目录
3.实现对XML文件bounding box矩形框坐标的获取
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1.bounding box的形式1---xml文件
xml
xml文件中矩形框坐标的获取比较简单。
1.xml文件可采用标注软件labelImg进行生成
2.xml中记录了被标注图像信息和标注的信息
（1）labelImg的安装（着重说Ubuntu下的一个安装，别的版本可参照上面说到的labelImg博客）
现在就可以Terminal下打开看看了，点击Open打开一张带标记图片，如图
根据上面的英文，也都该知道怎么用，其中有些省事省力的工作，就是：
-
先给待label图片做好命名，放在同一文件夹;
-
然后设定OpenDir和待保存.xml文件夹下ChangeSaveDir;
-
如果是一个类别，可使用Use Default label，这样提高标注效率。
从图片中来，再到图片中去，我们来找一下对应关系
2.bounding box的形式1---txt文件
内容按行存储，依次是label，x_center，y_center，x_relative，y_relative
直观换算后是这样的矩形框
3.实现对XML文件bounding box矩形框坐标的获取
__author__ = "lingjun"
# E-mail: [email protected]
# 微信公众号：小白CV
# -*- coding:utf8 -*-
import os
import xml.etree.ElementTree as ET
import cv2
import numpy as np
def main(input_path):
Sum_Bndbox_Area = 0
all_N=0
xml_N=0
bndbox_N = 0
for f_1 in os.listdir(input_path):
target_path=os.path.join(input_path, f_1)
for f_2 in os.listdir(target_path):
if f_2 == "label":
doc_path = os.path.join(target_path, f_2)
#print(doc_path)
for (path, dirs, files) in os.walk(doc_path):
for filename in files:
all_N += 1
# if filename.split('_')[1]=="classes.txt":
# print(filename)
# classestxt_file_path = os.path.join(doc_path, filename)
# os.remove(classestxt_file_path)
xmin_list = []
ymin_list = []
xmax_list = []
ymax_list = []
suffix_name = filename.split('.')[1]
# print(suffix_name)
if suffix_name == 'xml':
xml_file_path = os.path.join(doc_path, filename)
xml_N += 1
#print(xml_file_path)
# 处理对应的xml文件
tree = ET.parse(xml_file_path)
root = tree.getroot()
# for name in root.iter('object'):
# label_name = name.find('name').text
for size in root.iter('size'):
width = int(size.find('width').text)
height = int(size.find('height').text)
#print("width:%.f height:%.f" % (width, height))
for box in root.iter('bndbox'):
xmin = int(box.find('xmin').text)
xmin_list.append(xmin)
ymin = int(box.find('ymin').text)
ymin_list.append(ymin)
xmax = int(box.find('xmax').text)
xmax_list.append(xmax)
ymax = int(box.find('ymax').text)
ymax_list.append(ymax)
#print("xmin:%.f ymin:%.f xmax:%.f ymax:%.f"%(xmin,ymin,xmax,ymax))
#one_bndbox_area = (ymax-ymin)*(xmax-xmin)
bndbox_N += 1
#Sum_Bndbox_Area += one_bndbox_area
#creat_label_image(xmin_list, ymin_list, xmax_list, ymax_list, 512, 512, filename)
else:
xml_file_path = os.path.join(doc_path, filename)
#print(xml_file_path)
xmin_list = []
ymin_list = []
xmax_list = []
ymax_list = []
with open(xml_file_path, "r") as f:
for line in f.readlines():
line = line.strip('\n') # 去掉列表中每一个元素的换行符
#print(line.split(" ")[0])
x_center = int(float(line.split(" ")[1])*512)
y_center = int(float(line.split(" ")[2])*512)
x_shift = int(float(line.split(" ")[3])*256)
y_shift = int(float(line.split(" ")[4])*256)
xmin=x_center-x_shift
xmax=x_center+x_shift
ymin=y_center-y_shift
ymax=y_center+y_shift
xmin_list.append(xmin)
ymin_list.append(ymin)
xmax_list.append(xmax)
ymax_list.append(ymax)
print("xmin_list[0]=",xmin_list[0])
creat_label_image( xmin_list, ymin_list, xmax_list, ymax_list,512, 512,filename)
#draw_rectangle_test(xmin_list, ymin_list, xmax_list, ymax_list, filename, xml_file_path)
Average_Bndbox_Area = Sum_Bndbox_Area/bndbox_N
print("all_N=",all_N)
print("xml_N=",xml_N)
print("bndbox_N=",bndbox_N)
print("Average_Bndbox_Area=",Average_Bndbox_Area)
4.两Bounding_Box的IOU的计算
import numpy as np
# ############################################################
# # IOU
# ############################################################
def two_Box_iou(list_a, list_b):
"""Compute the iou of two boxes.
"""
# 获取矩形框交集对应的顶点坐标(intersection)
xmin1, ymin1, xmax1, ymax1 = int(list_a[0]),int(list_a[1]), int(list_a[2]), int(list_a[3])
xmin2, ymin2, xmax2, ymax2 = int(list_b[0]),int(list_b[1]), int(list_b[2]), int(list_b[3])
xx1 = np.max([xmin1, xmin2])
yy1 = np.max([ymin1, ymin2])
xx2 = np.min([xmax1, xmax2])
yy2 = np.min([ymax1, ymax2])
# 计算两个矩形框面积
area1 = (xmax1 - xmin1 + 1) * (ymax1 - ymin1 + 1)
area2 = (xmax2 - xmin2 + 1) * (ymax2 - ymin2 + 1)
# 计算交集面积
inter_area = (np.max([0, xx2 - xx1])) * (np.max([0, yy2 - yy1]))
# 计算交并比
iou = inter_area / (area1 + area2 - inter_area + 1e-6)
return iou
#
list_a = [321,296,387,342]
list_b = [328,313,359,332]
rst_IOU = two_Box_iou(list_a, list_b)
print(rst_IOU)
