Generate subtitles with Python

Generate subtitles with Python

Table of Contents:

1. Introduction
2. The Process of Auto-generating Subtitles
3. Getting the Audio from the Video
4. Transcribing the Audio Using AI
5. Extracting Frames and Cropping for Instagram Reels
6. Slicing and Adding Transcription to Frames
7. Creating the Output Video
8. Importing Necessary Libraries
9. Creating the Video Transcriber Class
10. Transcribing the Video
11. Extracting Audio from the Video
12. Extracting Frames and Adding Text
13. Creating the Final Video
14. Conclusion

The Process of Auto-generating Subtitles

Auto-generating subtitles for videos has become an essential feature for content creators, making their videos accessible to a wider audience and improving engagement. In this article, we'll explore the process of auto-generating subtitles using a simple Python script and AI technology. We'll cover everything from extracting audio and transcribing it using AI to extracting frames, adding text, and creating the final video output. By the end of this guide, you'll have a clear understanding of how to automate the subtitles generation process for your next Instagram reel or YouTube short.

1. Introduction

Have you ever wondered how auto-generated subtitles are created? In this video, I'm going to show you a simple Python script where I use AI to automate this process and produce your next Instagram reel from a video. Let's get started!

2. Getting the Audio from the Video

The first step in auto-generating subtitles is extracting the audio from the video. By extracting the audio, we can process it and convert it into text using AI. To extract the audio, we'll use a Python library called moviepy. This library allows us to load the video and extract the audio from it. Once we have the audio, we can proceed to the next step.

3. Transcribing the Audio Using AI

To transcribe the audio into text, we'll use an AI called Whisper. Whisper is a powerful speech recognition system that can convert spoken language into written text. In our Python script, we'll load the Whisper model and feed the extracted audio into it. The result will be a transcription of the audio, which we can further process.

4. Extracting Frames and Cropping for Instagram Reels

Next, we'll take the video and extract all of its frames. We'll also crop the frames to a horizontal 16:9 ratio, which is ideal for Instagram reels and YouTube shorts. By extracting frames and cropping them, we'll prepare the canvas for adding the transcribed text later in the process.

5. Slicing and Adding Transcription to Frames

Now that we have the transcription from Whisper, we'll slice it into smaller parts that fit the screen. We'll divide the text segments based on the size of the screen and calculate how many words can fit at each given time. By doing this, we ensure that the text remains visible and readable throughout the video.

6. Creating the Output Video

In this step, we'll gather all the frames and produce the final output video. We'll create a folder to store the frames and use the image sequence clip function from the moviepy library to combine them into a video. We'll also add the transcribed text as subtitles on each frame. The result will be a complete auto-generated video with subtitles.

7. Importing Necessary Libraries

Before getting started, we need to import the necessary libraries. These libraries include moviepy for video processing, Whisper for speech recognition, and OpenCV for frame extraction and manipulation. If any library is missing, we can easily install it using pip.

8. Creating the Video Transcriber Class

To structure our code, we'll create a video transcriber class. This class will contain the necessary constructors and methods to perform the auto-generating subtitles process. The constructors will handle loading the Whisper model and other necessary variables.

9. Transcribing the Video

Inside the video transcriber class, we'll write the method to transcribe the video. This method will use the loaded Whisper model to transcribe the audio and store the resulting text in a variable. We'll also process this text to obtain the segments' start time, end time, and the text within.

10. Extracting Audio from the Video

Now, we'll implement the method to extract audio from the video using the moviepy library. We'll load the video, extract the audio, and save it to a specified output path. This extracted audio will be used later in the transcription process.

11. Extracting Frames and Adding Text

In this step, we'll write the method to extract frames from the video using OpenCV. We'll loop over each frame, add the corresponding text from the transcription, and check if the frame number matches the starting and ending frames of the text segment. By doing this, we'll ensure that the text appears at the right time on the frames.

12. Creating the Final Video

Finally, we'll create the method that processes the extracted frames and creates the final output video. This method will create a folder to store the frames if it doesn't exist already. Then, it will call the frame extraction method described earlier. Once the frames are extracted and text is added, we'll use the image sequence clip function from moviepy to combine them into a video. We'll also include the audio extracted earlier.

13. Conclusion

Auto-generating subtitles for videos can save you time and effort. By using a Python script and AI technology, you can automate the process of transcribing audio and adding subtitles to your videos. This not only improves accessibility but also enhances the overall viewing experience. With the steps outlined in this article, you'll be able to create auto-generated subtitles for your next Instagram reel or YouTube short with ease.

Highlights:

• Auto-generating subtitles using a Python script and AI technology
• Extracting audio from a video and transcribing it using Whisper AI
• Extracting frames and cropping them for Instagram reels and YouTube shorts
• Adding transcribed text to frames and creating the final auto-generated video
• Improving accessibility and viewer engagement with auto-generated subtitles

FAQ: Q: Can I use any video for the auto-generating subtitles process? A: Yes, you can use any video as long as you can extract the audio from it using the moviepy library.

Q: Do I need programming experience to use the Python script? A: Some programming experience would be beneficial, but the provided guide will help you understand the steps involved.

Q: Can I customize the appearance of the subtitles? A: Yes, you can customize the appearance of the subtitles by modifying the code and adding additional styling options.

Q: Does the Python script support languages other than English? A: Yes, the Whisper AI used in the script supports multiple languages, allowing you to transcribe audio in various languages.