json2yolo

标签：box name img json json2yolo path txt

json2yolo脚本

• yolo所对应的格式是.txt,其中包含框的类别索引，中心点坐标，boundingboxs的宽，高。

import json
import os
#由x1,y1,x2,y2  ---->Cx,Cy,W,H 相对位置（取值范围0-1）
name2id = {'person':0,'mask':1}#写好自己的类别和标签
               
def convert(img_size, box):
    dw = 1./(img_size[0])#压缩到0-1之间
    dh = 1./(img_size[1])
    x = (box[0] + box[2])/2.0 - 1
    y = (box[1] + box[3])/2.0 - 1
    w = box[2] - box[0]
    h = box[3] - box[1]
    x = x*dw
    w = w*dw
    y = y*dh
    h = h*dh
    return (x,y,w,h)#返回中心点和WH
 
def decode_json(json_floder_path,json_name):
    #转换好的标签路径（转换好的放哪）
    txt_name = 'C:\\Users\\***\\AA-project\\pytorch\\PyTorch-YOLOv3\\data\\custom\\labels\\' + json_name[0:-5] + '.txt'
    txt_file = open(txt_name, 'w')
 
    json_path = os.path.join(json_floder_path, json_name)
    data = json.load(open(json_path, 'r', encoding='gb2312'))
 
    img_w = data['imageWidth']
    img_h = data['imageHeight']
 
    for i in data['shapes']:#标注文件中的
        
        label_name = i['label']#标注名称
        if (i['shape_type'] == 'rectangle'):#矩形
 
            x1 = int(i['points'][0][0])#拿到坐标
            y1 = int(i['points'][0][1])
            x2 = int(i['points'][1][0])
            y2 = int(i['points'][1][1])
 
            bb = (x1,y1,x2,y2)#组成框
            bbox = convert((img_w,img_h),bb)#转换
            txt_file.write(str(name2id[label_name]) + " " + " ".join([str(a) for a in bbox]) + '\n')
    
if __name__ == "__main__":
    #读入json路径
    json_floder_path = 'C:\\Users\\***\\AA-project\\pytorch\\PyTorch-YOLOv3\\data\\custom\\label-test'
    json_names = os.listdir(json_floder_path)
    for json_name in json_names:
        decode_json(json_floder_path,json_name)

标签：box,name,img,json,json2yolo,path,txt
From： https://www.cnblogs.com/lushuang55/p/17609455.html