Introducing Whisper-TikTok 🤖🎥

Discover Whisper-TikTok, an innovative AI-powered tool that leverages the prowess of Edge TTS, OpenAI-Whisper, and FFMPEG to craft captivating TikTok videos. Harnessing the capabilities of OpenAI's Whisper model, Whisper-TikTok effortlessly generates an accurate transcription from provided audio files, laying the foundation for the creation of mesmerizing TikTok videos through the utilization of FFMPEG. Additionally, the program seamlessly integrates the Microsoft Edge Cloud Text-to-Speech (TTS) API to lend a vibrant voiceover to the video. Opting for Microsoft Edge Cloud TTS API's voiceover is a deliberate choice, as it delivers a remarkably natural and authentic auditory experience, setting it apart from the often monotonous and artificial voiceovers prevalent in numerous TikTok videos.

Webui 🎨

Demo Video 🎬

demo.mp4

Operating Principle

Employing Whisper-TikTok is a breeze: simply modify the video.json. The JSON file contains the following fields:

series: The name of the series.
part: The part number of the video.
text: The text to be spoken in the video.
outro: The outro text to be spoken in the video.
tags: The tags to be used for the video.

Summarizing the program's functionality:

Furnished with a structured JSON dataset containing details such as the series name, video part number, video text and outro text, the program orchestrates the synthesis of a video incorporating the provided text and outro. Subsequently, the generated video is stored within the designated output folder.

In-Depth Insights

The program conducts the sequence of actions outlined below:

Retrieve environment variables from the optional .env file.
Validate the presence of PyTorch with CUDA installation. If the requisite dependencies are absent, the program will use the CPU instead of the GPU.
Download a random video from platforms like YouTube, e.g., a Minecraft parkour gameplay clip.
Load the OpenAI Whisper model into memory.
Extract the video text from the provided JSON file and initiate a Text-to-Speech request to the Microsoft Edge Cloud TTS API, preserving the response as an .mp3 audio file.
Utilize the OpenAI Whisper model to generate a detailed transcription of the .mp3 file, available in .srt format.
Select a random background video from the dedicated folder.
Integrate the srt file into the chosen video using FFMPEG, creating a final .mp4 output.
Upload the video to TikTok using the TikTok session cookie. For this step it is required to have a TikTok account and to be logged in on your browser. Then the required cookies.txt file can be generated using this guide available here. The cookies.txt file must be placed in the root folder of the project.
Voila! In a matter of minutes, you've crafted a captivating TikTok video while sipping your favorite coffee ☕️.

Webui Access 🔐

There is a webui hosted thanks to streamlit. To do it, just click on this link that will take you directly to the webui.

https://convert.streamlit.app/

Auto Installation 🤖

To auto install Whisper-TikTok on your system, follow the instructions below based on your operating system:

For Linux Users (Bash) 🟩

Download the .sh file
Open a terminal.
Run the following command:
```
./Whisper-TikTok-Linux.sh
```

This script will check and install necessary dependencies, create a Conda environment, clone the repository, install Python dependencies, and prompt you to choose between running the web user interface (webui) or the script.

For Windows Users (PowerShell) 🟥

Click on the Whisper-TikTok-Windows.bat file and let him do the work.

Download the .bat file
Open a Command Prompt.
Run the following command:
```
Whisper-TikTok-Windows.bat
```

This batch script performs a similar set of tasks as the Linux script, ensuring that Conda, Git, Python, and other dependencies are installed. It then prompts you to choose between running the web user interface (webui) or the script.

What the Script Does

Check and Install Conda: Verifies if Conda is installed; if not, installs the latest version.
Create Conda Environment: Sets up a Conda environment with Python 3.11.
Clone Repository: Clones the Whisper-TikTok repository from GitHub.
Install Dependencies: Installs Python dependencies specified in the requirements.txt file.
Check and Install FFmpeg: Ensures FFmpeg is installed; if not, checks the system package manager (apt, brew, etc.) or installs it using Scoop on Windows.
Run the Program: Prompts the user to choose between running the web user interface (webui) or the script (main.py).

Feel free to reach out if you have any questions or encounter issues while running the script.

Manual Installation 🛠️

Whisper-TikTok has undergone rigorous testing on Windows 10, Windows 11 and Ubuntu 23.04 systems equipped with Python versions 3.8, 3.9 and 3.11.

First clone the repository

git clone https://github.com/MatteoFasulo/Whisper-TikTok.git

Dependencies 🌿

To streamline the installation of necessary dependencies, execute the following command within your terminal:

pip install -U -r requirements.txt

It also requires the command-line tool ffmpeg to be installed on your system, which is available from most package managers:

# on Ubuntu or Debian

sudo apt update && sudo apt install ffmpeg

# on Arch Linux

sudo pacman -S ffmpeg

# on MacOS using Homebrew (<https://brew.sh/>)

brew install ffmpeg

# on Windows using Chocolatey (<https://chocolatey.org/>)

choco install ffmpeg

# on Windows using Scoop (<https://scoop.sh/>)

scoop install ffmpeg

Please note that for optimal performance, it's advisable to have a GPU when using the OpenAI Whisper model for speech recognition. However, the program will work without a GPU, but it will run more slowly. This performance difference is because GPUs efficiently handle fp16 computation, while CPUs use fp32 or fp64 (depending on your machine), which are slower.

Webui 🔧

To embark on your Whisper-TikTok journey, initiate the following command within your terminal:

python app.py

Command-Line ♨️

To embark on your Whisper-TikTok journey, initiate the following command within your terminal:

python main.py

Command-Line Options

Whisper-TikTok supports the following command-line options:

python main.py [OPTIONS]

Options:
  --model TEXT        Model to use
                      [tiny|base|small|medium|large] (Default: small)
  --non_english       Use general model, not the English one specifically. (Flag)
  --url TEXT          YouTube URL to download as background video.
                      (Default: <https://www.youtube.com/watch?v=intRX7BRA90>)
  --tts TEXT          Voice to use for TTS (Default: en-US-ChristopherNeural)
  --list-voices       Use `edge-tts --list-voices` to list all voices.
  --random_voice      Random voice for TTS (Flag)
  --gender TEXT       Gender of the random TTS voice [Male|Female].
  --language TEXT     Language of the random TTS voice
                      (e.g., en-US)
  --sub_format TEXT   Subtitle format to use [u|i|b] (Default: b) | b (Bold), u (Underline), i (Italic)
  --sub_position INT Subtitle position to use [1-9] (Default: 5)
  --font TEXT         Font to use for subtitles (Default: Lexend Bold)
  --font_color TEXT   Font color to use for subtitles in HEX format (Default: #FFF000).
  --font_size INT    Font size to use for subtitles (Default: 21)
  --upload_tiktok     Upload the video to TikTok (Flag)
  -v, --verbose       Verbose (Flag)

If you use the --random_voice option, please specify both --gender and --language arguments. Also you will need to specify the --non_english argument if you want to use a non-English voice otherwise the program will use the English model. Whisper model will auto-detect the language of the audio file and use the corresponding model.

Usage Examples

Generate a TikTok video using a specific TTS model and voice:

python main.py --model medium --tts en-US-EricNeural

Generate a TikTok video without using the English model:

python main.py --non_english --tts de-DE-KillianNeural

Use a custom YouTube video as the background video:

python main.py --url https://www.youtube.com/watch?v=dQw4w9WgXcQ --tts en-US-JennyNeural

Modify the font color of the subtitles:

python main.py --sub_format b --font_color #FFF000 --tts en-US-JennyNeural

Generate a TikTok video with a random TTS voice:

python main.py --random_voice --gender Male --language en-US

List all available voices:

edge-tts --list-voices

Additional Resources

Accelerate Video Creation with reddit2json

reddit2json is a Python script that transforms Reddit post URLs into a JSON file, streamlining the process of creating video.json files. This tool not only converts Reddit links but also offers functionalities such as translating Reddit post content using DeepL and modifying content through custom OpenAI GPT calls.

reddit2json: Directly Convert Reddit Links to JSON

reddit2json is designed to process a list of Reddit post URLs, converting them into a JSON format that can be used directly for video creation. This tool enhances the video creation process by providing a faster and more efficient way to generate video.json files.

Here is the detailed README for reddit2json which includes instructions for installation, setting up the .env file, example calls, and more.

Code of Conduct

Please review our Code of Conduct before contributing to Whisper-TikTok.

Contributing

We welcome contributions from the community! Please see our Contributing Guidelines for more information.

Upcoming Features 🔮

Integration with the OpenAI API to generate more advanced responses.
Generate content by extracting it from reddit MatteoFasulo#22

OpenAI Whisper Forum Discussion

openai/whisper#223

Acknowledgments

We'd like to give a huge thanks to @rany2 for their edge-tts package, which made it possible to use the Microsoft Edge Cloud TTS API with Whisper-TikTok.
We also acknowledge the contributions of the Whisper model by @OpenAI for robust speech recognition via large-scale weak supervision
Also @jianfch for the stable-ts package, which made it possible to use the OpenAI Whisper model with Whisper-TikTok in a stable manner with font color and subtitle format options.

YotomiY/Whisper-TikTok