diff --git a/generate_bullet_wordcloud.py b/generate_bullet_wordcloud.py
deleted file mode 100644
index 2bce63d..0000000
--- a/generate_bullet_wordcloud.py
+++ /dev/null
@@ -1,68 +0,0 @@
-import collections
-import matplotlib.pyplot as plt
-from wordcloud import WordCloud
-from PIL import Image
-import numpy as np
-
-
-# 读取弹幕文件
-def read_comments(file_path):
-    with open(file_path, 'r', encoding='utf-8') as file:
-        comments = file.readlines()
-
-    # 移除每条弹幕的换行符
-    cleaned_comments = [comment.strip() for comment in comments]
-    return cleaned_comments
-
-
-# 统计词频
-def count_words(comments):
-    word_counter = collections.Counter()
-    for comment in comments:
-        words = comment.split()  # 简单分词，按空格切分词语
-        word_counter.update(words)
-    return word_counter
-
-
-# 生成词云图
-def generate_wordcloud(word_frequencies, output_file, mask_image=None):
-    wordcloud = WordCloud(
-        width=1600,  # 提高图像分辨率
-        height=800,  # 提高图像分辨率
-        background_color='white',  # 设置背景为白色
-        max_words=150,  # 减少最大词数，避免文字重叠
-        min_font_size=10,  # 确保最小字体大小不会太小
-        relative_scaling=0.5,  # 调整字体大小比例
-        colormap='cool',  # 使用冷色调配色方案
-        mask=mask_image,  # 可选：使用自定义形状的mask
-        contour_width=3,  # 设置轮廓宽度
-        contour_color='steelblue',  # 轮廓颜色
-        font_path='C:/Windows/Fonts/simhei.ttf'  # Windows下的黑体字体
-    ).generate_from_frequencies(word_frequencies)
-
-    # 显示词云图
-    plt.figure(figsize=(12, 6))  # 设置展示窗口的尺寸
-    plt.imshow(wordcloud, interpolation='bilinear')
-    plt.axis('off')  # 不显示坐标轴
-    plt.show()
-
-    # 保存词云图到文件
-    wordcloud.to_file(output_file)
-    print(f"词云图已保存至 {output_file}")
-
-
-# 主函数：读取文件、统计词频、生成词云
-file_path = '弹幕.txt'  # 弹幕文件的路径
-output_wordcloud_file = 'bullet_wordcloud.png'  # 输出的词云图文件名
-
-# 1. 读取所有弹幕
-comments = read_comments(file_path)
-
-# 2. 统计词频
-word_frequencies = count_words(comments)
-
-# 3. (可选) 使用自定义图片作为词云形状
-mask_image = None  # 如果不使用自定义形状，设为 None
-
-# 4. 生成并展示词云图
-generate_wordcloud(word_frequencies, output_wordcloud_file, mask_image)