voc_annotation.py

import xml.etree.ElementTree as ET

import pickle

import os

from os import listdir, getcwd

from os.path import join

sets = ['train', 'test', 'val']

classes = ["aircraft"]  # 我们只是检测细胞，因此只有一个类别


def convert(size, box):
    dw = 1. / size[0]

    dh = 1. / size[1]

    x = (box[0] + box[1]) / 2.0

    y = (box[2] + box[3]) / 2.0

    w = box[1] - box[0]

    h = box[3] - box[2]

    x = x * dw

    w = w * dw

    y = y * dh

    h = h * dh

    return (x, y, w, h)


def convert_annotation(image_id):
    in_file = open('data/Annotations/xml/%s.xml' % (image_id))

    out_file = open('data/labels/%s.txt' % (image_id), 'w')

    tree = ET.parse(in_file)

    root = tree.getroot()

    size = root.find('size')

    w = int(size.find('width').text)

    h = int(size.find('height').text)

    for obj in root.iter('object'):

        difficult = obj.find('difficult').text

        cls = obj.find('name').text

        if cls not in classes or int(difficult) == 1:
            continue

        cls_id = classes.index(cls)

        xmlbox = obj.find('bndbox')

        b = (float(xmlbox.find('xmin').text), float(xmlbox.find('xmax').text), float(xmlbox.find('ymin').text),

             float(xmlbox.find('ymax').text))

        bb = convert((w, h), b)

        out_file.write(str(cls_id) + " " + " ".join([str(a) for a in bb]) + '\n')


wd = getcwd()

print(wd)

for image_set in sets:

    if not os.path.exists('data/labels/'):
        os.makedirs('data/labels/')

    image_ids = open('data/ImageSets/Main/%s.txt' % (image_set)).read().strip().split()

    list_file = open('%s.txt' % (image_set), 'w')

    for image_id in image_ids:
        list_file.write('data/JPEGImages/%s.jpg\n' % (image_id))

        convert_annotation(image_id)

    list_file.close()