Beautiful Captions 🎬

A fast and elegant Python library for adding beautiful captions to videos. Combines the speed of FFmpeg with the beauty of custom styling.

Features

• ⚡ Lightning-fast caption rendering
• 🎨 Beautiful default styling with customization options
• 💃 Engaging bounce animation for captions
• 🤖 Built-in support for AssemblyAI
• 📝 Support for SRT files
• 🛠️ Simple, intuitive API

Installation

pip install beautiful-captions

Quick Start

Beautiful Captions provides two API styles to suit your needs:

Functional API

from beautiful_captions import add_captions, transcribe, process_video

# Using an existing SRT file
subtitles_from_srt("input.mp4", "subtitles.srt", style="default")

# Transcribe and caption
transcribe("video.mp4", service="assemblyai", api_key="YOUR_KEY")
subtitles_from_srt("video.mp4", "generated.srt", style="default")

# All-in-one process
add_subtitles("input.mp4", 
    transcribe_with="assemblyai",
    api_key="YOUR_KEY",
    style="default"
)

Object-Oriented API

from beautiful_captions import Video

# Using an existing SRT file
video = Video("input.mp4")
video.subtitles_from_srt("subtitles.srt", style="default")
video.save("output.mp4")

# Transcribe and caption
video = Video("input.mp4")
video.transcribe(service="assemblyai", api_key="YOUR_KEY")
video.subtitles_from_srt(style="default", animation="bounce")
video.save("output.mp4")

Styling Options

Customize your captions with these options:

from beautiful_captions import Style

style = Style(
    font="Arial",          # Font family
    color="white",         # Text color
    outline_color="black", # Outline color
    outline_width=2,       # Outline thickness
    position="bottom",     # Vertical position
    animation="bounce"     # Animation type
)

add_captions("input.mp4", "subtitles.srt", style=style)

Transcription Services

Beautiful Captions supports multiple transcription services out of the box:

# Using AssemblyAI
video.transcribe(service="assemblyai", api_key="YOUR_ASSEMBLYAI_KEY")

Performance

Beautiful Captions is optimized for speed while maintaining high-quality output. Here's how it compares to MoviePy:

Benchmarks coming soon

Contributing

We welcome contributions of all sizes! Beautiful Captions is designed to be modular and easy to extend. Here are some ways you can contribute:

Areas for Contribution

1. Transcription Services: Add support for new transcription services by implementing the transcription interface
2. Caption Styles: Create new preset styles that others can use
3. Animations: Develop new caption animation types
4. Performance Improvements: Help optimize the caption rendering pipeline
5. Documentation: Improve docs, add examples, or fix typos
6. Bug Reports: Submit detailed bug reports and feature requests

Getting Started

1. Check our Contributing Guide for detailed instructions
2. Look for issues labeled good-first-issue or help-wanted
3. Join discussions in GitHub Discussions to share ideas
4. Read our Code of Conduct

See CONTRIBUTING.md for full details on our development process.

Development Setup

1. Clone the repository:

git clone https://github.com/aayushgupta16/beautiful-captions.git
cd beautiful-captions

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install development dependencies:

pip install -e ".[dev]"

Future Features

Vote on upcoming features in our GitHub Discussions:

• Additional preset styles (TikTok-style, Hormozi-style, etc.)
• Support for VTT format
• More animation types
• Additional transcription services

Configuration Reference

CaptionConfig accepts three nested configs: style, animation, and diarization. You can pass them as dict literals or as config objects.

from beautiful_captions import Video, CaptionConfig

CaptionConfig

The top-level config that wraps everything:

# Using dicts (recommended)
config = CaptionConfig(
    style={...},
    animation={...},
    diarization={...},
)

# Using config objects
from beautiful_captions.core.config import StyleConfig, AnimationConfig, DiarizationConfig

config = CaptionConfig(
    style=StyleConfig(...),
    animation=AnimationConfig(...),
    diarization=DiarizationConfig(...),
)

StyleConfig

AnimationConfig

DiarizationConfig

Config Examples

Minimal — all defaults:

video = Video("input.mp4")
video.add_captions(srt_content=srt, output_path="output.mp4")

No animation, no scaling — plain constant-size text:

video = Video("input.mp4", config=CaptionConfig(
    animation={"enabled": False},
    style={"auto_scale_font": False},
))

Animation on, scaling off — constant size with no flicker:

video = Video("input.mp4", config=CaptionConfig(
    animation={"enabled": True},
    style={"auto_scale_font": False},
))

Animation off, scaling on — static size adapts to text length:

video = Video("input.mp4", config=CaptionConfig(
    animation={"enabled": False},
    style={"auto_scale_font": True},
))

Bounce animation with auto-scaling:

video = Video("input.mp4", config=CaptionConfig(
    animation={"enabled": True, "type": "bounce", "keyframes": 10},
    style={"auto_scale_font": True},
))

Multi-word lines (2 words per line):

video = Video("input.mp4", config=CaptionConfig(
    style={"max_words_per_line": 2},
))

Speaker diarization with custom colors:

video = Video("input.mp4", config=CaptionConfig(
    diarization={"enabled": True, "colors": ["yellow", "white"]},
))

Speaker labels visible:

video = Video("input.mp4", config=CaptionConfig(
    diarization={"enabled": True, "colors": ["red", "green"], "keep_speaker_labels": True},
))

Large font, no animation:

video = Video("input.mp4", config=CaptionConfig(
    style={"font_size": 200, "auto_scale_font": False},
    animation={"enabled": False},
))

Small font with bounce:

video = Video("input.mp4", config=CaptionConfig(
    style={"font_size": 80, "auto_scale_font": True},
    animation={"enabled": True},
))

Custom outline:

video = Video("input.mp4", config=CaptionConfig(
    style={"outline_thickness": 20, "outline_color": "blue"},
    animation={"enabled": False},
))

Bottom position:

video = Video("input.mp4", config=CaptionConfig(
    style={"verticle_position": 0.15},
))

Top position:

video = Video("input.mp4", config=CaptionConfig(
    style={"verticle_position": 0.85},
))

Profanity censoring:

video = Video("input.mp4", config=CaptionConfig(
    style={"censor_subtitles": True},
))

Custom censored words:

video = Video("input.mp4", config=CaptionConfig(
    style={
        "censor_subtitles": True,
        "custom_censored_words": {"damn": "d*mn", "hell": "h*ll"},
    },
))

Kitchen sink — everything combined:

video = Video("input.mp4", config=CaptionConfig(
    animation={"enabled": True, "type": "bounce", "keyframes": 15},
    style={
        "font": "Montserrat",
        "font_size": 120,
        "color": "white",
        "outline_color": "black",
        "outline_thickness": 10,
        "verticle_position": 0.5,
        "auto_scale_font": True,
        "max_words_per_line": 2,
        "censor_subtitles": False,
    },
    diarization={
        "enabled": True,
        "colors": ["yellow", "white", "red"],
        "max_speakers": 3,
        "keep_speaker_labels": False,
    },
))
video.add_captions(
    srt_content=subtitle_content,
    output_path="output.mp4",
    add_styling=True,
    cuda=False,  # Set True for NVIDIA GPU acceleration
)

Using with SRT file path:

video = Video("input.mp4", config=CaptionConfig(
    style={"auto_scale_font": False},
    animation={"enabled": False},
))
video.add_captions(srt_input_path="subtitles.srt", output_path="output.mp4")

Using with inline SRT content:

srt = """
1
00:00:00,000 --> 00:00:02,500
Speaker A: Hello world.

2
00:00:02,500 --> 00:00:05,000
Speaker B: How are you?
"""

video = Video("input.mp4", config=CaptionConfig(
    diarization={"enabled": True, "colors": ["yellow", "white"]},
    animation={"enabled": False},
    style={"auto_scale_font": False},
))
video.add_captions(srt_content=srt, output_path="output.mp4", add_styling=True)

License

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

Support

• 📫 For bug reports and feature requests, use GitHub Issues
• 💬 For questions and discussions, join our GitHub Discussions
• 🗳️ Vote on new features in our Ideas section