Master Multi-Modal AI Coding

Table of Contents:

1. Introduction
2. How GPT Works for Vision
3. Steps to Create an AI Video with Voice Over
4. Uploading the Video and Adding a Prompt
5. Splitting the Video into Frames
6. Interpreting the Frames with GPT-4 Vision
7. Creating Audio with OpenAI's Text to Speech
8. Merging the Audio and Frames into a New Video
9. Building the AI Video Maker
10. Conclusion

Introduction

In this article, we will explore the use of GPT-4, an advanced AI model developed by OpenAI, to create AI videos with voice-overs. We will walk through the process of uploading a video, adding a prompt, splitting the video into frames, interpreting the frames using GPT-4 Vision, creating audio using OpenAI's Text to Speech, and merging everything into a new video. By the end of this article, You will have a clear understanding of how to use GPT-4 to make your own AI video with a personalized voice-over.

How GPT Works for Vision

GPT-4 Vision is a powerful AI model developed by OpenAI that can analyze visual data. When a video is uploaded to the system, GPT-4 Vision splits the video into frames and sends an API request to interpret each frame. It processes all the frames and generates a text representation of the content in the video. This text is then used to create an audio narrative using OpenAI's Text to Speech (TTS) model. Finally, the audio and frames are merged to create a new video with an AI-generated voice-over.

Steps to Create an AI Video with Voice Over

To create an AI video with a voice-over using GPT-4 Vision, we need to follow a series of steps. Let's take a closer look at each step involved in the process.

1. Uploading the Video and Adding a Prompt

The first step is to upload the video to our front-end application built on Streamlit. Once the video is uploaded, the user will be prompted to provide a description of the video and specify the Type of voice-over they require.

2. Splitting the Video into Frames

After the video and prompt are received, we split the video into frames. This allows us to bypass the Current rate limits with GPT-4 Vision and ensures smooth processing of the video. Each frame is encoded into a Base64 format to facilitate further processing.

3. Interpreting the Frames with GPT-4 Vision

The frames, encoded in Base64, are passed to GPT-4 Vision for interpretation. GPT-4 Vision analyzes each frame and generates a text representation of the video content. This text will later be used to create the audio narrative.

4. Creating Audio with OpenAI's Text to Speech

Using the text generated by GPT-4 Vision, we leverage OpenAI's Text to Speech (TTS) model to convert the text into an audio narrative. The audio is carefully streamed, buffered, and saved to ensure a seamless transition between the visual frames and the auditory narration.

5. Merging the Audio and Frames into a New Video

Finally, we merge the audio file created with the frames from the original video. This process involves using the MoviePy library to process and combine the audio clips. The result is a new video file that includes the AI-generated voice-over synchronized with the original visual content.

Building the AI Video Maker

To build our AI video maker, we will combine existing functions from Jason AI with our own functions. This allows us to bypass rate limits and process longer videos. We import necessary libraries such as IPython, display, Streamlit, OS, MoviePy, CV2, and OpenAI.

The main functions in our AI video maker include video_to_frames_in_chunks, frames_to_story, text_to_audio, and generate.

video_to_frames_in_chunks

This function is responsible for splitting the uploaded video into frame chunks. It creates a temporary file for the video, calculates its duration, and captures frames using CV2. The frames are then encoded into Base64 and divided into chunks. The function returns data about each chunk, including the frame count, video file name, and duration.

frames_to_story

The frames_to_story function utilizes GPT-4 Vision to transform a sequence of images into a Cohesive narrative. It selects every 25th frame from a set of Base64 encoded images and pairs them with a user prompt. These inputs are then fed into GPT-4 to generate a text story.

text_to_audio

The text_to_audio function converts the text story generated by GPT-4 into spoken word using OpenAI's advanced TTS model. It streams, buffers, and saves the audio to ensure a smooth transition from the visual frames to an engaging auditory experience.

generate

The generate function is the main entry point of the AI video maker. It serves as the user interface and handles the processing of the video. Users can upload a video, provide a prompt, and generate an enhanced video with an AI-generated voice-over. The function includes error handling and retry logic to ensure successful processing even in case of API timeouts or rate limits.

Conclusion

In conclusion, GPT-4 Vision combined with OpenAI's Text to Speech model empowers us to create AI videos with personalized voice-overs. By following the step-by-step process outlined in this article, you can leverage the power of AI to transform ordinary videos into engaging stories. The AI video maker we have built integrates seamlessly with various technologies and libraries to enhance multimedia experiences. With the potential to process longer videos and bypass rate limits, the AI video maker opens up new possibilities for creative voiceovers and storytelling.

Highlights:

• Use GPT-4 and OpenAI's Text to Speech to create AI videos with voice-overs
• Split videos into frames and interpret the content using GPT-4 Vision
• Convert the interpreted text into audio narratives
• Merge the audio and frames to create a new AI-enhanced video
• Bypass rate limits and process longer videos using custom functions

FAQ

Q: Can I use GPT-4 Vision to analyze images as well? A: Yes, GPT-4 Vision can analyze both images and videos.

Q: Does GPT-4 Vision support real-time video processing? A: GPT-4 Vision can process videos in real-time by splitting them into frames and interpreting each frame individually.

Q: What type of voice-over options are available with OpenAI's Text to Speech? A: OpenAI's Text to Speech offers multiple voices to choose from, allowing you to customize the voice-over based on your preferences.

Q: Is there a limit to the length of the videos that can be processed by the AI video maker? A: The AI video maker can process longer videos by splitting them into chunks and processing them individually.

Q: Can I customize the prompt for the AI-generated voice-over? A: Yes, you can provide a prompt that describes the video and specifies the type of voice-over you require. This prompt serves as a starting point for the AI to generate the narrative.