用Python做一个漂亮小姐姐词云跳舞视频

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前言

本文以“【欣小萌】芒种，一想到你我就……”为教程视频

图片[1]-用Python做一个漂亮小姐姐词云跳舞视频-软件开发技术分享

下载视频

参考 macOS 安装 you-get 下载视频

获取弹幕内容

导入用到的库

import requests
import pandas as pd
import re
import time
import random
from concurrent.futures import ThreadPoolExecutor
import datetime
from fake_useragent import UserAgent
# 随机产生请求头
ua = UserAgent(verify_ssl=False, path='fake_useragent.json')
start_time = datetime.datetime.now()
import requests
import pandas as pd
import re
import time
import random
from concurrent.futures import ThreadPoolExecutor
import datetime
from fake_useragent import UserAgent

# 随机产生请求头
ua = UserAgent(verify_ssl=False, path='fake_useragent.json')
start_time = datetime.datetime.now()
import requests
import pandas as pd
import re
import time
import random
from concurrent.futures import ThreadPoolExecutor
import datetime
from fake_useragent import UserAgent

# 随机产生请求头
ua = UserAgent(verify_ssl=False, path='fake_useragent.json')
start_time = datetime.datetime.now()

爬取弹幕数据

def  Grab_barrage(date):
    # 伪装请求头
    headers = {
        "sec-fetch-dest": "empty",
        "sec-fetch-mode": "cors",
        "sec-fetch-site": "same-site",
        "accept-encoding": "gzip",
        "origin": "https://www.bilibili.com",
        "referer": "https://www.bilibili.com/video/BV1sJ411P7CF",
        "user-agent": ua.random,
        "cookie": "chage to your cookies"
    }
    # 构造url访问   需要用到的参数  爬取指定日期的弹幕
    params = {
        'type': 1,
        'oid': '116963870',
        'date': date
    }
    # 发送请求  获取响应
    response = requests.get(url, params=params, headers=headers)
    # print(response.encoding)   重新设置编码
    response.encoding = 'utf-8'
    # print(response.text)
    # 正则匹配提取数据  转成集合去除重复弹幕
    comment = set(re.findall('<d p=".*?">(.*?)</d>', response.text))
    # 将每条弹幕数据写入txt
    with open('bullet.txt', 'a+') as f:
        for con in comment:
            f.write(con + '\n')
            print(con)
    time.sleep(random.randint(1, 3))   # 休眠
def  Grab_barrage(date):
    # 伪装请求头
    headers = {
        "sec-fetch-dest": "empty",
        "sec-fetch-mode": "cors",
        "sec-fetch-site": "same-site",
        "accept-encoding": "gzip",
        "origin": "https://www.bilibili.com",
        "referer": "https://www.bilibili.com/video/BV1sJ411P7CF",
        "user-agent": ua.random,
        "cookie": "chage to your cookies"
    }
    # 构造url访问   需要用到的参数  爬取指定日期的弹幕
    params = {
        'type': 1,
        'oid': '116963870',
        'date': date
    }
    # 发送请求  获取响应
    response = requests.get(url, params=params, headers=headers)
    # print(response.encoding)   重新设置编码
    response.encoding = 'utf-8'
    # print(response.text)
    # 正则匹配提取数据  转成集合去除重复弹幕
    comment = set(re.findall('<d p=".*?">(.*?)</d>', response.text))
    # 将每条弹幕数据写入txt
    with open('bullet.txt', 'a+') as f:
        for con in comment:
            f.write(con + '\n')
            print(con)
    time.sleep(random.randint(1, 3))   # 休眠
def  Grab_barrage(date):
    # 伪装请求头
    headers = {
        "sec-fetch-dest": "empty",
        "sec-fetch-mode": "cors",
        "sec-fetch-site": "same-site",
        "accept-encoding": "gzip",
        "origin": "https://www.bilibili.com",
        "referer": "https://www.bilibili.com/video/BV1sJ411P7CF",
        "user-agent": ua.random,
        "cookie": "chage to your cookies"
    }
    # 构造url访问   需要用到的参数  爬取指定日期的弹幕
    params = {
        'type': 1,
        'oid': '116963870',
        'date': date
    }
    # 发送请求  获取响应
    response = requests.get(url, params=params, headers=headers)
    # print(response.encoding)   重新设置编码
    response.encoding = 'utf-8'
    # print(response.text)
    # 正则匹配提取数据  转成集合去除重复弹幕
    comment = set(re.findall('<d p=".*?">(.*?)</d>', response.text))
    # 将每条弹幕数据写入txt
    with open('bullet.txt', 'a+') as f:
        for con in comment:
            f.write(con + '\n')
            print(con)
    time.sleep(random.randint(1, 3))   # 休眠

爬取弹幕数据

def main():
    # 开多线程爬取   提高爬取效率
    with ThreadPoolExecutor(max_workers=4) as executor:
        executor.map(Grab_barrage, date_list)
    # 计算所用时间
    delta = (datetime.datetime.now() - start_time).total_seconds()
    print(f'用时：{delta}s  -----------> 弹幕数据成功保存到本地txt')
def main():
    # 开多线程爬取   提高爬取效率
    with ThreadPoolExecutor(max_workers=4) as executor:
        executor.map(Grab_barrage, date_list)
    # 计算所用时间
    delta = (datetime.datetime.now() - start_time).total_seconds()
    print(f'用时：{delta}s  -----------> 弹幕数据成功保存到本地txt')
def main():
    # 开多线程爬取   提高爬取效率
    with ThreadPoolExecutor(max_workers=4) as executor:
        executor.map(Grab_barrage, date_list)
    # 计算所用时间
    delta = (datetime.datetime.now() - start_time).total_seconds()
    print(f'用时：{delta}s  -----------> 弹幕数据成功保存到本地txt')

主函数调用

if __name__ == '__main__':
    # 目标url
    url = "https://api.bilibili.com/x/v2/dm/history"
    start = '20201201'
    end = '20210128'
    # 生成时间序列
    date_list = [x for x in pd.date_range(start, end).strftime('%Y-%m-%d')]
    print(date_list)
    count = 0
    # 调用主函数
    main()
if __name__ == '__main__':
    # 目标url
    url = "https://api.bilibili.com/x/v2/dm/history"
    start = '20201201'
    end = '20210128'
    # 生成时间序列
    date_list = [x for x in pd.date_range(start, end).strftime('%Y-%m-%d')]
    print(date_list)
    count = 0
    # 调用主函数
    main()
if __name__ == '__main__':
    # 目标url
    url = "https://api.bilibili.com/x/v2/dm/history"
    start = '20201201'
    end = '20210128'
    # 生成时间序列
    date_list = [x for x in pd.date_range(start, end).strftime('%Y-%m-%d')]
    print(date_list)
    count = 0
    # 调用主函数
    main()

结果如下

图片[2]-用Python做一个漂亮小姐姐词云跳舞视频-软件开发技术分享

从视频中提取图片

import cv2
# ============================ 视频处理 分割成一帧帧图片 =======================================
cap = cv2.VideoCapture(r"beauty.flv")
num = 1
while True:
    # 逐帧读取视频  按顺序保存到本地文件夹
    ret, frame = cap.read()
    if ret:
        if 88 <= num < 888:
            cv2.imwrite(f"./imgs/img_{num}.jpg", frame)   # 保存一帧帧的图片
            print(f'========== 已成功保存第{num}张图片 ==========')
        num += 1
    else:
        break
cap.release()   # 释放资源
import cv2

# ============================ 视频处理 分割成一帧帧图片 =======================================
cap = cv2.VideoCapture(r"beauty.flv")
num = 1
while True:
    # 逐帧读取视频  按顺序保存到本地文件夹
    ret, frame = cap.read()
    if ret:
        if 88 <= num < 888:
            cv2.imwrite(f"./imgs/img_{num}.jpg", frame)   # 保存一帧帧的图片
            print(f'========== 已成功保存第{num}张图片 ==========')
        num += 1
    else:
        break
cap.release()   # 释放资源
import cv2

# ============================ 视频处理 分割成一帧帧图片 =======================================
cap = cv2.VideoCapture(r"beauty.flv")
num = 1
while True:
    # 逐帧读取视频  按顺序保存到本地文件夹
    ret, frame = cap.read()
    if ret:
        if 88 <= num < 888:
            cv2.imwrite(f"./imgs/img_{num}.jpg", frame)   # 保存一帧帧的图片
            print(f'========== 已成功保存第{num}张图片 ==========')
        num += 1
    else:
        break
cap.release()   # 释放资源

结果如下

图片[3]-用Python做一个漂亮小姐姐词云跳舞视频-软件开发技术分享

从视频中提取图片

利用百度AI进行人像分割

import cv2
import base64
import numpy as np
import os
from aip import AipBodyAnalysis
import time
import random
# 利用百度AI的人像分割服务 转化为二值图  有小姐姐身影的蒙版
# 百度云中已创建应用的  APP_ID API_KEY SECRET_KEY
APP_ID = '23649226'
API_KEY = '**********************'
SECRET_KEY = '**********************'
client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
# 保存图像分割后的路径
path = './mask_img/'
# os.listdir  列出保存到图片名称
img_files = os.listdir('./imgs')
print(img_files)
for num in range(88, len(img_files) + 1):
    # 按顺序构造出图片路径
    img = f'./imgs/img_{num}.jpg'
    img1 = cv2.imread(img)
    height, width, _ = img1.shape
    # print(height, width)
    # 二进制方式读取图片
    with open(img, 'rb') as fp:
        img_info = fp.read()
    # 设置只返回前景   也就是分割出来的人像
    seg_res = client.bodySeg(img_info)
    labelmap = base64.b64decode(seg_res['labelmap'])
    nparr = np.frombuffer(labelmap, np.uint8)
    labelimg = cv2.imdecode(nparr, 1)
    labelimg = cv2.resize(labelimg, (width, height), interpolation=cv2.INTER_NEAREST)
    new_img = np.where(labelimg == 1, 255, labelimg)
    mask_name = path + 'mask_{}.png'.format(num)
    # 保存分割出来的人像
    cv2.imwrite(mask_name, new_img)
    print(f'======== 第{num}张图像分割完成 ========')
    time.sleep(random.randint(1,2))
import cv2
import base64
import numpy as np
import os
from aip import AipBodyAnalysis
import time
import random

# 利用百度AI的人像分割服务 转化为二值图  有小姐姐身影的蒙版
# 百度云中已创建应用的  APP_ID API_KEY SECRET_KEY
APP_ID = '23649226'
API_KEY = '**********************'
SECRET_KEY = '**********************'

client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
# 保存图像分割后的路径
path = './mask_img/'

# os.listdir  列出保存到图片名称
img_files = os.listdir('./imgs')
print(img_files)
for num in range(88, len(img_files) + 1):
    # 按顺序构造出图片路径
    img = f'./imgs/img_{num}.jpg'
    img1 = cv2.imread(img)
    height, width, _ = img1.shape
    # print(height, width)
    # 二进制方式读取图片
    with open(img, 'rb') as fp:
        img_info = fp.read()

    # 设置只返回前景   也就是分割出来的人像
    seg_res = client.bodySeg(img_info)
    labelmap = base64.b64decode(seg_res['labelmap'])
    nparr = np.frombuffer(labelmap, np.uint8)
    labelimg = cv2.imdecode(nparr, 1)
    labelimg = cv2.resize(labelimg, (width, height), interpolation=cv2.INTER_NEAREST)
    new_img = np.where(labelimg == 1, 255, labelimg)
    mask_name = path + 'mask_{}.png'.format(num)
    # 保存分割出来的人像
    cv2.imwrite(mask_name, new_img)
    print(f'======== 第{num}张图像分割完成 ========')
    time.sleep(random.randint(1,2))
import cv2
import base64
import numpy as np
import os
from aip import AipBodyAnalysis
import time
import random

# 利用百度AI的人像分割服务 转化为二值图  有小姐姐身影的蒙版
# 百度云中已创建应用的  APP_ID API_KEY SECRET_KEY
APP_ID = '23649226'
API_KEY = '**********************'
SECRET_KEY = '**********************'

client = AipBodyAnalysis(APP_ID, API_KEY, SECRET_KEY)
# 保存图像分割后的路径
path = './mask_img/'

# os.listdir  列出保存到图片名称
img_files = os.listdir('./imgs')
print(img_files)
for num in range(88, len(img_files) + 1):
    # 按顺序构造出图片路径
    img = f'./imgs/img_{num}.jpg'
    img1 = cv2.imread(img)
    height, width, _ = img1.shape
    # print(height, width)
    # 二进制方式读取图片
    with open(img, 'rb') as fp:
        img_info = fp.read()

    # 设置只返回前景   也就是分割出来的人像
    seg_res = client.bodySeg(img_info)
    labelmap = base64.b64decode(seg_res['labelmap'])
    nparr = np.frombuffer(labelmap, np.uint8)
    labelimg = cv2.imdecode(nparr, 1)
    labelimg = cv2.resize(labelimg, (width, height), interpolation=cv2.INTER_NEAREST)
    new_img = np.where(labelimg == 1, 255, labelimg)
    mask_name = path + 'mask_{}.png'.format(num)
    # 保存分割出来的人像
    cv2.imwrite(mask_name, new_img)
    print(f'======== 第{num}张图像分割完成 ========')
    time.sleep(random.randint(1,2))

结果如下

图片[4]-用Python做一个漂亮小姐姐词云跳舞视频-软件开发技术分享

小姐姐跳舞词云生成

from wordcloud import WordCloud
import collections
import jieba
import re
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
# 读取数据
with open('bullet.txt') as f:
    data = f.read()
# 文本预处理  去除一些无用的字符   只提取出中文出来
new_data = re.findall('[\u4e00-\u9fa5]+', data, re.S)
new_data = "/".join(new_data)
# 文本分词
seg_list_exact = jieba.cut(new_data, cut_all=True)
result_list = []
with open('stop_words.txt', encoding='utf-8') as f:
    con = f.read().split('\n')
    stop_words = set()
    for i in con:
        stop_words.add(i)
for word in seg_list_exact:
    # 设置停用词并去除单个词
    if word not in stop_words and len(word) > 1:
        result_list.append(word)
# 筛选后统计词频
word_counts = collections.Counter(result_list)
path = './wordcloud/'
for num in range(88, 888):
    img = f'./mask_img/mask_{num}'
    # 获取蒙版图片
    mask_ = 255 - np.array(Image.open(img))
    # 绘制词云
    plt.figure(figsize=(8, 5), dpi=200)
    my_cloud = WordCloud(
        background_color='black',  # 设置背景颜色  默认是black
        mask=mask_,      # 自定义蒙版
        mode='RGBA',
        max_words=500,
        font_path='simhei.ttf',   # 设置字体  显示中文
    ).generate_from_frequencies(word_counts)
    # 显示生成的词云图片
    plt.imshow(my_cloud)
    # 显示设置词云图中无坐标轴
    plt.axis('off')
    word_cloud_name = path + 'wordcloud_{}.png'.format(num)
    my_cloud.to_file(word_cloud_name)    # 保存词云图片
    print(f'======== 第{num}张词云图生成 ========')
from wordcloud import WordCloud
import collections
import jieba
import re
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np


# 读取数据
with open('bullet.txt') as f:
    data = f.read()

# 文本预处理  去除一些无用的字符   只提取出中文出来
new_data = re.findall('[\u4e00-\u9fa5]+', data, re.S)
new_data = "/".join(new_data)

# 文本分词
seg_list_exact = jieba.cut(new_data, cut_all=True)

result_list = []
with open('stop_words.txt', encoding='utf-8') as f:
    con = f.read().split('\n')
    stop_words = set()
    for i in con:
        stop_words.add(i)

for word in seg_list_exact:
    # 设置停用词并去除单个词
    if word not in stop_words and len(word) > 1:
        result_list.append(word)

# 筛选后统计词频
word_counts = collections.Counter(result_list)
path = './wordcloud/'

for num in range(88, 888):
    img = f'./mask_img/mask_{num}'
    # 获取蒙版图片
    mask_ = 255 - np.array(Image.open(img))
    # 绘制词云
    plt.figure(figsize=(8, 5), dpi=200)
    my_cloud = WordCloud(
        background_color='black',  # 设置背景颜色  默认是black
        mask=mask_,      # 自定义蒙版
        mode='RGBA',
        max_words=500,
        font_path='simhei.ttf',   # 设置字体  显示中文
    ).generate_from_frequencies(word_counts)

    # 显示生成的词云图片
    plt.imshow(my_cloud)
    # 显示设置词云图中无坐标轴
    plt.axis('off')
    word_cloud_name = path + 'wordcloud_{}.png'.format(num)
    my_cloud.to_file(word_cloud_name)    # 保存词云图片
    print(f'======== 第{num}张词云图生成 ========')
from wordcloud import WordCloud
import collections
import jieba
import re
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np


# 读取数据
with open('bullet.txt') as f:
    data = f.read()

# 文本预处理  去除一些无用的字符   只提取出中文出来
new_data = re.findall('[\u4e00-\u9fa5]+', data, re.S)
new_data = "/".join(new_data)

# 文本分词
seg_list_exact = jieba.cut(new_data, cut_all=True)

result_list = []
with open('stop_words.txt', encoding='utf-8') as f:
    con = f.read().split('\n')
    stop_words = set()
    for i in con:
        stop_words.add(i)

for word in seg_list_exact:
    # 设置停用词并去除单个词
    if word not in stop_words and len(word) > 1:
        result_list.append(word)

# 筛选后统计词频
word_counts = collections.Counter(result_list)
path = './wordcloud/'

for num in range(88, 888):
    img = f'./mask_img/mask_{num}'
    # 获取蒙版图片
    mask_ = 255 - np.array(Image.open(img))
    # 绘制词云
    plt.figure(figsize=(8, 5), dpi=200)
    my_cloud = WordCloud(
        background_color='black',  # 设置背景颜色  默认是black
        mask=mask_,      # 自定义蒙版
        mode='RGBA',
        max_words=500,
        font_path='simhei.ttf',   # 设置字体  显示中文
    ).generate_from_frequencies(word_counts)

    # 显示生成的词云图片
    plt.imshow(my_cloud)
    # 显示设置词云图中无坐标轴
    plt.axis('off')
    word_cloud_name = path + 'wordcloud_{}.png'.format(num)
    my_cloud.to_file(word_cloud_name)    # 保存词云图片
    print(f'======== 第{num}张词云图生成 ========')

结果如下

图片[5]-用Python做一个漂亮小姐姐词云跳舞视频-软件开发技术分享

合成跳舞视频

import cv2
import os
# 输出视频的保存路径
video_dir = 'result.mp4'
# 帧率
fps = 30
# 图片尺寸
img_size = (1920, 1080)
fourcc = cv2.VideoWriter_fourcc('M', 'P', '4', 'V')  # opencv3.0 mp4会有警告但可以播放
videoWriter = cv2.VideoWriter(video_dir, fourcc, fps, img_size)
img_files = os.listdir('./wordcloud')
for i in range(88, 888):
    img_path = './wordcloud/' + 'wordcloud_{}.png'.format(i)
    frame = cv2.imread(img_path)
    frame = cv2.resize(frame, img_size)   # 生成视频   图片尺寸和设定尺寸相同
    videoWriter.write(frame)      # 写进视频里
    print(f'======== 按照视频顺序第{i}张图片合进视频 ========')
videoWriter.release()   # 释放资源
import cv2
import os

# 输出视频的保存路径
video_dir = 'result.mp4'
# 帧率
fps = 30
# 图片尺寸
img_size = (1920, 1080)

fourcc = cv2.VideoWriter_fourcc('M', 'P', '4', 'V')  # opencv3.0 mp4会有警告但可以播放
videoWriter = cv2.VideoWriter(video_dir, fourcc, fps, img_size)
img_files = os.listdir('./wordcloud')

for i in range(88, 888):
    img_path = './wordcloud/' + 'wordcloud_{}.png'.format(i)
    frame = cv2.imread(img_path)
    frame = cv2.resize(frame, img_size)   # 生成视频   图片尺寸和设定尺寸相同
    videoWriter.write(frame)      # 写进视频里
    print(f'======== 按照视频顺序第{i}张图片合进视频 ========')

videoWriter.release()   # 释放资源
import cv2
import os

# 输出视频的保存路径
video_dir = 'result.mp4'
# 帧率
fps = 30
# 图片尺寸
img_size = (1920, 1080)

fourcc = cv2.VideoWriter_fourcc('M', 'P', '4', 'V')  # opencv3.0 mp4会有警告但可以播放
videoWriter = cv2.VideoWriter(video_dir, fourcc, fps, img_size)
img_files = os.listdir('./wordcloud')

for i in range(88, 888):
    img_path = './wordcloud/' + 'wordcloud_{}.png'.format(i)
    frame = cv2.imread(img_path)
    frame = cv2.resize(frame, img_size)   # 生成视频   图片尺寸和设定尺寸相同
    videoWriter.write(frame)      # 写进视频里
    print(f'======== 按照视频顺序第{i}张图片合进视频 ========')

videoWriter.release()   # 释放资源

效果如下

视频插入音频

import moviepy.editor as mpy
# 读取词云视频
my_clip = mpy.VideoFileClip('result.mp4')
# 截取背景音乐
audio_background = mpy.AudioFileClip('song.mp4').subclip(17, 44)
audio_background.write_audiofile('vmt.mp3')
# 视频中插入音频
final_clip = my_clip.set_audio(audio_background)
# 保存为最终的视频   动听的音乐！漂亮小姐姐词云跳舞视频！
final_clip.write_videofile('final_video.mp4')
import moviepy.editor as mpy

# 读取词云视频
my_clip = mpy.VideoFileClip('result.mp4')
# 截取背景音乐
audio_background = mpy.AudioFileClip('song.mp4').subclip(17, 44)
audio_background.write_audiofile('vmt.mp3')
# 视频中插入音频
final_clip = my_clip.set_audio(audio_background)
# 保存为最终的视频   动听的音乐！漂亮小姐姐词云跳舞视频！
final_clip.write_videofile('final_video.mp4')
import moviepy.editor as mpy

# 读取词云视频
my_clip = mpy.VideoFileClip('result.mp4')
# 截取背景音乐
audio_background = mpy.AudioFileClip('song.mp4').subclip(17, 44)
audio_background.write_audiofile('vmt.mp3')
# 视频中插入音频
final_clip = my_clip.set_audio(audio_background)
# 保存为最终的视频   动听的音乐！漂亮小姐姐词云跳舞视频！
final_clip.write_videofile('final_video.mp4')

效果如下

视频播放器
本文参考 叶庭云利用Python做一个漂亮小姐姐词云跳舞视频
© 版权声明
文章版权归作者所有，未经允许请勿转载。
THE END
图文教程
# Python# 词云# 小姐姐# 跳舞
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谢谢你的分享，我从中学到了很多！
教程很好用，谢谢！
好东西，学习一下！
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    • Drixn的头像-软件开发技术分享钻石会员Drixn等级-LV6-软件开发技术分享作者0
      做一个漂亮小姐姐词云跳舞视频
      4年前回复
    • 头像Seandy0
      I risk to seem the layman, but nevertheless I will ask, whence it and who in general has written?
      4年前回复
    • 头像DanieluniSP0
      Спасибо за пост
      4年前回复
    • 头像我是谁0
      一想到你我就……
      4年前回复
    • 头像imgss0
      Python的魅力只有使用了才体会的到
      4年前回复
    • 头像Cherry0
      用Python做一个漂亮小姐姐词云跳舞视频
      4年前回复
    • 头像Firsdd0
      小姐姐好漂亮！
      4年前回复
    • 头像vessly0
      有个视频不见了。。。
      4年前回复

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