🎙️ Transcripto

A simple Streamlit app that transcribes videos into text using OpenAI’s Whisper model.

🌐 Live Demo on Streamlit Cloud

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🎬 Demo

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✨ Features

• 🎥 Upload video files (.mp4, .avi, .mov, .mkv)

• 🔊 Automatic audio extraction with ffmpeg

• 🧠 Transcribe speech into text using Whisper

• ⏱️ Accurate timestamps in hh:mm:ss.ms format

• 📥 Export transcription as:

  • .txt (Plain Text)
  • .docx (Word Document)
  • .pdf (Portable Document Format)

• ☁️ Free deployment on Streamlit Cloud

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📸 Screenshots & Demo

🔹 Uploading a Video

🔹 Transcription Output

🔹 Download Options

(You can also add a short GIF demo made with ScreenToGif or OBS Studio for better presentation.)

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📂 Project Structure

transcripto/
│── app.py              # Main Streamlit app
│── requirements.txt    # Python dependencies
│── packages.txt        # System packages (for Streamlit Cloud, includes ffmpeg)
│── runtime.txt         # Python runtime version (for Streamlit Cloud)
│── README.md           # Documentation
│── assets/             # Screenshots & demo GIFs

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🚀 Usage

🔗 Online (Recommended)

1. Open the app 👉 Live Demo
2. Upload your video file
3. Select a Whisper model size (tiny → large) 🔧 Tip: Use tiny or small for quick tests. Use medium or large for higher accuracy (but requires more time/memory).
4. Wait for transcription to finish
5. Download your transcript in .txt, .docx, or .pdf

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🛠️ Installation (Local)

1. Clone repo

git clone https://github.com/fns12/transcripto.git
cd transcripto

2. Create & activate virtual environment

python -m venv venv
source venv/bin/activate   # Mac/Linux
venv\Scripts\activate      # Windows

3. Install dependencies

pip install -r requirements.txt

4. Install ffmpeg

• Linux/macOS

  sudo apt-get install ffmpeg

• Windows → Download from ffmpeg.org and add to PATH

5. Run the app

streamlit run app.py

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☁️ Deployment (Streamlit Cloud)

This app is deployed on Streamlit Cloud:

• requirements.txt → Python dependencies
• packages.txt → includes ffmpeg so Streamlit installs it automatically
• runtime.txt → sets Python version (3.9)

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🔄 Development Workflow

• ✅ Prototyped on Google Colab (to avoid RAM/GPU issues)
• ✅ Used ngrok for temporary live demos during testing
• ✅ Final version copied into app.py, pushed to GitHub
• ✅ Deployed on Streamlit Cloud for free & easy sharing

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📝 Example Transcript

[00:00:01.200 → 00:00:03.450] Hello everyone, welcome to this session.
[00:00:04.000 → 00:00:06.150] Today we will be testing transcription.

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📜 License

MIT License — Free to use and modify.