python labelme标注的多分类数据集转化为YOLO数据集（json转txt）

1、如何使用脚本

        （此脚本支持多分类的目标检测数据）

        1、修改dir_json为自己生成的coco数据集文件夹目录

        2、修改dir_txt为要放进去Yolo格式标签的文件夹目录

        3、直接运行代码

import os

import json

# labelme标注的json标签文件目录和保存生成的txt标签的文件夹

dir_json = r'D:/Json/'

dir_txt = r'D:/txt/'

# os.mkdir(dir_txt)

classes2id = {}

num = 0

jsons = os.listdir(dir_json)

for i in jsons:

json_path = os.path.join(dir_json, i)

with open(json_path, 'r', encoding="utf-8") as f:

json_data = json.load(f)

# print(json_data['shapes'])

for j in json_data['shapes']:

if j['label'] not in classes2id:

classes2id[j['label']] = num

num += 1

print(classes2id)

def json2txt(path_json, path_txt): # 可修改生成格式

with open(path_json, 'r', encoding='utf-8') as path_json:

jsonx = json.load(path_json)

with open(path_txt, 'w+') as ftxt:

shapes = jsonx['shapes']

# 获取图片长和宽

width = jsonx['imageWidth']

height = jsonx['imageHeight']

# print(shapes)

cat=shapes[0]['label']

cat=classes2id[cat]

for shape in shapes:

# 获取矩形框两个角点坐标

x1 = shape['points'][0][0]

y1 = shape['points'][0][1]

x2 = shape['points'][1][0]

y2 = shape['points'][1][1]

dw = 1. / width

dh = 1. / height

x = dw * (x1 + x2) / 2

y = dh * (y1 + y2) / 2

w = dw * abs(x2 - x1)

h = dh * abs(y2 - y1)

yolo = f"{cat} {x} {y} {w} {h} \n"

ftxt.writelines(yolo)

list_json = os.listdir(dir_json)

for cnt, json_name in enumerate(list_json):

if os.path.splitext(json_name)[-1] == ".json":

path_json = dir_json + json_name

path_txt = dir_txt + json_name.replace('.json', '.txt')

json2txt(path_json, path_txt)

2、实现过程

读取所有的.json文件，遍历后生成classes2id字典

classes2id={}

num=0

jsons=os.listdir(dir_json)

for i in jsons:

json_path=os.path.join(dir_json,i)

with open(json_path, 'r',encoding="utf-8") as f:

json_data = json.load(f)

#print(json_data['shapes'])

for j in json_data['shapes']:

if j['label'] not in classes2id:

classes2id[j['label']]=num

num+=1

print(classes2id)

 将.json文件转化为.txt文件

def json2txt(path_json, path_txt): # 可修改生成格式

with open(path_json, 'r', encoding='utf-8') as path_json:

jsonx = json.load(path_json)

with open(path_txt, 'w+') as ftxt:

shapes = jsonx['shapes']

# 获取图片长和宽

width = jsonx['imageWidth']

height = jsonx['imageHeight']

# print(shapes)

cat=shapes[0]['label']

cat=classes2id[cat]

for shape in shapes:

# 获取矩形框两个角点坐标

x1 = shape['points'][0][0]

y1 = shape['points'][0][1]

x2 = shape['points'][1][0]

y2 = shape['points'][1][1]

dw = 1. / width

dh = 1. / height

x = dw * (x1 + x2) / 2

y = dh * (y1 + y2) / 2

w = dw * abs(x2 - x1)

h = dh * abs(y2 - y1)

yolo = f"{cat} {x} {y} {w} {h} \n"

ftxt.writelines(yolo)

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