物體檢測標註格式轉換-pascal voc解析

解析xml文件

import os.path as osp
import xml.etree.ElementTree as ET

import mmcv
import numpy as np

def voc_classes():
    return [
        'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat',
        'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike', 'person',
        'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor'
    ]
    
label_ids = {name: i + 1 for i, name in enumerate(voc_classes())}

def parse_xml(args):
    xml_path, img_path = args
    tree = ET.parse(xml_path)
    root = tree.getroot()
    size = root.find('size')
    w = int(size.find('width').text)
    h = int(size.find('height').text)
    bboxes = []
    labels = []
    bboxes_ignore = []
    labels_ignore = []
    for obj in root.findall('object'):
        name = obj.find('name').text
        label = label_ids[name]
        difficult = int(obj.find('difficult').text)
        bnd_box = obj.find('bndbox')
        bbox = [
            int(bnd_box.find('xmin').text),
            int(bnd_box.find('ymin').text),
            int(bnd_box.find('xmax').text),
            int(bnd_box.find('ymax').text)
        ]
        if difficult:
            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)
    annotation = {
        'filename': img_path,
        'width': w,
        'height': h,
        'ann': {
            '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 annotation

參考：mmdetection tools/convert_datasets/pascal_voc.py