一、API,全稱Application Programming Interface,即應用程序編程接口.

API是一些預先定義函數,The purpose is to provide applications and developers with the ability to access a set of routines based on a piece of software or a piece of hardware,並且無需訪問源碼或無需理解內部工作機制細節.
API就是操作系統給應用程序的調用接口,應用程序通過調用操作系統的 API而使操作系統去執行應用程序的命令（動作）.在 Windows 中,系統API是以函數調用的方式提供的.

二、SDK和API

可以認為API是包含在SDK中的：SDK是一系列文件的組合,包括lib、dll、.h、文檔、示例等;API是對程序而言的,提供用戶編程時的接口,即一系列模塊化的類和函數.

三、python ET模塊解析xml文件

python中的xml.etree.ElementTreeModules are implemented simply and efficientlyAPI,Can be used to parse and createXML數據.

例如下面voc標注的數據,格式為xml文件：

<annotation verified="yes">
<folder>Annotation</folder>
<filename>invoice_direction_0_0.jpg</filename>
<path>invoice_stamp-PascalVOC-export/Annotations/invoice_direction_0_0.jpg</path>
<source>
<database>Unknown</database>
</source>
<size>
<width>2962</width>
<height>1753</height>
<depth>3</depth>
</size>
<segmented>0</segmented>
<object>
<name>stamp</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>1872.3010033444816</xmin>
<ymin>1216.3294491525423</ymin>
<xmax>2370.9208472686732</xmax>
<ymax>1579.474458568738</ymax>
</bndbox>
</object><object>
<name>stamp</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>1152.4392419175028</xmin>
<ymin>123.59310263653484</ymin>
<xmax>1505.7658862876256</xmax>
<ymax>351.3840630885122</ymax>
</bndbox>
</object>
</annotation>

import xml.etree.ElementTree as ET
import os
from PIL import Image, ImageDraw, ImageFont
def parse_rec(filename):
tree = ET.parse(filename) # 解析讀取xml函數
objects = []
img_dir =[]
# Element.findall()Finds elements with the specified tag in the immediate children of the current element
# Element.find()Find the first child with a specific label
# Elemtn.text 訪問元素的文本內容
# Element.get 訪問元素的屬性.
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'] = int(obj.find('truncated').text)
obj_struct['difficult'] = int(obj.find('difficult').text)
bbox = obj.find('bndbox')
obj_struct['bbox'] = [int(bbox.find('xmin').text),
int(bbox.find('ymin').text),
int(bbox.find('xmax').text),
int(bbox.find('ymax').text)]
objects.append(obj_struct)
return objects,img_dir
# Visualize the target box,並顯示標簽
def visualise_gt(objects,img_dir):
for id,img_path in enumerate(img_dir):
img = Image.open(img_path)
draw = ImageDraw.Draw(img)
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']
draw.rectangle((xmin,ymin,xmax,ymax), fill=None, outline=(0,255,0),width=2)
draw.text((xmin-10,ymin-15), label, fill = (0,255,0),font=font) # 利用ImageDraw的內置函數,在圖片上寫入文字
img.show()
fontPath = "C:\Windows\Fonts\Consolas\consola.ttf" # 字體路徑
root = 'F:/dataset/AQM'
ann_path = os.path.join(root, 'Annotations') # xml文件所在路徑
pic_path = os.path.join(root, 'JPEGImages') # Sample image path
font = ImageFont.truetype(fontPath, 16)
for filename in os.listdir(ann_path):
xml_path = os.path.join(ann_path,filename)
object,img_dir = parse_rec(xml_path)
visualise_gt(object,img_dir )

我自己在YOLOv5中解析xmlThe labels are used as follows：

xml文件：

<?xml version="1.0" encoding="utf-8"?>
<annotation>
<folder>null</folder>
<filaname>img.raw</filaname>
<path>null</path>
<size>
<width>2048</width>
<height>2048</height>
<depth>16</depth>
</size>
<imgclass>SAR</imgclass>
<condition>
<azimuth>0</azimuth>
<pitch>20</pitch>
<irazimuth>NULL</irazimuth>
<time>NULL</time>
<season>NULL</season>
<area>NULL</area>
<ceshijiao>20</ceshijiao>
<resolution>2</resolution>
<seastate>5</seastate>
<velocity>3800</velocity>
<range>630000</range>
</condition>
<object>
<name>0</name>
<bndbox>
<xmin>1006</xmin>
<xmax>1042</xmax>
<ymin>1169</ymin>
<ymax>1271</ymax>
</bndbox>
</object>
</annotation>

python解析得到左上角和右下角坐標：

# input: /images/ and single xml name
# output: img_path and list[dict[xyxy]]
def parse_rec(labelme_path, xml_file_, xml_filename):
out_file = open('%s/%s.txt' % (labelme_path, xml_file_), 'w')
tree = ET.parse(xml_filename)
objects = []
img_dir = []
for xml_name in tree.findall('filename'):
img_path = os.path.join(labelme_path, xml_name.text)
img_dir.append(img_path)
# height, width, channels = cv2.imread(imagePath).shape
width = int(tree.find('size').find('width').text)
height = int(tree.find('size').find('height').text)
for obj in tree.findall('object'):
obj_struct = {
}
obj_struct['name'] = obj.find('name').text
bbox = obj.find('bndbox')
xmin = int(bbox.find('xmin').text)
ymin = int(bbox.find('ymin').text)
xmax = int(bbox.find('xmax').text)
ymax = int(bbox.find('ymax').text)
obj_struct['bbox'] = [xmin, ymin, xmax, ymax]
# obj_struct['bbox'] = [int(bbox.find('xmin').text),
# int(bbox.find('ymin').text),
# int(bbox.find('xmax').text),
# int(bbox.find('ymax').text)]
objects.append(obj_struct)
if xmax <= xmin:
pass
elif ymax <= ymin:
pass
else:
cls_id = classes.index(label) # label name to index ID
b = (float(xmin), float(xmax), float(ymin), float(ymax))
bb = convert((width, height), b) # absolute' coordinates to relative' coordinates.
out_file.write(str(cls_id) + " " + " ".join([str(a) for a in bb]) + '\n')
print(xml_filename, xmin, ymin, xmax, ymax, cls_id)
return objects, img_dir

參考：https://blog.csdn.net/xinming_365/article/details/109039354