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xml2mask.py
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import xml.etree.ElementTree as ET # 读取xml。
import os, cv2
import numpy as np
from PIL import Image, ImageDraw, ImageFont
def parse_rec(filename):
if filename == 'E:\\Dataset\\detector\\last_ann\\Annotations\\30.xml':
print(" 30.xml ")
tree = ET.parse(filename) # 解析读取xml函数
objects = []
img_dir = []
for xml_name in tree.findall('filename'):
img_path = os.path.join(pic_path, xml_name.text)
img_dir.append(img_path)
for obj in tree.findall('object'):
obj_struct = {}
obj_struct['name'] = obj.find('name').text
obj_struct['pose'] = obj.find('pose').text
obj_struct['truncated'] = float(obj.find('truncated').text)
obj_struct['difficult'] = float(obj.find('difficult').text)
bbox = obj.find('bndbox')
obj_struct['bbox'] = [float(bbox.find('xmin').text),
float(bbox.find('ymin').text),
float(bbox.find('xmax').text),
float(bbox.find('ymax').text)]
objects.append(obj_struct)
return objects, img_dir
fontPath = "C:\Windows\Fonts\Consolas\consola.ttf" # 字体路径
ann_path = r'E:\Dataset\inf_voc_fuhe\VOC2007\Annotations' # xml文件所在路径
pic_path = r'E:\Dataset\inf_voc_fuhe\VOC2007\JPEGImages' # 样本图片路径
label_img_path = r'E:\Dataset\inf_Integrated\VOC\masks'
if not os.path.exists(label_img_path): # 判断是否存在文件夹如果不存在则创建为文件夹
os.makedirs(label_img_path)
font = ImageFont.truetype(fontPath, 16)
for filename in os.listdir(ann_path):
xml_path = os.path.join(ann_path, filename)
objects, img_dir = parse_rec(xml_path)
# print('img_dir:',img_dir)
for img_path in img_dir:
img = cv2.imread(img_path)
(w, h, c) = img.shape
# SIZE:PIL宽高，numpy.ndarray_img.size为 高x宽x通道数 的总个数，arry_img.shape为（高，宽，通道数）
mask = np.zeros([h, w], dtype=np.uint8)
# draw = ImageDraw.Draw(mask)
for a in objects:
xmin = int(a['bbox'][0])
ymin = int(a['bbox'][1])
xmax = int(a['bbox'][2])
ymax = int(a['bbox'][3])
label = a['name']
SAVE = cv2.rectangle(mask, (xmin, ymin), (xmax, ymax), (255, 255, 255), -1)
cv2.imwrite(label_img_path + '//' + os.path.basename(img_path), SAVE) # 写入label_img
if objects == []:
cv2.imwrite(label_img_path + '//' + os.path.basename(img_path), mask)
# # 运行单个文件
# idnum = 5
# ann_path = 'data'+str(idnum) # xml文件所在路径
# pic_path = r'D:\Research direction\data set\data'+str(idnum) # 样本图片路径
# label_img_path = r'C:\Users\11046\Desktop\mask\Newdata'+str(idnum) # 输出GT路径
# if not os.path.exists(label_img_path): # 判断是否存在文件夹如果不存在则创建为文件夹
# os.makedirs(label_img_path)
# # font = ImageFont.truetype(fontPath, 16)
#
# for filename in os.listdir(ann_path):
# xml_path = os.path.join(ann_path, filename)
# objects, img_dir = parse_rec(xml_path)
# # print('img_dir:',img_dir)
# for img_path in img_dir:
# img = cv2.imread(img_path)
# (w, h, c) = img.shape # SIZE:PIL宽高，numpy.ndarray_img.size为 高x宽x通道数 的总个数，arry_img.shape为（高，宽，通道数）
# mask = np.zeros([h, w], dtype=np.uint8)
# # draw = ImageDraw.Draw(mask)
# for a in objects:
# xmin = int(a['bbox'][0])
# ymin = int(a['bbox'][1])
# xmax = int(a['bbox'][2])
# ymax = int(a['bbox'][3])
# label = a['name']
#
# SAVE = cv2.rectangle(mask, (xmin, ymin), (xmax, ymax), (255, 255, 255), -1)
# cv2.imwrite(label_img_path + '//' + os.path.basename(img_path), SAVE) # 写入label_img