上图

你也想玩的话，可以直接上码云去看 码云链接

主方法调用

import analysisdata.WordDoingImage as WordDoingImage
import analysisdata.LetterDrawing as LetterDrawingif __name__ == '__main__':# 输入的文本，生成的动态图，没弄英文的text_str = '天生我材必有用，千金散尽还复来'#移除中文符号text_str = WordDoingImage.remove_number(text_str)# 生成汉字图片的模版WordDoingImage.main_method(text_str)# 将汉字做成散点图合成gifLetterDrawing.main_method(text_str=text_str, bg_color='#9ACD32')#清除使用完毕的图片LetterDrawing.delete_word_photo(text_str=text_str)

封装了两个类，调用起来更清晰了
散点图部分，参考了下面朋友的分析，大家可以去看看
https://blog.csdn.net/cainiao_python/article/details/117137163
下面是

LetterDrawing

的类

# *_m 代表独立方法，*_p 代表运行过程的方法
import os
import numpy as np
import matplotlib.pyplot as plt
import imageio
import random
import cv2# 跟据数据情况，转化为多个随机点
def random_point_m(text, intensity=2):# 多个随机点填充字母random.seed(420)x = []y = []for i in range(intensity):x = x + random.sample(range(0, 1000), 500)y = y + random.sample(range(0, 1000), 500)if text == ' ':return x, y# 获取图片的maskmask = cv2.imread(f'../photomodel/word/{text}.png', 0)mask = cv2.flip(mask, 0)# 检测点是否在mask中result_x = []result_y = []for i in range(len(x)):if (mask[y[i]][x[i]]) == 0:result_x.append(x[i])result_y.append(y[i])# 返回x,yreturn result_x, result_y# 将输入的文本进行切割
def split_text_m(text, repeat=True, intensity=2):print('将文本转换为数据\n')letters = []for i in text.upper():letters.append(random_point_m(i, intensity=intensity))# 如果repeat为1时,重复第一个字母if repeat:letters.append(random_point_m(text[0], intensity=intensity))return letters# 画图，生成gitdef build_git_m(coordinates_lists, gif_name, n_frames, bg_color, marker_color, marker_size, font_color):print('生成图表\n')filenames = []for index in np.arange(0, len(coordinates_lists) - 1):# 获取当前图像及下一图像的x与y轴坐标值x = coordinates_lists[index][0]y = coordinates_lists[index][1]x1 = coordinates_lists[index + 1][0]y1 = coordinates_lists[index + 1][1]# 查看两点差值while len(x) < len(x1):diff = len(x1) - len(x)x = x + x[:diff]y = y + y[:diff]while len(x1) < len(x):diff = len(x) - len(x1)x1 = x1 + x1[:diff]y1 = y1 + y1[:diff]# 计算路径x_path = np.array(x1) - np.array(x)y_path = np.array(y1) - np.array(y)for i in np.arange(0, n_frames + 1):# 计算当前位置x_temp = (x + (x_path / n_frames) * i)y_temp = (y + (y_path / n_frames) * i)# 绘制图表fig, ax = plt.subplots(figsize=(6, 6), subplot_kw=dict(aspect="equal"))ax.set_facecolor(bg_color)plt.xticks([])  # 去掉x轴plt.yticks([])  # 去掉y轴plt.axis('off')  # 去掉坐标轴plt.scatter(x_temp, y_temp, c=marker_color, s=marker_size)plt.xlim(0, 1000)plt.ylim(0, 1000)# 移除框线ax.spines['right'].set_visible(False)ax.spines['top'].set_visible(False)# 网格线ax.set_axisbelow(True)ax.yaxis.grid(color=font_color, linestyle='dashed', alpha=0.1)ax.xaxis.grid(color=font_color, linestyle='dashed', alpha=0.1)# 保存图片filename = f'../photomodel/frame_{index}_{i}.png'if (i == n_frames):for i in range(5):filenames.append(filename)filenames.append(filename)# 保存plt.savefig(filename, dpi=96, facecolor=bg_color)plt.close()print('保存图表\n')# 生成GIFprint('生成GIF\n')with imageio.get_writer(f'../photomodel/{gif_name}.gif', mode='I') as writer:for filename in filenames:image = imageio.v2.imread(filename)writer.append_data(image)print('保存GIF\n')print('删除图片\n')# 删除图片for filename in set(filenames):os.remove(filename)print('完成')passdef main_method(text_str, bg_color):coordinates_obj = split_text_m(text_str, repeat=True, intensity=50)build_git_m(coordinates_obj,gif_name=text_str[0:5],n_frames=7,bg_color=bg_color,marker_color='#000000',marker_size=0.2,font_color='#000000')passdef delete_word_photo(text_str):text_list = [text_str[i:i + 1] for i in range(0, len(text_str), 1)]for t in text_list:file_name = f'../photomodel/word/{t}.png'os.remove(file_name)pass

以下是图片生成类

WordDoingImage

，使用的词云工具，每个字生成一个图片，不用费劲的去找网络的模版图片，直接自己弄多好

# 2号词云：面朝大海，春暖花开
# B站专栏：同济子豪兄 2019-5-23import wordcloud
import multiprocessing
import re# 将生成的词云保存为output2-poem.png图片文件，保存到当前文件夹中# 将汉字生成黑底的图片
def split_text_m(text_str):"""拆分字符串通过slice语法切割字符串成单个汉字，形成一个数组:return:"""# [word_list_analysis[i:i + num] for i in range(0, len(word_list_analysis), num)]return [text_str[i:i + 1] for i in range(0, len(text_str), 1)]# 作图，根据汉字形状
def draw_image(word):# 构建词云对象w，设置词云图片宽、高、字体、背景颜色等参数,生成白底黑字的图片for w in word:file_name = f'../photomodel/word/{w}.png'w = wordcloud.WordCloud(width=1000, height=1000,background_color='white',font_path='../fontmodel/mashanzhengmaobikaishu.ttf',color_func=lambda *args, **kwargs: (0, 0, 0)).generate(w)# 调用词云对象的generate方法，将文本传入w.to_file(file_name)# 多进程处理，加快速度
def multi_process(text_list, num):pool = multiprocessing.Pool(num)# 将数组拆分为多块parts = [text_list[i:i + num] for i in range(0, len(text_list), num)]pool.map(draw_image, parts)pool.close()pass# 过滤中文符号
def remove_number(text_str):pattern = re.compile(u'[^a-zA-Z0-9\u4e00-\u9fa5]')return re.sub(pattern, '', text_str)# 主方法
def main_method(text_str):text_str = remove_number(text_str)text_list = split_text_m(text_str)multi_process(text_list, 4)

感谢各位能够看完，想玩的，欢迎大家踊跃讨论！！！！