python之json文件转xml python之json文件转xml文件案例讲解
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json文件格式
这是yolov4模型跑出来的检测结果result.json
下面是截取的一张图的检测结果
{
"frame_id":1, #图片的序号
"filename":"/media/wuzhou/Gap/rgb-piglet/test/00000000.jpg", #图片的路径
"objects": [ #该图中所有的目标：目标类别、目标名称、归一化的框的坐标（xywh格式）、置信度
{"class_id":0, "name":"pp", "relative_coordinates":{"center_x":0.750913, "center_y":0.402691, "width":0.038380, "height":0.193304}, "confidence":0.995435},
{"class_id":0, "name":"pp", "relative_coordinates":{"center_x":0.764775, "center_y":0.199255, "width":0.049979, "height":0.130169}, "confidence":0.994495},
{"class_id":0, "name":"pp", "relative_coordinates":{"center_x":0.560050, "center_y":0.482614, "width":0.036331, "height":0.166377}, "confidence":0.994460},
{"class_id":0, "name":"pp", "relative_coordinates":{"center_x":0.710756, "center_y":0.406446, "width":0.041782, "height":0.191297}, "confidence":0.993540},
{"class_id":0, "name":"pp", "relative_coordinates":{"center_x":0.638335, "center_y":0.238725, "width":0.107689, "height":0.092282}, "confidence":0.992926},
{"class_id":0, "name":"pp", "relative_coordinates":{"center_x":0.780232, "center_y":0.448454, "width":0.041550, "height":0.179540}, "confidence":0.990020},
{"class_id":0, "name":"pp", "relative_coordinates":{"center_x":0.563412, "center_y":0.350035, "width":0.103184, "height":0.059460}, "confidence":0.979756},
{"class_id":0, "name":"pp", "relative_coordinates":{"center_x":0.522591, "center_y":0.195170, "width":0.083014, "height":0.071478}, "confidence":0.970642},
{"class_id":0, "name":"pp", "relative_coordinates":{"center_x":0.658721, "center_y":0.154640, "width":0.103852, "height":0.055686}, "confidence":0.967082},
{"class_id":0, "name":"pp", "relative_coordinates":{"center_x":0.537660, "center_y":0.256810, "width":0.101619, "height":0.095211}, "confidence":0.918135},
{"class_id":0, "name":"pp", "relative_coordinates":{"center_x":0.528618, "center_y":0.481005, "width":0.033226, "height":0.177723}, "confidence":0.310291}
]
},
完整代码
代码需要指定图片的路径，例如 file_dir = "H:/rgb-piglet/five/test"
注意：result.json文件要跟图片放一起
代码生成的xml与图片在同一个路径下
import json
import time
import os
from PIL import Image
import cv2
import numpy as np
'''人为构造xml文件的格式'''
out0 ='''<annotation>
<folder>%(folder)s</folder>
<filename>%(name)s</filename>
<path>%(path)s</path>
<source>
<database>None</database>
</source>
<size>
<width>%(width)d</width>
<height>%(height)d</height>
<depth>3</depth>
</size>
<segmented>0</segmented>
'''
out1 = ''' <object>
<name>%(class)s</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>%(xmin)d</xmin>
<ymin>%(ymin)d</ymin>
<xmax>%(xmax)d</xmax>
<ymax>%(ymax)d</ymax>
</bndbox>
</object>
'''
out2 = '''</annotation>
'''
def read_json(json_dir):
with open(json_dir,"r") as f:
data = json.load(f)
print(type(data),len(data),type(data[0]),data[0]['frame_id'])
return data
'''txt转xml函数'''
def translate(fdir,lists):
source = {}
label = {}
data = read_json(fdir+"/result.json")
k = 0
for jpg in lists:
print(jpg)
if jpg[-4:] == '.jpg':
image= cv2.imread(jpg)#路径不能有中文
h,w,_ = image.shape #图片大小
fxml = jpg.replace('.jpg','.xml')
fxml = open(fxml, 'w');
imgfile = jpg.split('/')[-1]
source['name'] = imgfile
source['path'] = jpg
source['folder'] = os.path.basename(fdir)
source['width'] = w
source['height'] = h
fxml.write(out0 % source)
for obj in data[k]["objects"]:
label['class'] = obj["class_id"]
box = obj["relative_coordinates"]
'''把txt上的数字（归一化）转成xml上框的坐标'''
xmin = float(box["center_x"] - 0.5*box["width"])*w
ymin = float(box["center_y"] - 0.5*box["height"])*h
xmax = float(xmin + box["width"]*w)
ymax = float(ymin + box["height"]*h)
label['xmin'] = xmin
label['ymin'] = ymin
label['xmax'] = xmax
label['ymax'] = ymax
fxml.write(out1 % label)
k = k+1
fxml.write(out2)
if __name__ == '__main__':
file_dir = "H:/rgb-piglet/five/test"
lists=[]
for i in os.listdir(file_dir):
if i[-3:]=='jpg':
lists.append(file_dir+'/'+i)
#print(lists)
translate(file_dir,lists)
print('---------------Done!!!--------------')
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