peg-this 4.1.0

A powerful and intuitive command-line video editor, built on FFmpeg.

FFmPEG-this

Your Editor within CLI

A powerful and user-friendly Python CLI tool for converting, manipulating, and inspecting media files using the power of FFmpeg. This tool provides a simple command-line menu to perform common audio and video tasks without needing to memorize complex FFmpeg commands.

Features at a Glance

Category	Feature	Description
Inspect	Media Properties	View detailed codec, resolution, frame rate, bitrate, and stream information
Convert	Video Formats	Convert to MP4, MKV, MOV, AVI, WebM with quality presets (CRF 18/23/28)
	Audio Formats	Convert to MP3 (128k-320k bitrate), FLAC, WAV
	GIF Creation	Convert video clips to animated GIFs with optimized palette
	Image Formats	Convert between JPG, PNG, WebP, BMP, TIFF with quality control
Subtitles	AI Transcription	Generate subtitles using Whisper AI (7 model sizes available)
	Sidecar Export	Save as .srt, .vtt, .txt, or .lrc files
	Soft Subtitles	Embed toggleable subtitle track into video
	Hard Subtitles	Burn permanent subtitles directly into video
	Multi-language	Support for 99+ languages with auto-detection
Edit	Trim/Cut	Extract video segments by start/end time (lossless, no re-encoding)
	Visual Crop	Interactive GUI to select crop area on video/image
	Join/Concatenate	Merge multiple videos with automatic resolution matching
Audio	Extract Audio	Rip audio track to MP3, FLAC, or WAV
	Remove Audio	Create silent version of video (keeps video intact)
Image	Resize	Scale images with aspect ratio preservation
	Rotate	Rotate 90°, 180°, or 270°
	Flip	Flip horizontally or vertically
	Crop	Visual cropping with click-and-drag selection
Batch	Batch Convert	Convert all media files in directory at once

Detailed Feature Breakdown

Video Operations

Operation	Input	Output	Method	Re-encoding
Convert	Any video	MP4, MKV, MOV, AVI, WebM	FFmpeg transcode	Yes (CRF quality)
Trim	Any video	Same format	Stream copy	No (lossless)
Crop	Any video	Same format	Visual selection + crop filter	Yes
Join	Multiple videos	Single MP4	Concat filter + normalize	Yes
To GIF	Any video	Animated GIF	2-pass palette optimization	Yes

Audio Operations

Operation	Input	Output	Notes
Extract	Video with audio	MP3, FLAC, WAV	Preserves original quality for FLAC/WAV
Remove	Video with audio	Silent video	Stream copy (fast, no re-encoding)
Convert	Audio file	MP3, FLAC, WAV	Bitrate selection for MP3

Subtitle Generation

Model	Size	Speed	Accuracy	Languages
tiny.en	~75 MB	Fastest	Good	English only
base.en	~150 MB	Fast	Better	English only
small.en	~500 MB	Balanced	Great	English only
medium.en	~1.5 GB	Slower	Excellent	English only
small	~500 MB	Balanced	Great	99+ languages
medium	~1.5 GB	Slower	Excellent	99+ languages
large-v3	~3 GB	Slowest	Best	99+ languages

Output Options:

Type	File Extension	Description
Sidecar	.srt	SubRip - most compatible format
Sidecar	.vtt	WebVTT - for web/HTML5 players
Sidecar	.txt	Plain text transcript
Sidecar	.lrc	Lyrics format with timestamps
Soft Subs	.mp4/.mkv	Embedded, toggleable in players
Hard Subs	.mp4/.mkv	Burned in, always visible

Image Operations

Operation	Options	Notes
Convert	JPG, PNG, WebP, BMP, TIFF	Quality presets (95%, 80%, 60%)
Resize	Custom width/height	Use -1 to preserve aspect ratio
Rotate	90° CW, 90° CCW, 180°	Lossless rotation
Flip	Horizontal, Vertical	Mirror image
Crop	Visual selection	Interactive GUI with preview

Supported Formats

Type	Supported Formats
Video Input	.mp4, .mkv, .avi, .mov, .webm, .flv, .wmv, .gif
Video Output	.mp4, .mkv, .mov, .avi, .webm, .gif
Audio Input	.mp3, .flac, .wav, .ogg, .aac, .m4a
Audio Output	.mp3, .flac, .wav
Image Input	.jpg, .jpeg, .png, .webp, .bmp, .tiff
Image Output	.jpg, .png, .webp, .bmp, .tiff
Subtitle Output	.srt, .vtt, .txt, .lrc

Usage

Prerequisite: Install FFmpeg

[!NOTE] peg_this uses a library called ffmpeg-python which acts as a controller for the main FFmpeg program. It does not include FFmpeg itself. Therefore, you must have FFmpeg installed on your system and available in your terminal's PATH.

For macOS users, the easiest way to install it is with Homebrew:

brew install ffmpeg

For Windows users, you can use a package manager like Chocolatey or Scoop:

# Using Chocolatey
choco install ffmpeg

# Using Scoop
scoop install ffmpeg

For other systems, please see the official download page: ffmpeg.org/download.html

There are three ways to use peg_this:

1. Pip Install (Recommended)

This is the easiest way to get started. This will install the tool and all its dependencies.

pip install peg_this

Once installed, you can run the tool from your terminal:

peg_this

2. Download from Release

If you prefer not to install the package, you can download a pre-built executable from the Releases page.

1. Download the executable for your operating system (Windows, macOS, or Linux).
2. Place it in a directory with your media files.
3. Run the executable directly from your terminal.

3. Run from Source

If you want to run the tool directly from the source code:

1. Clone the repository:

   git clone https://github.com/hariharen9/ffmpeg-this.git
   cd ffmpeg-this
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the tool:

   python -m src.peg_this.peg_this
   

Subtitle Generation

The subtitle feature uses faster-whisper, a fast and accurate speech-to-text engine powered by OpenAI's Whisper model.

How it works

1. Select a video file
2. Choose "Generate Subtitles (Whisper)"
3. Pick a model size (tiny to large-v3)
4. Select processing mode (Fast or Accurate)
5. Choose output type:
   • Sidecar file: Export as .srt, .vtt, .txt, or .lrc
   • Soft subtitles: Embed into video (can be toggled on/off in players)
   • Hard subtitles: Burn into video (permanent, always visible)

Supported Languages

Using multilingual models (small, medium, large-v3), you can transcribe audio in 99+ languages including English, Spanish, French, German, Chinese, Japanese, Korean, Hindi, Arabic, and many more.

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Contributors

Contributing

Contributions are welcome! Please see the Contributing Guidelines for more information.

License

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

Made with ❤️ by Hariharen