Video-Transcript

Easily transcribe any video from anywhere! This tool allows you to extract transcripts from YouTube videos, Canvas videos, McGraw Hill, and any streaming links or local files. Powered by advanced speech-to-text technology, it works with MP4, MP3, and streaming links, organizing the transcripts neatly with timestamps.

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How It Works

1. For YouTube Videos:

   • Paste the YouTube video link into the program.
   • The tool will automatically download the audio and generate the transcript.

2. For Canvas Videos:

   • Open the video in your browser.
   • Right-click on the video and select Inspect or press Ctrl + Shift + I (Windows) or Cmd + Option + I (Mac).
   • Find the video source (src) link in the HTML code under the <video> tag or Network tab.
   • Copy the source link and paste it into the program.

3. For McGraw Hill Videos:

   • Follow the same steps as for Canvas videos. Inspect the video source, find the src link, and paste it into the program.

4. For Other Websites or Local Files:

   • Paste the streaming link or load a local video/audio file to generate transcripts.

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Features

• Works with platforms like YouTube, Canvas, McGraw Hill, and more.
• Supports MP4, MP3, and direct streaming links.
• Organizes transcripts in a transcripted folder with filenames based on timestamps (e.g., transcript_2025-01-23_12-30-45.txt).
• Use the transcript as input to ChatGPT to summarize the video content, so you no longer have to watch it!

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Installation

1. Clone the Repository:

   git clone https://github.com/dannyphantom55/Video-Transcript.git
   cd Video-Transcript
   

2. pip install -r requirements.txt

3. Windows: Download FFmpeg from FFmpeg.org. Add the ffmpeg/bin directory to your system's PATH.

4. Run the program: python video2script.py Paste the video link or local file path as prompted:

YouTube: Paste the YouTube link. Canvas/McGraw Hill: Use the Inspect Element tool to get the video src link and paste it. Other Files: Provide the file path to a local MP4 or MP3 file. The transcript will be saved in the transcripted folder with a unique filename based on the current date and time.