- Imports a video
- Analyzes the video and generates a summary of the video
- Uses GPT to generate a set of quiz questions based on the video summary
- Converts these quiz questions to audio using Whisper
- Commits your code to a GitHub repository and adds
github.com/EWizardIIto the repo
- Choose a video file you would like to work with.
- Use appropriate Python libraries to import the video into your Jupyter Notebook.
- Use machine learning models to analyze the video content.
- Generate a concise summary of the video's main points and themes.
- Reference: GPT with Vision for Video Understanding
- Utilize GPT to generate a set of quiz questions based on the summary.
- Aim for a variety of question types (multiple-choice, true/false, short answer).
- Use Whisper or a similar text-to-speech library to convert the generated quiz questions into audio format.
- Ensure your code is clean, well-documented, and functional.
- Commit your Jupyter Notebook and any associated files to a GitHub repository.
- Add
github.com/EWizardIIto the repository as a collaborator.
- GPT with Vision for Video Understanding
- Use tools like ChatGPT, Claude AI, or GitHub Copilot to assist you in developing your code.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent