YouTube Shorts Automation Tool

This project automates the creation of YouTube Shorts by generating videos with Text-to-Speech (TTS), subtitles, and background music. It allows users to input images and text, which are then transformed into short videos suitable for YouTube Shorts.

Example

Take a look at this channel - all of the shorts were created using this tool.

Features

• Text-to-Speech Integration: Supports TTS using either ElevenLabs or TikTok for generating voiceovers from provided text.
• Automatic Subtitles Generation: Subtitles are auto-generated based on the TTS audio output, and users can choose to skip manual subtitle review.
• Image-to-Video Conversion: Converts images into videos by adding animated effects and placing the image within a video frame.
• Background Music: Option to add background music to the video, enhancing the overall production.
• Multi-Video Merging: Combines multiple video clips into a single video output if multiple items are provided.
• Customizable Output: Users can specify various settings such as the voice for TTS, audio volume, and whether to keep the original audio in the video.

Installation

1. Clone the repository:

   git clone https://github.com/IvanPeshykov/youtube-shorts-automation.git

2. Install the required dependencies:

   pip install -r requirements.txt

3. Create a .env file in the project root directory and add your ElevenLabs API key and TikTok session ID (if using TikTok TTS):

   elevenlabs_apikey=your_elevenlabs_apikey
   session_id=your_tiktok_session_id

4. Ensure you have the following external libraries installed:

   • moviepy
   • whisper
   • pydub
   • requests
   • dotenv

Configuration

The tool uses a configuration file (config.json) to customize the video creation process. Here's an example configuration:

{
  "mode": "manual",
  "tts": "elevenlabs",
  "elevenlabs": {
    "voice_id": "EiNlNiXeDU1pqqOPrYMO"
  },
  "tiktok": {
    "voice_name": "en_us_010"
  },
  "song": "D:/Shorts/assets/music/epic/epic.mp3",
  "skip": true,
  "items": [
    {
      "path": "C:/Users/Ivan/Downloads/tiger.jpg",
      "text": "Why the Tiger1 tank is undoubtedly the best tank ever created?",
      "keep_audio": false
    }
  ]
}

Configuration Parameters:

• mode: Defines whether the process is manual or auto. In manual mode, you can review and edit subtitles before the video is generated.
• tts: Choose between elevenlabs or tiktok for generating voiceovers from text.
• elevenlabs.voice_id: The ID of the voice to use for ElevenLabs TTS.
• tiktok.voice_name: The name of the voice to use for TikTok TTS.
• song: Path to the background music to include in the video.
• skip: If set to true, the process skips manual subtitle review and proceeds with the video generation automatically.
• items: List of items to be processed, where each item includes:
  • path: Path to the image to be used in the video.
  • text: Text to be converted to speech.
  • keep_audio: If true, retains the original audio from the video file.

Usage

1. Set up the configuration: Modify the config.json file to include your desired settings (TTS voice, image, text, music, etc.).

2. Run the script:

   python main.py

3. The script will generate the video, combining the image with the generated voiceover, subtitles, and any provided background music. The final video will be saved to the output directory.

4. The generated video will be ready for uploading to YouTube Shorts.

File Structure

.
├── config.json            # Configuration file with settings for the video creation
├── main.py                # Main script for processing the video creation
├── output/                # Directory where the output videos are saved
├── src/                   # Source code files containing the logic for video creation
├── .env                   # Environment variables (API keys, etc.)
└── requirements.txt       # Python dependencies

Dependencies

• moviepy: Video editing library to handle video and audio processing.
• whisper: For transcribing audio into subtitles.
• pydub: For handling audio manipulation (combining and editing).
• requests: For making HTTP requests to the TTS APIs.
• dotenv: For loading environment variables.

License

This project is licensed under the MIT License - see the LICENSE file for details.