lableme标注完转分割数据集mask图的生成

import os
import json
import numpy as np
from labelme import utils
from skimage import img_as_ubyte
import matplotlib.pyplot as plt
from PIL import Image
jsondir = '.\\json'
svdir = '.\\jsonmask'


label_name_to_value = {'_background_': 0,'quexian1':1,'qiaobian2':2,'quexian2':3,'quexian2':4,'quexian2':5}
def cvtmask(jspath,svpath):
    data = json.load(open(jspath))

    imageData = data.get('imageData')
    img = utils.img_b64_to_arr(imageData)  # 原始图像


    for shape in sorted(data['shapes'], key=lambda x: x['label']):
        label_name = shape['label']
        print('label_name==',label_name)
        if label_name in label_name_to_value:
            label_value = label_name_to_value[label_name]
        else:
            label_value = len(label_name_to_value)
            label_name_to_value[label_name] = label_value

    lbl, _ = utils.shapes_to_label(img.shape, data['shapes'], label_name_to_value, type='instance')


    mask = img_as_ubyte(lbl)
    #mask = np.uint8(mask) * 255  # 掩码
    # 掩码像素值 0,1*10+100,2*10+100,3*10+100

    mask = np.uint8(mask)*10+100

    im = Image.fromarray(mask)
    im.save(svpath)
if __name__ =='__main__':
    for jsnm in os.listdir(jsondir):

        print('js==',jsnm)
        if('.json' in jsnm):
            jsonpth = os.path.join(jsondir,jsnm)
            print('jspath==',jsonpth)
            svpth = os.path.join(svdir,jsnm.replace('.json','.bmp'))
            cvtmask(jsonpth ,svpth )