', 'pencil sharpener',
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'pickelhaube', 'pillow', 'planetarium', 'plastic bag',
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'polaroid camera', 'pole', 'pot', 'purse', 'quilt', 'radiator',
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'radio', 'radio telescope', 'rain barrel', 'reflex camera',
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'refrigerator', 'rifle', 'rocking chair', 'rubber eraser', 'rule',
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'running shoe', 'sewing machine', 'shield', 'shoji', 'ski', 'ski mask',
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'slot', 'soap dispenser', 'soccer ball', 'sock', 'soup bowl',
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'space heater', 'spider web', 'spindle', 'sports car',
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'steel arch bridge', 'stethoscope', 'streetcar', 'submarine',
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'swimming trunks', 'syringe', 'table lamp', 'tank', 'teddy',
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'television', 'throne', 'tile roof', 'toilet seat', 'trench coat',
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'trimaran', 'typewriter keyboard', 'umbrella', 'vase', 'volleyball',
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'wardrobe', 'warplane', 'washer', 'water bottle', 'water tower',
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'whiskey jug', 'wig', 'wine bottle', 'wok', 'wreck', 'yawl', 'yurt',
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'street sign', 'traffic light', 'consomme', 'ice cream', 'bagel',
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'cheeseburger', 'hotdog', 'mashed potato', 'spaghetti squash',
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'bell pepper', 'cardoon', 'granny smith', 'strawberry', 'lemon',
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'carbonara', 'burrito', 'cup', 'coral reef', "yellow lady's slipper",
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'buckeye', 'agaric', 'gyromitra', 'earthstar', 'bolete')
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CLASSES919 = (
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'others', 'house finch', 'stupa', 'agaric', 'hen-of-the-woods',
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'wild boar', 'kit fox', 'desk', 'beaker', 'spindle', 'lipstick',
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'cardoon', 'ringneck snake', 'daisy', 'sturgeon', 'scorpion',
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'pelican', 'bustard', 'rock crab', 'rock beauty', 'minivan', 'menu',
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'thunder snake', 'zebra', 'partridge', 'lacewing', 'starfish',
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'italian greyhound', 'marmot', 'cardigan', 'plate', 'ballpoint',
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'chesapeake bay retriever', 'pirate', 'potpie', 'keeshond', 'dhole',
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'waffle iron', 'cab', 'american egret', 'colobus', 'radio telescope',
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'gordon setter', 'mousetrap', 'overskirt', 'hamster', 'wine bottle',
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'bluetick', 'macaque', 'bullfrog', 'junco', 'tusker', 'scuba diver',
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'pool table', 'samoyed', 'mailbox', 'purse', 'monastery', 'bathtub',
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'window screen', 'african crocodile', 'traffic light', 'tow truck',
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'radio', 'recreational vehicle', 'grey whale', 'crayfish',
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'rottweiler', 'racer', 'whistle', 'pencil box', 'barometer',
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'cabbage butterfly', 'sloth bear', 'rhinoceros beetle', 'guillotine',
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'rocking chair', 'sports car', 'bouvier des flandres', 'border collie',
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'fiddler crab', 'slot', 'go-kart', 'cocker spaniel', 'plate rack',
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'common newt', 'tile roof', 'marimba', 'moped', 'terrapin', 'oxcart',
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'lionfish', 'bassinet', 'rain barrel', 'american black bear', 'goose',
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'half track', 'kite', 'microphone', 'shield', 'mexican hairless',
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'measuring cup', 'bubble', 'platypus', 'saint bernard', 'police van',
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'vase', 'lhasa', 'wardrobe', 'teapot', 'hummingbird', 'revolver',
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'jinrikisha', 'mailbag', 'red-breasted merganser', 'assault rifle',
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'loudspeaker', 'fig', 'american lobster', 'can opener', 'arctic fox',
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'broccoli', 'long-horned beetle', 'television', 'airship',
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'black stork', 'marmoset', 'panpipe', 'drumstick', 'knee pad',
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'lotion', 'french loaf', 'throne', 'jeep', 'jersey', 'tiger cat',
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'cliff', 'sealyham terrier', 'strawberry', 'minibus', 'goldfinch',
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'goblet', 'burrito', 'harp', 'tractor', 'cornet', 'leopard', 'fly',
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'fireboat', 'bolete', 'barber chair', 'consomme', 'tripod',
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'breastplate', 'pineapple', 'wok', 'totem pole', 'alligator lizard',
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'common iguana', 'digital clock', 'bighorn', 'siamese cat', 'bobsled',
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'irish setter', 'zucchini', 'crock pot', 'loggerhead',
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'irish wolfhound', 'nipple', 'rubber eraser', 'impala', 'barbell',
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'snow leopard', 'siberian husky', 'necklace', 'manhole cover',
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'electric fan', 'hippopotamus', 'entlebucher', 'prison', 'doberman',
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'ruffed grouse', 'coyote', 'toaster', 'puffer', 'black swan',
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'schipperke', 'file', 'prairie chicken', 'hourglass',
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'greater swiss mountain dog', 'pajama', 'ear', 'pedestal', 'viaduct',
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'shoji', 'snowplow', 'puck', 'gyromitra', 'birdhouse', 'flatworm',
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'pier', 'coral reef', 'pot', 'mortar', 'polaroid camera',
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'passenger car', 'barracouta', 'banded gecko',
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'black-and-tan coonhound', 'safe', 'ski', 'torch', 'green lizard',
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'volleyball', 'brambling', 'solar dish', 'lawn mower', 'swing',
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'hyena', 'staffordshire bullterrier', 'screw', 'toilet tissue',
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'velvet', 'scale', 'stopwatch', 'sock', 'koala', 'garbage truck',
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'spider monkey', 'afghan hound', 'chain', 'upright', 'flagpole',
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'tree frog', 'cuirass', 'chest', 'groenendael', 'christmas stocking',
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'lakeland terrier', 'perfume', 'neck brace', 'lab coat', 'carbonara',
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'porcupine', 'shower curtain', 'slug', 'pitcher',
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'flat-coated retriever', 'pekinese', 'oscilloscope', 'church', 'lynx',
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'cowboy hat', 'table lamp', 'pug', 'crate', 'water buffalo',
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'labrador retriever', 'weimaraner', 'giant schnauzer', 'stove',
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'sea urchin', 'banjo', 'tiger', 'miniskirt', 'eft',
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'european gallinule', 'vending machine', 'miniature schnauzer',
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'maypole', 'bull mastiff', 'hoopskirt', 'coffeepot', 'four-poster',
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'safety pin', 'monarch', 'beer glass', 'grasshopper', 'head cabbage',
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'parking meter', 'bonnet', 'chiffonier', 'great dane', 'spider web',
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'electric locomotive', 'scotch terrier', 'australian terrier',
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'honeycomb', 'leafhopper', 'beer bottle', 'mud turtle', 'lifeboat',
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'cassette', "potter's wheel", 'oystercatcher', 'space heater',
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'coral fungus', 'sunglass', 'quail', 'triumphal arch', 'collie',
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'walker hound', 'bucket', 'bee', 'komodo dragon', 'dugong', 'gibbon',
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'trailer truck', 'king crab', 'cheetah', 'rifle', 'stingray', 'bison',
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'ipod', 'modem', 'box turtle', 'motor scooter', 'container ship',
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'vestment', 'dingo', 'radiator', 'giant panda', 'nail', 'sea slug',
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'indigo bunting', 'trimaran', 'jacamar', 'chimpanzee', 'comic book',
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'odometer', 'dishwasher', 'bolo tie', 'barn', 'paddlewheel',
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'appenzeller', 'great white shark', 'green snake', 'jackfruit',
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'llama', 'whippet', 'hay', 'leaf beetle', 'sombrero', 'ram',
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'washbasin', 'cup', 'wall clock', 'acorn squash', 'spotted salamander',
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'boston bull', 'border terrier', 'doormat', 'cicada', 'kimono',
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'hand blower', 'ox', 'meerkat', 'space shuttle', 'african hunting dog',
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'violin', 'artichoke', 'toucan', 'bulbul', 'coucal', 'red wolf',
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'seat belt', 'bicycle-built-for-two', 'bow tie', 'pretzel',
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'bedlington terrier', 'albatross', 'punching bag', 'cocktail shaker',
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'diamondback', 'corn', 'ant', 'mountain bike', 'walking stick',
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'standard schnauzer', 'power drill', 'cardigan', 'accordion',
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'wire-haired fox terrier', 'streetcar', 'beach wagon', 'ibizan hound',
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'hair spray', 'car mirror', 'mountain tent', 'trench coat',
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'studio couch', 'pomeranian', 'dough', 'corkscrew', 'broom',
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'parachute', 'band aid', 'water tower', 'teddy', 'fire engine',
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'hornbill', 'hotdog', 'theater curtain', 'crane', 'malinois', 'lion',
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'african elephant', 'handkerchief', 'caldron', 'shopping basket',
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'gown', 'wolf spider', 'vizsla', 'electric ray', 'freight car',
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'pembroke', 'feather boa', 'wallet', 'agama', 'hard disc', 'stretcher',
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'sorrel', 'trilobite', 'basset', 'vulture', 'tarantula', 'hermit crab',
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'king snake', 'robin', 'bernese mountain dog', 'ski mask',
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'fountain pen', 'combination lock', 'yurt', 'clumber', 'park bench',
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'baboon', 'kuvasz', 'centipede', 'tabby', 'steam locomotive', 'badger',
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'irish water spaniel', 'picket fence', 'gong', 'canoe',
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'swimming trunks', 'submarine', 'echidna', 'bib', 'refrigerator',
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'hammer', 'lemon', 'admiral', 'chihuahua', 'basenji', 'pinwheel',
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'golfcart', 'bullet train', 'crib', 'muzzle', 'eggnog',
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'old english sheepdog', 'tray', 'tiger beetle', 'electric guitar',
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'peacock', 'soup bowl', 'wallaby', 'abacus', 'dalmatian', 'harvester',
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'aircraft carrier', 'snowmobile', 'welsh springer spaniel',
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'affenpinscher', 'oboe', 'cassette player', 'pencil sharpener',
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'japanese spaniel', 'plunger', 'black widow', 'norfolk terrier',
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'reflex camera', 'ice bear', 'redbone', 'mongoose', 'warthog',
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'arabian camel', 'bittern', 'mixing bowl', 'tailed frog', 'scabbard',
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'castle', 'curly-coated retriever', 'garden spider', 'folding chair',
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'mouse', 'prayer rug', 'red fox', 'toy terrier', 'leonberg',
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'lycaenid', 'poncho', 'goldfish', 'red-backed sandpiper', 'holster',
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'hair slide', 'coho', 'komondor', 'macaw', 'maltese dog', 'megalith',
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'sarong', 'green mamba', 'sea lion', 'water ouzel', 'bulletproof vest',
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'sulphur-crested cockatoo', 'scottish deerhound', 'steel arch bridge',
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'catamaran', 'brittany spaniel', 'redshank', 'otter',
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'brabancon griffon', 'balloon', 'rule', 'planetarium', 'trombone',
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'mitten', 'abaya', 'crash helmet', 'milk can', 'hartebeest',
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'windsor tie', 'irish terrier', 'african chameleon', 'matchstick',
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'water bottle', 'cloak', 'ground beetle', 'ashcan', 'crane',
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'gila monster', 'unicycle', 'gazelle', 'wombat', 'brain coral',
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'projector', 'custard apple', 'proboscis monkey', 'tibetan mastiff',
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'mosque', 'plastic bag', 'backpack', 'drum', 'norwich terrier',
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'pizza', 'carton', 'plane', 'gorilla', 'jigsaw puzzle', 'forklift',
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'isopod', 'otterhound', 'vacuum', 'european fire salamander', 'apron',
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'langur', 'boxer', 'african grey', 'ice lolly', 'toilet seat',
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'golf ball', 'titi', 'drake', 'ostrich', 'magnetic compass',
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'great pyrenees', 'rhodesian ridgeback', 'buckeye', 'dungeness crab',
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'toy poodle', 'ptarmigan', 'amphibian', 'monitor', 'school bus',
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'schooner', 'spatula', 'weevil', 'speedboat', 'sundial', 'borzoi',
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'bassoon', 'bath towel', 'pill bottle', 'acorn', 'tick', 'briard',
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'thimble', 'brass', 'white wolf', 'boathouse', 'yawl',
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'miniature pinscher', 'barn spider', 'jean', 'water snake', 'dishrag',
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'yorkshire terrier', 'hammerhead', 'typewriter keyboard', 'papillon',
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'ocarina', 'washer', 'standard poodle', 'china cabinet', 'steel drum',
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'swab', 'mobile home', 'german short-haired pointer', 'saluki',
|
|
'bee eater', 'rock python', 'vine snake', 'kelpie', 'harmonica',
|
|
'military uniform', 'reel', 'thatch', 'maraca', 'tricycle',
|
|
'sidewinder', 'parallel bars', 'banana', 'flute', 'paintbrush',
|
|
'sleeping bag', "yellow lady's slipper", 'three-toed sloth',
|
|
'white stork', 'notebook', 'weasel', 'tiger shark', 'football helmet',
|
|
'madagascar cat', 'dowitcher', 'wreck', 'king penguin', 'lighter',
|
|
'timber wolf', 'racket', 'digital watch', 'liner', 'hen',
|
|
'suspension bridge', 'pillow', "carpenter's kit", 'butternut squash',
|
|
'sandal', 'sussex spaniel', 'hip', 'american staffordshire terrier',
|
|
'flamingo', 'analog clock', 'black and gold garden spider',
|
|
'sea cucumber', 'indian elephant', 'syringe', 'lens cap', 'missile',
|
|
'cougar', 'diaper', 'chambered nautilus', 'garter snake',
|
|
'anemone fish', 'organ', 'limousine', 'horse cart', 'jaguar',
|
|
'frilled lizard', 'crutch', 'sea anemone', 'guenon', 'meat loaf',
|
|
'slide rule', 'saltshaker', 'pomegranate', 'acoustic guitar',
|
|
'shopping cart', 'drilling platform', 'nematode', 'chickadee',
|
|
'academic gown', 'candle', 'norwegian elkhound', 'armadillo',
|
|
'horizontal bar', 'orangutan', 'obelisk', 'stone wall', 'cannon',
|
|
'rugby ball', 'ping-pong ball', 'window shade', 'trolleybus',
|
|
'ice cream', 'pop bottle', 'cock', 'harvestman', 'leatherback turtle',
|
|
'killer whale', 'spaghetti squash', 'chain saw', 'stinkhorn',
|
|
'espresso maker', 'loafer', 'bagel', 'ballplayer', 'skunk',
|
|
'chainlink fence', 'earthstar', 'whiptail', 'barrel',
|
|
'kerry blue terrier', 'triceratops', 'chow', 'grey fox', 'sax',
|
|
'binoculars', 'ladybug', 'silky terrier', 'gas pump', 'cradle',
|
|
'whiskey jug', 'french bulldog', 'eskimo dog', 'hog', 'hognose snake',
|
|
'pickup', 'indian cobra', 'hand-held computer', 'printer', 'pole',
|
|
'bald eagle', 'american alligator', 'dumbbell', 'umbrella', 'mink',
|
|
'shower cap', 'tank', 'quill', 'fox squirrel', 'ambulance',
|
|
'lesser panda', 'frying pan', 'letter opener', 'hook', 'strainer',
|
|
'pick', 'dragonfly', 'gar', 'piggy bank', 'envelope', 'stole', 'ibex',
|
|
'american chameleon', 'bearskin', 'microwave', 'petri dish',
|
|
'wood rabbit', 'beacon', 'dung beetle', 'warplane', 'ruddy turnstone',
|
|
'knot', 'fur coat', 'hamper', 'beagle', 'ringlet', 'mask',
|
|
'persian cat', 'cellular telephone', 'american coot', 'apiary',
|
|
'shovel', 'coffee mug', 'sewing machine', 'spoonbill', 'padlock',
|
|
'bell pepper', 'great grey owl', 'squirrel monkey',
|
|
'sulphur butterfly', 'scoreboard', 'bow', 'malamute', 'siamang',
|
|
'snail', 'remote control', 'sea snake', 'loupe', 'model t',
|
|
'english setter', 'dining table', 'face powder', 'tench',
|
|
"jack-o'-lantern", 'croquet ball', 'water jug', 'airedale', 'airliner',
|
|
'guinea pig', 'hare', 'damselfly', 'thresher', 'limpkin', 'buckle',
|
|
'english springer', 'boa constrictor', 'french horn',
|
|
'black-footed ferret', 'shetland sheepdog', 'capuchin', 'cheeseburger',
|
|
'miniature poodle', 'spotlight', 'wooden spoon',
|
|
'west highland white terrier', 'wig', 'running shoe', 'cowboy boot',
|
|
'brown bear', 'iron', 'brassiere', 'magpie', 'gondola', 'grand piano',
|
|
'granny smith', 'mashed potato', 'german shepherd', 'stethoscope',
|
|
'cauliflower', 'soccer ball', 'pay-phone', 'jellyfish', 'cairn',
|
|
'polecat', 'trifle', 'photocopier', 'shih-tzu', 'orange', 'guacamole',
|
|
'hatchet', 'cello', 'egyptian cat', 'basketball', 'moving van',
|
|
'mortarboard', 'dial telephone', 'street sign', 'oil filter', 'beaver',
|
|
'spiny lobster', 'chime', 'bookcase', 'chiton', 'black grouse', 'jay',
|
|
'axolotl', 'oxygen mask', 'cricket', 'worm fence', 'indri',
|
|
'cockroach', 'mushroom', 'dandie dinmont', 'tennis ball',
|
|
'howler monkey', 'rapeseed', 'tibetan terrier', 'newfoundland',
|
|
'dutch oven', 'paddle', 'joystick', 'golden retriever',
|
|
'blenheim spaniel', 'mantis', 'soft-coated wheaten terrier',
|
|
'little blue heron', 'convertible', 'bloodhound', 'palace',
|
|
'medicine chest', 'english foxhound', 'cleaver', 'sweatshirt',
|
|
'mosquito net', 'soap dispenser', 'ladle', 'screwdriver',
|
|
'fire screen', 'binder', 'suit', 'barrow', 'clog', 'cucumber',
|
|
'baseball', 'lorikeet', 'conch', 'quilt', 'eel', 'horned viper',
|
|
'night snake', 'angora', 'pickelhaube', 'gasmask', 'patas')
|
|
|
|
# Some too large images are downsampled in LoadImageNetSImageFromFile.
|
|
# These images should be upsampled back in results2img.
|
|
LARGES = {
|
|
'00022800': [1225, 900],
|
|
'00037230': [2082, 2522],
|
|
'00011749': [1000, 1303],
|
|
'00040173': [1280, 960],
|
|
'00027045': [1880, 1330],
|
|
'00019424': [2304, 3072],
|
|
'00015496': [1728, 2304],
|
|
'00025715': [1083, 1624],
|
|
'00008260': [1400, 1400],
|
|
'00047233': [850, 1540],
|
|
'00043667': [2066, 1635],
|
|
'00024274': [1920, 2560],
|
|
'00028437': [1920, 2560],
|
|
'00018910': [1536, 2048],
|
|
'00046074': [1600, 1164],
|
|
'00021215': [1024, 1540],
|
|
'00034174': [960, 1362],
|
|
'00007361': [960, 1280],
|
|
'00030207': [1512, 1016],
|
|
'00015637': [1600, 1200],
|
|
'00013665': [2100, 1500],
|
|
'00028501': [1200, 852],
|
|
'00047237': [1624, 1182],
|
|
'00026950': [1200, 1600],
|
|
'00041704': [1920, 2560],
|
|
'00027074': [1200, 1600],
|
|
'00016473': [1200, 1200],
|
|
'00012206': [2448, 3264],
|
|
'00019622': [960, 1280],
|
|
'00008728': [2806, 750],
|
|
'00027712': [1128, 1700],
|
|
'00007195': [1290, 1824],
|
|
'00002942': [2560, 1920],
|
|
'00037032': [1954, 2613],
|
|
'00018543': [1067, 1600],
|
|
'00041570': [1536, 2048],
|
|
'00004422': [1728, 2304],
|
|
'00044827': [800, 1280],
|
|
'00046674': [1200, 1600],
|
|
'00017711': [1200, 1600],
|
|
'00048488': [1889, 2834],
|
|
'00000706': [1501, 2001],
|
|
'00032736': [1200, 1600],
|
|
'00024348': [1536, 2048],
|
|
'00023430': [1051, 1600],
|
|
'00030496': [1350, 900],
|
|
'00026543': [1280, 960],
|
|
'00010969': [2560, 1920],
|
|
'00025272': [1294, 1559],
|
|
'00019950': [1536, 1024],
|
|
'00004466': [1182, 1722],
|
|
'00029917': [3072, 2304],
|
|
'00014683': [1145, 1600],
|
|
'00013084': [1281, 2301],
|
|
'00039792': [1760, 1034],
|
|
'00046246': [2448, 3264],
|
|
'00004280': [984, 1440],
|
|
'00009435': [1127, 1502],
|
|
'00012860': [1673, 2500],
|
|
'00016702': [1444, 1000],
|
|
'00011278': [2048, 3072],
|
|
'00048174': [1605, 2062],
|
|
'00035451': [1225, 1636],
|
|
'00024769': [1200, 900],
|
|
'00032797': [1251, 1664],
|
|
'00027924': [1453, 1697],
|
|
'00010965': [1536, 2048],
|
|
'00020735': [1200, 1600],
|
|
'00027789': [853, 1280],
|
|
'00015113': [1324, 1999],
|
|
'00037571': [1251, 1586],
|
|
'00030120': [1536, 2048],
|
|
'00044219': [2448, 3264],
|
|
'00024604': [1535, 1955],
|
|
'00010926': [1200, 900],
|
|
'00017509': [1536, 2048],
|
|
'00042373': [924, 1104],
|
|
'00037066': [1536, 2048],
|
|
'00025494': [1880, 1060],
|
|
'00028610': [1377, 2204],
|
|
'00007196': [1202, 1600],
|
|
'00030788': [2592, 1944],
|
|
'00046865': [1920, 2560],
|
|
'00027141': [1600, 1200],
|
|
'00023215': [1200, 1600],
|
|
'00000218': [1439, 1652],
|
|
'00048126': [1516, 927],
|
|
'00030408': [1600, 2400],
|
|
'00038582': [1600, 1200],
|
|
'00046959': [1304, 900],
|
|
'00016988': [1242, 1656],
|
|
'00017201': [1629, 1377],
|
|
'00017658': [1000, 1035],
|
|
'00002766': [1495, 2383],
|
|
'00038573': [1600, 1071],
|
|
'00042297': [1200, 1200],
|
|
'00010564': [995, 1234],
|
|
'00001189': [1600, 1200],
|
|
'00007018': [1858, 2370],
|
|
'00043554': [1200, 1600],
|
|
'00000746': [1200, 1600],
|
|
'00001386': [960, 1280],
|
|
'00029975': [1600, 1200],
|
|
'00016221': [2877, 2089],
|
|
'00003152': [1200, 1600],
|
|
'00002552': [1200, 1600],
|
|
'00009402': [1125, 1500],
|
|
'00040672': [960, 1280],
|
|
'00024540': [960, 1280],
|
|
'00049770': [1457, 1589],
|
|
'00014533': [841, 1261],
|
|
'00006228': [1417, 1063],
|
|
'00034688': [1354, 2032],
|
|
'00032897': [1071, 1600],
|
|
'00024356': [2043, 3066],
|
|
'00019656': [1318, 1984],
|
|
'00035802': [2288, 2001],
|
|
'00017499': [1502, 1162],
|
|
'00046898': [1200, 1600],
|
|
'00040883': [1024, 1280],
|
|
'00031353': [1544, 1188],
|
|
'00028419': [1600, 1200],
|
|
'00048897': [2304, 3072],
|
|
'00040683': [1296, 1728],
|
|
'00042406': [848, 1200],
|
|
'00036007': [900, 1200],
|
|
'00010515': [1688, 1387],
|
|
'00048409': [5005, 3646],
|
|
'00032654': [1200, 1600],
|
|
'00037955': [1200, 1600],
|
|
'00038471': [3072, 2048],
|
|
'00036201': [913, 1328],
|
|
'00038619': [1728, 2304],
|
|
'00038165': [926, 2503],
|
|
'00033240': [1061, 1158],
|
|
'00023086': [1200, 1600],
|
|
'00041385': [1200, 1600],
|
|
'00014066': [2304, 3072],
|
|
'00049973': [1211, 1261],
|
|
'00043188': [2000, 3000],
|
|
'00047186': [1535, 1417],
|
|
'00046975': [1560, 2431],
|
|
'00034402': [1776, 2700],
|
|
'00017033': [1392, 1630],
|
|
'00041068': [1280, 960],
|
|
'00011024': [1317, 900],
|
|
'00048035': [1800, 1200],
|
|
'00033286': [994, 1500],
|
|
'00016613': [1152, 1536],
|
|
'00044160': [888, 1200],
|
|
'00021138': [902, 1128],
|
|
'00022300': [798, 1293],
|
|
'00034300': [1920, 2560],
|
|
'00008603': [1661, 1160],
|
|
'00045173': [2312, 903],
|
|
'00048616': [960, 1280],
|
|
'00048317': [3872, 2592],
|
|
'00045470': [1920, 1800],
|
|
'00043934': [1667, 2500],
|
|
'00010699': [2240, 1488],
|
|
'00030550': [1200, 1600],
|
|
'00010516': [1704, 2272],
|
|
'00001779': [1536, 2048],
|
|
'00018389': [1084, 1433],
|
|
'00013889': [3072, 2304],
|
|
'00022440': [2112, 2816],
|
|
'00024005': [2592, 1944],
|
|
'00046620': [960, 1280],
|
|
'00035227': [960, 1280],
|
|
'00033636': [1110, 1973],
|
|
'00003624': [1165, 1600],
|
|
'00033400': [1200, 1600],
|
|
'00013891': [1200, 1600],
|
|
'00022593': [1472, 1456],
|
|
'00009546': [1936, 2592],
|
|
'00022022': [1182, 1740],
|
|
'00022982': [1200, 1600],
|
|
'00039569': [1600, 1067],
|
|
'00009276': [930, 1240],
|
|
'00026777': [960, 1280],
|
|
'00047680': [1425, 882],
|
|
'00040785': [853, 1280],
|
|
'00002037': [1944, 2592],
|
|
'00005813': [1098, 987],
|
|
'00018328': [1128, 1242],
|
|
'00022318': [1500, 1694],
|
|
'00026654': [790, 1285],
|
|
'00012895': [1600, 1067],
|
|
'00007882': [980, 1024],
|
|
'00043771': [1008, 1043],
|
|
'00032990': [3621, 2539],
|
|
'00034094': [1175, 1600],
|
|
'00034302': [1463, 1134],
|
|
'00025021': [1503, 1520],
|
|
'00000771': [900, 1200],
|
|
'00025149': [1600, 1200],
|
|
'00005211': [1063, 1600],
|
|
'00049544': [1063, 1417],
|
|
'00025378': [1800, 2400],
|
|
'00024287': [1200, 1600],
|
|
'00013550': [2448, 3264],
|
|
'00008076': [1200, 1600],
|
|
'00039536': [1000, 1500],
|
|
'00020331': [1024, 1280],
|
|
'00002623': [1050, 1400],
|
|
'00031071': [873, 1320],
|
|
'00025266': [1024, 1536],
|
|
'00015109': [1213, 1600],
|
|
'00027390': [1200, 1600],
|
|
'00018894': [1584, 901],
|
|
'00049009': [900, 1203],
|
|
'00026671': [1201, 1601],
|
|
'00018668': [1024, 990],
|
|
'00016942': [1024, 1024],
|
|
'00046430': [1944, 3456],
|
|
'00033261': [1341, 1644],
|
|
'00017363': [2304, 2898],
|
|
'00045935': [2112, 2816],
|
|
'00027084': [900, 1200],
|
|
'00037716': [1611, 981],
|
|
'00030879': [1200, 1600],
|
|
'00027539': [1534, 1024],
|
|
'00030052': [1280, 852],
|
|
'00011015': [2808, 2060],
|
|
'00037004': [1920, 2560],
|
|
'00044012': [2240, 1680],
|
|
'00049818': [1704, 2272],
|
|
'00003541': [1200, 1600],
|
|
'00000520': [2448, 3264],
|
|
'00028331': [3264, 2448],
|
|
'00030244': [1200, 1600],
|
|
'00039079': [1600, 1200],
|
|
'00033432': [1600, 1200],
|
|
'00010533': [1200, 1600],
|
|
'00005916': [899, 1200],
|
|
'00038903': [1052, 1592],
|
|
'00025169': [1895, 850],
|
|
'00049042': [1200, 1600],
|
|
'00021828': [1280, 988],
|
|
'00013420': [3648, 2736],
|
|
'00045201': [1381, 1440],
|
|
'00021857': [776, 1296],
|
|
'00048810': [1168, 1263],
|
|
'00047860': [2592, 3888],
|
|
'00046960': [2304, 3072],
|
|
'00039357': [1200, 1600],
|
|
'00019620': [1536, 2048],
|
|
'00026710': [1944, 2592],
|
|
'00021277': [1079, 1151],
|
|
'00028387': [1128, 1585],
|
|
'00028796': [990, 1320],
|
|
'00035149': [1064, 1600],
|
|
'00020182': [1843, 1707],
|
|
'00018286': [2592, 1944],
|
|
'00035658': [1488, 1984],
|
|
'00008180': [1024, 1633],
|
|
'00018740': [1200, 1600],
|
|
'00044356': [1536, 2048],
|
|
'00038857': [1252, 1676],
|
|
'00035014': [1200, 1600],
|
|
'00044824': [1200, 1600],
|
|
'00009912': [1200, 1600],
|
|
'00014572': [2400, 1800],
|
|
'00001585': [1600, 1067],
|
|
'00047704': [1200, 1600],
|
|
'00038537': [920, 1200],
|
|
'00027941': [2200, 3000],
|
|
'00028526': [2592, 1944],
|
|
'00042353': [1280, 1024],
|
|
'00043409': [2000, 1500],
|
|
'00002209': [2592, 1944],
|
|
'00040841': [1613, 1974],
|
|
'00038889': [900, 1200],
|
|
'00046941': [1200, 1600],
|
|
'00014029': [846, 1269],
|
|
'00023091': [900, 1200],
|
|
'00036184': [877, 1350],
|
|
'00006165': [1200, 1600],
|
|
'00033991': [868, 2034],
|
|
'00035078': [1680, 2240],
|
|
'00045681': [1467, 1134],
|
|
'00043867': [1200, 1600],
|
|
'00003586': [1200, 1600],
|
|
'00039024': [1283, 2400],
|
|
'00048990': [1200, 1200],
|
|
'00044334': [960, 1280],
|
|
'00020939': [960, 1280],
|
|
'00031529': [1302, 1590],
|
|
'00014867': [2112, 2816],
|
|
'00034239': [1536, 2048],
|
|
'00031845': [1200, 1600],
|
|
'00045721': [1536, 2048],
|
|
'00025336': [1441, 1931],
|
|
'00040323': [900, 1152],
|
|
'00009133': [876, 1247],
|
|
'00033687': [2357, 3657],
|
|
'00038351': [1306, 1200],
|
|
'00022618': [1060, 1192],
|
|
'00001626': [777, 1329],
|
|
'00039137': [1071, 1600],
|
|
'00034896': [1426, 1590],
|
|
'00048502': [1187, 1837],
|
|
'00048077': [1712, 2288],
|
|
'00026239': [1200, 1600],
|
|
'00032687': [857, 1280],
|
|
'00006639': [1498, 780],
|
|
'00037738': [2112, 2816],
|
|
'00035760': [1123, 1447],
|
|
'00004897': [1083, 1393],
|
|
'00012141': [3584, 2016],
|
|
'00016278': [3234, 2281],
|
|
'00006661': [1787, 3276],
|
|
'00033040': [1200, 1800],
|
|
'00009881': [960, 1280],
|
|
'00008240': [2592, 1944],
|
|
'00023506': [960, 1280],
|
|
'00046982': [1693, 2480],
|
|
'00049632': [2310, 1638],
|
|
'00005473': [960, 1280],
|
|
'00013491': [2000, 3008],
|
|
'00005581': [1593, 1200],
|
|
'00005196': [1417, 2133],
|
|
'00049433': [1207, 1600],
|
|
'00012323': [1200, 1800],
|
|
'00021883': [1600, 2400],
|
|
'00031877': [2448, 3264],
|
|
'00046428': [1200, 1600],
|
|
'00000725': [881, 1463],
|
|
'00044936': [894, 1344],
|
|
'00012054': [3040, 4048],
|
|
'00025447': [900, 1200],
|
|
'00005290': [1520, 2272],
|
|
'00023326': [984, 1312],
|
|
'00047891': [1067, 1600],
|
|
'00026115': [1067, 1600],
|
|
'00010051': [1062, 1275],
|
|
'00005999': [1123, 1600],
|
|
'00021752': [1071, 1600],
|
|
'00041559': [1200, 1600],
|
|
'00025931': [836, 1410],
|
|
'00009327': [2848, 4288],
|
|
'00029735': [1905, 1373],
|
|
'00012922': [1024, 1547],
|
|
'00042259': [1548, 1024],
|
|
'00024949': [1050, 956],
|
|
'00014669': [900, 1200],
|
|
'00028028': [1170, 1730],
|
|
'00003183': [1152, 1535],
|
|
'00039304': [1050, 1680],
|
|
'00014939': [1904, 1240],
|
|
'00048366': [1600, 1200],
|
|
'00022406': [3264, 2448],
|
|
'00033363': [1125, 1500],
|
|
'00041230': [1125, 1500],
|
|
'00044222': [2105, 2472],
|
|
'00021950': [1200, 1200],
|
|
'00028475': [2691, 3515],
|
|
'00002149': [900, 1600],
|
|
'00033356': [1080, 1920],
|
|
'00041158': [960, 1280],
|
|
'00029672': [1536, 2048],
|
|
'00045816': [1023, 1153],
|
|
'00020471': [2076, 2716],
|
|
'00012398': [1067, 1600],
|
|
'00017884': [2048, 3072],
|
|
'00025132': [1200, 1600],
|
|
'00042429': [1362, 1980],
|
|
'00021285': [1127, 1200],
|
|
'00045113': [2792, 2528],
|
|
'00047915': [1200, 891],
|
|
'00009481': [1097, 924],
|
|
'00025448': [1760, 2400],
|
|
'00033911': [1759, 2197],
|
|
'00044684': [1200, 1600],
|
|
'00033754': [2304, 1728],
|
|
'00002733': [1536, 2048],
|
|
'00027371': [936, 1128],
|
|
'00019941': [685, 1591],
|
|
'00028479': [1944, 2592],
|
|
'00018451': [1028, 1028],
|
|
'00024067': [1000, 1352],
|
|
'00016524': [1704, 2272],
|
|
'00048926': [1944, 2592],
|
|
'00020992': [1024, 1280],
|
|
'00044576': [1024, 1280],
|
|
'00031796': [960, 1280],
|
|
'00043540': [2448, 3264],
|
|
'00049250': [1056, 1408],
|
|
'00030602': [2592, 3872],
|
|
'00046571': [1118, 1336],
|
|
'00024908': [1442, 1012],
|
|
'00018903': [3072, 2304],
|
|
'00032370': [1944, 2592],
|
|
'00043445': [1050, 1680],
|
|
'00030791': [2228, 3168],
|
|
'00046866': [2057, 3072],
|
|
'00047293': [1800, 2400],
|
|
'00024853': [1296, 1936],
|
|
'00014344': [1125, 1500],
|
|
'00041327': [960, 1280],
|
|
'00017867': [2592, 3872],
|
|
'00037615': [1664, 2496],
|
|
'00011247': [1605, 2934],
|
|
'00034664': [2304, 1728],
|
|
'00013733': [1024, 1280],
|
|
'00009125': [1200, 1600],
|
|
'00035163': [1654, 1233],
|
|
'00017537': [1200, 1600],
|
|
'00043423': [1536, 2048],
|
|
'00035755': [1154, 900],
|
|
'00021712': [1600, 1200],
|
|
'00000597': [2792, 1908],
|
|
'00033579': [882, 1181],
|
|
'00035830': [2112, 2816],
|
|
'00005917': [920, 1380],
|
|
'00029722': [2736, 3648],
|
|
'00039979': [1200, 1600],
|
|
'00040854': [1606, 2400],
|
|
'00039884': [2848, 4288],
|
|
'00003508': [1128, 1488],
|
|
'00019862': [1200, 1600],
|
|
'00041813': [1226, 1160],
|
|
'00007121': [985, 1072],
|
|
'00013315': [883, 1199],
|
|
'00049822': [922, 1382],
|
|
'00027622': [1434, 1680],
|
|
'00047689': [1536, 2048],
|
|
'00017415': [1491, 2283],
|
|
'00023713': [927, 1287],
|
|
'00001632': [1200, 1600],
|
|
'00033104': [1200, 1600],
|
|
'00017643': [1002, 1200],
|
|
'00038396': [1330, 1999],
|
|
'00027614': [2166, 2048],
|
|
'00025962': [1600, 1200],
|
|
'00015915': [1067, 1600],
|
|
'00008940': [1942, 2744],
|
|
'00012468': [2000, 2000],
|
|
'00046953': [828, 1442],
|
|
'00002084': [1067, 1600],
|
|
'00040245': [2657, 1898],
|
|
'00023718': [900, 1440],
|
|
'00022770': [924, 1280],
|
|
'00028957': [960, 1280],
|
|
'00001054': [2048, 3072],
|
|
'00040541': [1369, 1809],
|
|
'00024869': [960, 1280],
|
|
'00037655': [900, 1440],
|
|
'00037200': [2171, 2575],
|
|
'00037390': [1394, 1237],
|
|
'00025318': [1054, 1024],
|
|
'00021634': [1800, 2400],
|
|
'00044217': [1003, 1024],
|
|
'00014877': [1200, 1600],
|
|
'00029504': [1224, 1632],
|
|
'00016422': [960, 1280],
|
|
'00028015': [1944, 2592],
|
|
'00006235': [967, 1291],
|
|
'00045909': [2272, 1704]
|
|
}
|
|
|
|
def __init__(self, subset=919, **kwargs):
|
|
|
|
assert subset in (50, 300, 919), \
|
|
'ImageNet-S has three subsets, i.e., '\
|
|
'ImageNet-S50, ImageNet-S300 and ImageNet-S919.'
|
|
if subset == 50:
|
|
self.CLASSES = self.CLASSES50
|
|
elif subset == 300:
|
|
self.CLASSES = self.CLASSES300
|
|
else:
|
|
self.CLASSES = self.CLASSES919
|
|
|
|
super(ImageNetSDataset, self).__init__(
|
|
img_suffix='.JPEG',
|
|
seg_map_suffix='.png',
|
|
reduce_zero_label=False,
|
|
ignore_index=1000,
|
|
**kwargs)
|
|
|
|
self.subset = subset
|
|
gt_seg_map_loader_cfg = kwargs.get('gt_seg_map_loader_cfg', None)
|
|
self.gt_seg_map_loader = LoadImageNetSAnnotations(
|
|
) if gt_seg_map_loader_cfg is None else LoadImageNetSAnnotations(
|
|
**gt_seg_map_loader_cfg)
|
|
|
|
def pre_eval(self, preds, indices):
|
|
"""Collect eval result for ImageNet-S. In LoadImageNetSImageFromFile,
|
|
the too large images have been downsampled. Here the preds should be
|
|
upsampled back after argmax.
|
|
|
|
Args:
|
|
preds (list[torch.Tensor] | torch.Tensor): the segmentation logit
|
|
after argmax, shape (N, H, W).
|
|
indices (list[int] | int): the prediction related ground truth
|
|
indices.
|
|
|
|
Returns:
|
|
list[torch.Tensor]: (area_intersect, area_union, area_prediction,
|
|
area_ground_truth).
|
|
"""
|
|
# In order to compat with batch inference
|
|
if not isinstance(indices, list):
|
|
indices = [indices]
|
|
if not isinstance(preds, list):
|
|
preds = [preds]
|
|
|
|
pre_eval_results = []
|
|
|
|
for pred, index in zip(preds, indices):
|
|
seg_map = self.get_gt_seg_map_by_idx(index)
|
|
pred = mmcv.imresize(
|
|
pred,
|
|
size=(seg_map.shape[1], seg_map.shape[0]),
|
|
interpolation='nearest')
|
|
pre_eval_results.append(
|
|
intersect_and_union(
|
|
pred,
|
|
seg_map,
|
|
len(self.CLASSES),
|
|
self.ignore_index,
|
|
# as the labels has been converted when dataset initialized
|
|
# in `get_palette_for_custom_classes ` this `label_map`
|
|
# should be `dict()`, see
|
|
# https://github.com/open-mmlab/mmsegmentation/issues/1415
|
|
# for more ditails
|
|
label_map=dict(),
|
|
reduce_zero_label=self.reduce_zero_label))
|
|
|
|
return pre_eval_results
|
|
|
|
def results2img(self, results, imgfile_prefix, to_label_id, indices=None):
|
|
"""Write the segmentation results to images for ImageNetS. The results
|
|
should be converted as RGB images due to 919 (>256) categroies. In
|
|
LoadImageNetSImageFromFile, the too large images have been downsampled.
|
|
Here the results should be upsampled back after argmax.
|
|
|
|
Args:
|
|
results (list[ndarray]): Testing results of the
|
|
dataset.
|
|
imgfile_prefix (str): The filename prefix of the png files.
|
|
If the prefix is "somepath/xxx",
|
|
the png files will be named "somepath/xxx.png".
|
|
to_label_id (bool): whether convert output to label_id for
|
|
submission.
|
|
indices (list[int], optional): Indices of input results, if not
|
|
set, all the indices of the dataset will be used.
|
|
Default: None.
|
|
|
|
Returns:
|
|
list[str: str]: result txt files which contains corresponding
|
|
semantic segmentation images.
|
|
"""
|
|
if indices is None:
|
|
indices = list(range(len(self)))
|
|
|
|
result_files = []
|
|
for result, idx in zip(results, indices):
|
|
|
|
filename = self.img_infos[idx]['filename']
|
|
|
|
directory = filename.split('/')[-2]
|
|
basename = osp.splitext(osp.basename(filename))[0]
|
|
|
|
png_filename = osp.join(imgfile_prefix, directory,
|
|
f'{basename}.png')
|
|
|
|
# The index range of output is from 0 to 919/300/50.
|
|
result_rgb = np.zeros(shape=(result.shape[0], result.shape[1], 3))
|
|
result_rgb[:, :, 0] = result % 256
|
|
result_rgb[:, :, 1] = result // 256
|
|
|
|
if basename.split('_')[2] in self.LARGES.keys():
|
|
result_rgb = mmcv.imresize(
|
|
result_rgb,
|
|
size=(self.LARGES[basename.split('_')[2]][1],
|
|
self.LARGES[basename.split('_')[2]][0]),
|
|
interpolation='nearest')
|
|
|
|
mmcv.mkdir_or_exist(osp.join(imgfile_prefix, directory))
|
|
output = Image.fromarray(result_rgb.astype(np.uint8))
|
|
output.save(png_filename)
|
|
result_files.append(png_filename)
|
|
|
|
return result_files
|
|
|
|
def format_results(self,
|
|
results,
|
|
imgfile_prefix,
|
|
to_label_id=True,
|
|
indices=None):
|
|
"""Format the results into dir (standard format for ImageNetS
|
|
evaluation).
|
|
|
|
Args:
|
|
results (list): Testing results of the dataset.
|
|
imgfile_prefix (str | None): The prefix of images files. It
|
|
includes the file path and the prefix of filename, e.g.,
|
|
"a/b/prefix".
|
|
to_label_id (bool): whether convert output to label_id for
|
|
submission. Default: False
|
|
indices (list[int], optional): Indices of input results, if not
|
|
set, all the indices of the dataset will be used.
|
|
Default: None.
|
|
|
|
Returns:
|
|
tuple: (result_files, tmp_dir), result_files is a list containing
|
|
the image paths, tmp_dir is the temporal directory created
|
|
for saving json/png files when img_prefix is not specified.
|
|
"""
|
|
|
|
if indices is None:
|
|
indices = list(range(len(self)))
|
|
|
|
assert isinstance(results, list), 'results must be a list.'
|
|
assert isinstance(indices, list), 'indices must be a list.'
|
|
|
|
result_files = self.results2img(results, imgfile_prefix, to_label_id,
|
|
indices)
|
|
|
|
return result_files
|