mmpretrain/mmcls/datasets/voc.py

70 lines
2.4 KiB
Python

# Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import xml.etree.ElementTree as ET
import mmcv
import numpy as np
from .builder import DATASETS
from .multi_label import MultiLabelDataset
@DATASETS.register_module()
class VOC(MultiLabelDataset):
"""`Pascal VOC <http://host.robots.ox.ac.uk/pascal/VOC/>`_ Dataset."""
CLASSES = ('aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car',
'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse',
'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train',
'tvmonitor')
def __init__(self, **kwargs):
super(VOC, self).__init__(**kwargs)
if 'VOC2007' in self.data_prefix:
self.year = 2007
else:
raise ValueError('Cannot infer dataset year from img_prefix.')
def load_annotations(self):
"""Load annotations.
Returns:
list[dict]: Annotation info from XML file.
"""
data_infos = []
img_ids = mmcv.list_from_file(self.ann_file)
for img_id in img_ids:
filename = f'JPEGImages/{img_id}.jpg'
xml_path = osp.join(self.data_prefix, 'Annotations',
f'{img_id}.xml')
tree = ET.parse(xml_path)
root = tree.getroot()
labels = []
labels_difficult = []
for obj in root.findall('object'):
label_name = obj.find('name').text
# in case customized dataset has wrong labels
# or CLASSES has been override.
if label_name not in self.CLASSES:
continue
label = self.class_to_idx[label_name]
difficult = int(obj.find('difficult').text)
if difficult:
labels_difficult.append(label)
else:
labels.append(label)
gt_label = np.zeros(len(self.CLASSES))
# The order cannot be swapped for the case where multiple objects
# of the same kind exist and some are difficult.
gt_label[labels_difficult] = -1
gt_label[labels] = 1
info = dict(
img_prefix=self.data_prefix,
img_info=dict(filename=filename),
gt_label=gt_label.astype(np.int8))
data_infos.append(info)
return data_infos