利用Python做一个小姐姐词云跳舞视频
Python编程与实战
共 9041字,需浏览 19分钟
· 2021-03-01
作者:北山啦
https://blog.csdn.net/qq_45176548/article/details/113410073
本文将以哔哩哔哩–乘风破浪视频为例,you-get下载视频,同时利用python爬取B站视频弹幕,并利用opencv对视频进行分割,百度AI进行人像分割,moviepy生成词云跳舞视频,并添加音频。
1. 导入模块
1.1 下载所需模块
import os
import time
libs = {"lxml","requests","pandas","numpy","you-get","opencv-python","pandas","fake_useragent","matplotlib","moviepy"}
try:
for lib in libs:
os.system(f"pip3 install -i https://pypi.doubanio.com/simple/ {lib}")
print(lib+"下载成功")
except:
print("下载失败")
1.2 导入模块
import os
import re
import cv2
import jieba
import requests
import moviepy
import pandas as pd
import numpy as np
from PIL import Image
from lxml import etree
from wordcloud import WordCloud
import matplotlib.pyplot as plt
from fake_useragent import UserAgent
2. 视频处理
2.1 下载视频
2.2 视频分割
2.2.1代码展示
# -*- coding:utf-8 -*-
# @Author : 北山啦
# @Time : 2021/1/29 14:08
# @File : 视频分割.py
# @Software : PyCharm
import cv2
cap = cv2.VideoCapture(r"无价之姐~让我乘风破浪~~~.flv")
while 1:
# 逐帧读取视频 按顺序保存到本地文件夹
ret,frame = cap.read()
if ret:
cv2.imwrite(f".\pictures\img_{num}.jpg",frame)
else:
break
cap.release() # 释放资源
2.2.2 结果展示
2.3 人像分割
2.3.1创建应用
2.3.2 Python SDK参考文档
2.3.3 代码展示
# -*- coding:utf-8 -*-
# @Author : 北山啦
# @Time : 2021/1/29 14:38
# @File : 人像分割.py
# @Software : PyCharm
"""原文链接:"""
import cv2
import base64
import numpy as np
import os
from aip import AipBodyAnalysis
import time
import random
APP_ID = '******'
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('./pictures')
print(img_files)
for num in range(1, len(img_files) + 1):
# 按顺序构造出图片路径
img = f'./pictures/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 ========')
2.3.4 结果展示
3. 弹幕爬取
3.1 网页分析
3.2 观察历史弹幕
3.3爬取弹幕
3.3.1构造时间序列
import pandas as pd
a = pd.date_range("2020-08-08","2020-09-08")
print(a)
DatetimeIndex(['2020-08-08', '2020-08-09', '2020-08-10', '2020-08-11',
'2020-08-12', '2020-08-13', '2020-08-14', '2020-08-15',
'2020-08-50', '2020-08-17', '2020-08-18', '2020-08-19',
'2020-08-20', '2020-08-21', '2020-08-22', '2020-08-23',
'2020-08-24', '2020-08-25', '2020-08-26', '2020-08-27',
'2020-08-28', '2020-08-29', '2020-08-30', '2020-08-31',
'2020-09-01', '2020-09-02', '2020-09-03', '2020-09-04',
'2020-09-05', '2020-09-06', '2020-09-07', '2020-09-08'],
dtype='datetime64[ns]', freq='D')
3.3.2 爬取数据
# -*- coding:utf-8 -*-
# @Author : 北山啦
# @Time : 2021/1/29 19:33
# @File : 弹幕爬取.py
# @Software : PyCharm
import requests
import pandas as pd
import re
import csv
from fake_useragent import UserAgent
from concurrent.futures import ThreadPoolExecutor
import datetime
ua = UserAgent()
start_time = datetime.datetime.now()
def Grab_barrage(date):
headers = {
"origin": "https://www.bilibili.com",
"referer": "https://www.bilibili.com/video/BV1jZ4y1K78N?from=search&seid=1084505810439035065",
"cookie": "",
"user-agent": ua.random(),
}
params = {
'type': 1,
'oid' : "222413092",
'date': date
}
r= requests.get(url, params=params, headers=headers)
r.encoding = 'utf-8'
comment = re.findall('<d p=".*?">(.*?)</d>', r.text)
for i in comments:
df.append(i)
a = pd.DataFrame(df)
a.to_excel("danmu.xlsx")
def main():
with ThreadPoolExecutor(max_workers=4) as executor:
executor.map(Grab_barrage, date_list)
"""计算所需时间"""
delta = (datetime.datetime.now() - start_time).total_seconds()
print(f'用时:{delta}s')
if __name__ == '__main__':
# 目标url
url = "https://api.bilibili.com/x/v2/dm/history"
start,end = '20200808','20200908'
date_list = [x for x in pd.date_range(start, end).strftime('%Y-%m-%d')]
count = 0
main()
3.3.3结果展示
4.生成词云图
4.1 评论内容机械压缩去重
def func(s):
for i in range(1,int(len(s)/2)+1):
for j in range(len(s)):
if s[j:j+i] == s[j+i:j+2*i]:
k = j + i
while s[k:k+i] == s[k+i:k+2*i] and k<len(s):
k = k + i
s = s[:j] + s[k:]
return s
data["短评"] = data["短评"].apply(func)
4.2 添加停用词和自定义词组
import pandas as pd
from wordcloud import WordCloud
import jieba
from tkinter import _flatten
import matplotlib.pyplot as plt
jieba.load_userdict("./词云图//add.txt")
with open('./词云图//stoplist.txt', 'r', encoding='utf-8') as f:
stopWords = f.read()
4.3生成词云图
# -*- coding:utf-8 -*-
# @Author : 北山啦
# @Time : 2021/1/29 19:10
# @File : 跳舞词云图生成.py
# @Software : PyCharm
from wordcloud import WordCloud
import collections
import jieba
import re
from PIL import Image
import matplotlib.pyplot as plt
import numpy as np
with open('barrages.txt') as f:
data = f.read()
jieba.load_userdict("./词云图//add.txt")
# 读取数据
with open('barrages.txt') as f:
data = f.read()
jieba.load_userdict("./词云图//add.txt")
# 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('./词云图/stoplist.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/'
img_files = os.listdir('./mask_img')
print(img_files)
for num in range(1, len(img_files) + 1):
img = fr'.\mask_img\mask_{num}.png'
# 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 ========')
5. 合成视频
5.1图片合成
# -*- coding:utf-8 -*-
# @Author : 北山啦
# @Time : 2021/1/29 19:10
# @File : 跳舞词云图生成.py
# @Software : PyCharm
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
5.2 音频添加
# -*- coding:utf-8 -*-
# @Author : 北山啦
# @Time : 2021/1/29 19:10
# @File : 跳舞词云图生成.py
# @Software : PyCharm
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.mp3').subclip(0,25)
audio_background.write_audiofile('song1.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')
6. 结果展示
到这里就结束了,如果对你有帮助,欢迎点赞,你的点赞对我很重要。
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