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voc_label.py
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voc_label.py
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"""
Usage:
$ python voc_label.py --path 'DataPath'
"""
# encoding=utf-8
import xml.etree.ElementTree as ET
import pickle
import os
from os import listdir, getcwd
from os.path import join
import argparse
sets = ['train', 'test', 'val']
classes = ['class_1','class2'] #define your classes
def parse_opt():
parser = argparse.ArgumentParser()
parser.add_argument('--path', type=str, default='/all_labelData', help='data path')
opt = parser.parse_args()
print(opt)
return opt
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)
opt = parse_opt()
def convert_annotation(image_id):
in_file = open(opt.path + '/Annotations/%s.xml' % (image_id), encoding='utf-8')
out_file = open(opt.path + '/labels/%s.txt' % (image_id), 'w', encoding='utf-8')
tree = ET.parse(in_file)
root = tree.getroot()
size = root.find('size')
if size != None:
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))
print(image_id, cls, b, i)
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(opt.path + '/labels/'):
os.makedirs(opt.path + '/labels/')
image_ids = open(opt.path + '/ImageSets/%s.txt' % (image_set)).read().strip().split()
list_file = open(opt.path + '/%s.txt' % (image_set), 'w')
for image_id in image_ids:
list_file.write(opt.path + '/images/%s.jpg\n' % (image_id))
convert_annotation(image_id)
list_file.close()