import jieba from PIL import Image import numpy as np from wordcloud import WordCloud import random from utils.query import querys from utils.utils import typeList import matplotlib import re matplotlib.use('Agg') # 使用非交互式后端 import matplotlib.pyplot as plt # 评论 def getImageByComments(comments): # 调用函数，并传入要排除的关键字列表 exclude_words_pl = [] text = '' for i in comments: text = text + i['content'] # 分词 cut = jieba.cut(text) string = ' '.join(cut) # 排除指定关键字 if exclude_words_pl: for word in exclude_words_pl: string = re.sub(word, '', string) # 过滤掉长度为1的单词 filtered_string = ' '.join(word for word in string.split() if len(word) > 1) img = Image.open('./static/img/2.png') img_arr = np.array(img) wc = WordCloud( background_color='white', # mask=img_arr, # font_path=r'C:\Windows\Fonts\simsun.ttc', font_path='.\飞波正点体.otf', ) wc.generate_from_text(filtered_string) # 绘制图片 flg = plt.figure(1) plt.imshow(wc) plt.axis('off') randomInt = random.randint(1, 100000000) plt.savefig(f'./static/img/{randomInt}.png') # 关闭图形 plt.close() return f'./static/img/{randomInt}.png' # 标题 def getImageByAuthor(field, targetImage, resImage, exclude_words=None): sql = 'select {} from movie'.format(field) data = querys(sql, [], 'select') text = '' for i in data: if i[0] is not None: text = text + i[0] # 分词 cut = jieba.cut(text) string = ' '.join(cut) # 排除指定关键字 if exclude_words: for word in exclude_words: string = re.sub(word, '', string) # 过滤掉长度为1的单词 filtered_string = ' '.join(word for word in string.split() if len(word) > 1) img = Image.open(targetImage) img_arr = np.array(img) wc = WordCloud( background_color='white', # mask=img_arr, font_path='.\飞波正点体.otf', ) wc.generate_from_text(filtered_string) # 绘制图片 plt.figure(1) plt.imshow(wc, interpolation='bilinear') plt.axis('off') randomInt = random.randint(1, 100000000) plt.savefig(resImage) # 关闭图形 plt.close() # 调用函数，并传入要排除的关键字列表 exclude_words = [] getImageByAuthor('title', './static/img/2.png', './static/img/title_cloud.png', exclude_words) def getCastsDataTop(): castsList = typeList('casts') castsObj = {} for i in castsList: if castsObj.get(i, -1) == -1: castsObj[i] = 1 else: castsObj[i] = castsObj[i] + 1 castsObj = sorted(castsObj.items(), key=lambda x: x[1], reverse=True)[:100] row = [] columns = [] for i in castsObj: row.append(i[0]) columns.append(i[1]) # print(row,columns) return row, columns # 演员 # def getImageByCasts(targetImage, resImage): # # 假设getCastsDataTop20()返回演员名单和频率列表 # castsList, castsFrequency = getCastsDataTop() # # print(castsList, castsFrequency) # # 将演员名单和频率结合起来，生成一个用于生成词云的文本字符串 # text = ' '.join([name + ' ' * freq for name, freq in zip(castsList, castsFrequency)]) # # # 打开目标图片并获取其形状 # img = Image.open(targetImage) # img_arr = np.array(img) # # # 创建词云对象 # wc = WordCloud( # background_color='white', # # mask=img_arr, # font_path='STHUPO.TTF' # ) # # # 生成词云 # wc.generate_from_text(text) # # # 绘制词云图 # flg = plt.figure(1) # plt.imshow(wc) # plt.axis('off') # # # 保存词云图 # randomInt = random.randint(1, 100000000) # plt.savefig(resImage) # # # 关闭绘图 # plt.close() # 演员 def getImageByCasts(targetImage, resImage): # 假设getCastsDataTop20()返回演员名单和频率列表 castsList, castsFrequency = getCastsDataTop() # 将演员名单和频率结合起来，生成一个字典，用于生成词云 frequency_dict = {name: freq for name, freq in zip(castsList, castsFrequency)} # 打开目标图片并获取其形状 img = Image.open(targetImage) img_arr = np.array(img) # 创建词云对象 wc = WordCloud( background_color='white', # mask=img_arr, # 使用目标图片的形状作为词云的形状 font_path='.\飞波正点体.otf', max_font_size=100, # 设置最大字体大小 font_step=1, # 设置字体大小变化的步长 random_state=30, # 为字体大小和颜色的随机性设置一个种子 max_words=200 # 设置词云显示的最大单词数 ) # 生成词云 wc.generate_from_frequencies(frequency_dict) # 使用频率字典生成词云 # 绘制词云图 # plt.figure(figsize=(10, 8)) # 设置图形的大小 plt.imshow(wc, interpolation='bilinear') plt.axis('off') # 不显示坐标轴 # 保存词云图 randomInt = random.randint(1, 100000000) plt.savefig(resImage, bbox_inches=0) # 使用bbox_inches=0来确保没有额外的空白边界 # 关闭绘图 plt.close() # 调用函数生成词云图片 getImageByCasts('./static/img/2.png', './static/img/cloud_cloud.png') # getImageByAuthor('title', './static/img/1.jpg', './static/img/title_cloud.png') getImageByAuthor('summary', './static/img/2.png', './static/img/summary_cloud.png') print('生成词云图成功！') # def getImageByComments(comments): # text = '' # for i in comments: # text = text + i['content'] # # # 分词 # cut = jieba.cut(text) # string = ' '.join(cut) # # img = Image.open('./static/img/2.png') # img_arr = np.array(img) # wc = WordCloud( # background_color='white', # mask=img_arr, # font_path='STHUPO.TTF' # ) # wc.generate_from_text(string) # # # 绘制图片 # flg = plt.figure(1) # plt.imshow(wc) # plt.axis('off') # # randomInt = random.randint(1, 100000000) # plt.savefig(f'./static/img/{randomInt}.png') # return f'./static/img/{randomInt}.png' # # # def getImageByAuthor(field, targetImage, resImage): # sql = 'select {} from movie'.format(field) # data = querys(sql, [], 'select') # text = '' # for i in data: # text = text + i[0] # # # 分词 # cut = jieba.cut(text) # string = ' '.join(cut) # # img = Image.open(targetImage) # img_arr = np.array(img) # wc = WordCloud( # background_color='white', # mask=img_arr, # font_path='STHUPO.TTF' # ) # wc.generate_from_text(string) # # # 绘制图片 # flg = plt.figure(1) # plt.imshow(wc) # plt.axis('off') # # randomInt = random.randint(1, 100000000) # plt.savefig(resImage) # # # getImageByAuthor('title', './static/img/2.png', './static/img/title_cloud.png') # getImageByAuthor('summary', './static/img/2.png', './static/img/summary_cloud.png') # # # def getImageByCasts(targetImage, resImage): # castsList = typeList('casts') # text = '' # for i in castsList: # text = text + i # # # 分词 # cut = jieba.cut(text) # string = ' '.join(cut) # # img = Image.open(targetImage) # img_arr = np.array(img) # wc = WordCloud( # background_color='white', # mask=img_arr, # font_path='STHUPO.TTF' # ) # wc.generate_from_text(string) # # # 绘制图片 # flg = plt.figure(1) # plt.imshow(wc) # plt.axis('off') # # randomInt = random.randint(1, 100000000) # plt.savefig(resImage) # # # getImageByCasts('./static/img/2.png', './static/img/cloud_cloud.png')