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# Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import xml.etree.ElementTree as ET
import mmcv
from .builder import DATASETS
from .xml_style import XMLDataset
@DATASETS.register_module()
class WIDERFaceDataset(XMLDataset):
"""Reader for the WIDER Face dataset in PASCAL VOC format.
Conversion scripts can be found in
https://github.com/sovrasov/wider-face-pascal-voc-annotations
"""
CLASSES = ('face', )
PALETTE = [(0, 255, 0)]
def __init__(self, **kwargs):
super(WIDERFaceDataset, self).__init__(**kwargs)
def load_annotations(self, ann_file):
"""Load annotation from WIDERFace XML style annotation file.
Args:
ann_file (str): Path of XML file.
Returns:
list[dict]: Annotation info from XML file.
"""
data_infos = []
img_ids = mmcv.list_from_file(ann_file)
for img_id in img_ids:
filename = f'{img_id}.jpg'
xml_path = osp.join(self.img_prefix, 'Annotations',
f'{img_id}.xml')
tree = ET.parse(xml_path)
root = tree.getroot()
size = root.find('size')
width = int(size.find('width').text)
height = int(size.find('height').text)
folder = root.find('folder').text
data_infos.append(
dict(
id=img_id,
filename=osp.join(folder, filename),
width=width,
height=height))
return data_infos
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