只需要提供文本数据以及轮廓照片即可

stopword为wordcloud自带的关键参数，可去掉不想要的文字

import jieba
from matplotlib import pyplot as plt
import wordcloud
from PIL import Image
import numpy as np

#r''单引号里面不需要转义
path = r'D:\Pycharm\.idea\frist_YF_project\Expy'

font = r'C:\Windows\Fonts\simsun.ttc'#电脑自带的字体

def tcg(texts):
    cut = jieba.cut(texts)  #分词

    string = ' '.join(cut)

    return string

text = (open(r'.\cloudtxtbad.txt','r',encoding='utf-8')).read()

string=tcg(text)

img = Image.open(r'.\cloud.png') #打开图片

img_array = np.array(img) #将图片装换为数组

stopword=['there','with','have','from',r'didn t','but','I','the','and','for','to','was','a','we','very',
          'of','it','in','is','my','they','were','not','at','had','no','that']  #设置停止词，也就是你不想显示的词

wc = wordcloud.WordCloud(
    background_color='white',
    width=1000,
    height=800,
    mask=img_array, #设置背景图片
    font_path=font,
    collocations=True,
    stopwords=stopword
)
wc.generate_from_text(string)#绘制图片

plt.imshow(wc)

plt.axis('off')

plt.show()  #显示图片

wc.to_file(r'.\beautifulcloud.png')  #保存图片