import os.path as osp
import xml.etree.ElementTree as ET
import mmcv
import numpy as np
from PIL import Image
from .builder import DATASETS
from .custom import CustomDataset
[docs]@DATASETS.register_module()
class XMLDataset(CustomDataset):
"""XML dataset for detection.
Args:
min_size (int | float, optional): The minimum size of bounding
boxes in the images. If the size of a bounding box is less than
``min_size``, it would be add to ignored field.
"""
def __init__(self, min_size=None, **kwargs):
assert self.CLASSES or kwargs.get(
'classes', None), 'CLASSES in `XMLDataset` can not be None.'
super(XMLDataset, self).__init__(**kwargs)
self.cat2label = {cat: i for i, cat in enumerate(self.CLASSES)}
self.min_size = min_size
[docs] def load_annotations(self, ann_file):
"""Load annotation from XML style ann_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'JPEGImages/{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')
if size is not None:
width = int(size.find('width').text)
height = int(size.find('height').text)
else:
img_path = osp.join(self.img_prefix, 'JPEGImages',
'{}.jpg'.format(img_id))
img = Image.open(img_path)
width, height = img.size
data_infos.append(
dict(id=img_id, filename=filename, width=width, height=height))
return data_infos
def _filter_imgs(self, min_size=32):
"""Filter images too small or without annotation."""
valid_inds = []
for i, img_info in enumerate(self.data_infos):
if min(img_info['width'], img_info['height']) < min_size:
continue
if self.filter_empty_gt:
img_id = img_info['id']
xml_path = osp.join(self.img_prefix, 'Annotations',
f'{img_id}.xml')
tree = ET.parse(xml_path)
root = tree.getroot()
for obj in root.findall('object'):
name = obj.find('name').text
if name in self.CLASSES:
valid_inds.append(i)
break
else:
valid_inds.append(i)
return valid_inds
[docs] def get_ann_info(self, idx):
"""Get annotation from XML file by index.
Args:
idx (int): Index of data.
Returns:
dict: Annotation info of specified index.
"""
img_id = self.data_infos[idx]['id']
xml_path = osp.join(self.img_prefix, 'Annotations', f'{img_id}.xml')
tree = ET.parse(xml_path)
root = tree.getroot()
bboxes = []
labels = []
bboxes_ignore = []
labels_ignore = []
for obj in root.findall('object'):
name = obj.find('name').text
if name not in self.CLASSES:
continue
label = self.cat2label[name]
difficult = obj.find('difficult')
difficult = 0 if difficult is None else int(difficult.text)
bnd_box = obj.find('bndbox')
# TODO: check whether it is necessary to use int
# Coordinates may be float type
bbox = [
int(float(bnd_box.find('xmin').text)),
int(float(bnd_box.find('ymin').text)),
int(float(bnd_box.find('xmax').text)),
int(float(bnd_box.find('ymax').text))
]
ignore = False
if self.min_size:
assert not self.test_mode
w = bbox[2] - bbox[0]
h = bbox[3] - bbox[1]
if w < self.min_size or h < self.min_size:
ignore = True
if difficult or ignore:
bboxes_ignore.append(bbox)
labels_ignore.append(label)
else:
bboxes.append(bbox)
labels.append(label)
if not bboxes:
bboxes = np.zeros((0, 4))
labels = np.zeros((0, ))
else:
bboxes = np.array(bboxes, ndmin=2) - 1
labels = np.array(labels)
if not bboxes_ignore:
bboxes_ignore = np.zeros((0, 4))
labels_ignore = np.zeros((0, ))
else:
bboxes_ignore = np.array(bboxes_ignore, ndmin=2) - 1
labels_ignore = np.array(labels_ignore)
ann = dict(
bboxes=bboxes.astype(np.float32),
labels=labels.astype(np.int64),
bboxes_ignore=bboxes_ignore.astype(np.float32),
labels_ignore=labels_ignore.astype(np.int64))
return ann
[docs] def get_cat_ids(self, idx):
"""Get category ids in XML file by index.
Args:
idx (int): Index of data.
Returns:
list[int]: All categories in the image of specified index.
"""
cat_ids = []
img_id = self.data_infos[idx]['id']
xml_path = osp.join(self.img_prefix, 'Annotations', f'{img_id}.xml')
tree = ET.parse(xml_path)
root = tree.getroot()
for obj in root.findall('object'):
name = obj.find('name').text
if name not in self.CLASSES:
continue
label = self.cat2label[name]
cat_ids.append(label)
return cat_ids