🎬 SUBGEN AI — Subtitle Generator (CLI)

---

🚀 Overview

SubgenAI is a lightweight and efficient command-line tool that uses OpenAI's Whisper model to automatically transcribe and generate subtitles (.srt) from video files.

✨ With a few simple commands, you can:

• Extract audio from any video
• Generate accurate subtitles
• Optionally translate them into English
• Save directly as .srt with automatic or custom file naming

---

✨ Features

• 🎯 Simple CLI – Run directly from your terminal
• 📝 Automatic Naming – Saves as video_name.srt if no output is specified
• 🌍 Translate to English – From any source language
• ⚡ Clean & Efficient – Uses temporary storage and cleans up automatically
• 🔄 Flexible Models – Choose from tiny, base, small, medium, large

---

🛠️ Tech Stack

• Language: Python
• Transcription: OpenAI Whisper
• Audio Extraction: FFmpeg

---

📦 Prerequisites

Before using SubgenAI, make sure you have:

• 🐍 Python 3.8+
• 🎵 FFmpeg (required for audio extraction)

🔧 Installation Instructions

• Windows: Download from the official FFmpeg site and add the bin folder to PATH
• macOS (Homebrew):

  brew install ffmpeg

• Linux (apt):

  sudo apt update && sudo apt install ffmpeg

---

⚙️ Installation & Setup

Clone the repository:

git clone https://github.com/nfs-tech-bd/subgenAI
cd subgenAI

Create and activate a virtual environment (recommended)

Windows:

python -m venv venv
.\env\Scripts\ctivate

macOS / Linux:

python3 -m venv venv
source venv/bin/activate

Install dependencies:

pip install -r requirements.txt

⚠️ The first time you run the script, Whisper will download the chosen model (default = base).

---

▶️ Usage

Basic (Automatic Output Name)

python subgenai.py --video "my_video.mp4"

👉 Output: my_video.srt

Specify Output File

python subgenai.py --video "my_video.mp4" --output "custom_subs.srt"

Choose a Model

python subgenai.py --video "my_video.mp4" --output "custom_subs.srt" --model "medium"

---

📊 Model Trade-offs

Model	Speed 🚀	Accuracy 🎯	Size 💾
tiny	Fastest	Lowest	~75 MB
base	Fast	Medium	~142 MB
small	Balanced	Good	~466 MB
medium	Slower	Very Good	~1.5 GB
large	Slowest	Best	~3 GB

---

📜 License

This project is licensed under the MIT License.

---

💡 Built with ❤️ by Nafis Fuad with python and a lot of curiosity.