BlogBot - a Python script that create blogs from YouTube videos.

Overview

BlogBot - Convert Youtube Videos To Blogs

BlogBot is a Python script that create blogs from YouTube videos.

Visit BlogBot to read blogs created from script.

Installation

Use requirements.txt file to install required packages.

pip install -r requirements.txt

Usage

Open bot.py and add Blogger and Youtube API ID's

" YOUTUBE_ID = ' '">
BLOG_ID = "
     
     
      
      "
     
     
YOUTUBE_ID = '
     
     
      
      '
     
     

Blogger ID can be obtained by going to the dashboard of blogger and check url:

Example Image:

image

Youtube API Key follow this tutorial to get api key or follow the official tutorial

Along with all this we also need to setup OAuth for Blogger. Follow this tutorial to setup OAuth.

If everything works well. You should get 'client_secret_ .json'

Rename this JSON file to 'credentials.json' and put it in the same directory as blogBot.py.

Almost Done!

Now we must pass the id of the channel from which we wish to obtain videos.

Click here and follow the instructions on page to obtain channel id.

When you get id, open bot.py and add or replace the information present in channels.

", "channel_tag": " ", "channel_id": " ", } ] ">
# You can add new channels to the list as well
channels = [
    {
        "channel_name": "Abhijit Chavda",
        "channel_tag": "abhijitchavda",
        "channel_id": "UC2bBsPXFWZWiBmkRiNlz8vg",
    },
    {
        "channel_name": "
     
     
      
      "
     
     ,
        "channel_tag": "
     
     
      
      "
     
     ,
        "channel_id": "
     
     
      
      "
     
     ,
    }
]

Contributing

Pull requests are welcome.

Known Issues

  • Some videos may throw error when fetching transcripts.
  • When publishing videos on blogger, 'tags' or 'label' error may occure.

P.S: I have not tested this script on a fresh env yet, some parts can be unstable.

License

MIT

Image and video quality assessment

CenseoQoE: 视觉感知画质评价框架 项目介绍 图像/视频在编解码、传输和显示等过程中难免引入不同类型/程度的失真导致图像质量下降。图像/视频质量评价(IVQA)的研究目标是希望模仿人类视觉感知系统, 通过算法评估图片/视频在终端用户的眼中画质主观体验的好坏,目前在视频编解码、画质增强、画质监。

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