Disclaimer:
All data included in this repository (including any CSV or Excel files) is dummy data and does not represent real individuals or organizations.

SeaDat is a free tool designed to showcase how one could search, analyze, and visualize structured data. It does not provide or distribute any real breached or sensitive data. If you wish to experiment with real-world datasets, you must acquire them yourself and put it there. There's the misc tools for you to use xlsx to csv.

• Employee Data Search: Search and filter dummy employee data by name or across all fields.
• AI Search: Use natural language queries powered by GPT-4o (via aimlapi.com) to find and analyze data.
• IP Address Tracker: Lookup IP address information, including geolocation and network details.
• Instagram Profile Lookup: Retrieve public Instagram profile information using multiple scraping methods.
• Image Search (Face Recognition): Search for faces in images using a simple face recognition system.
  • Note: The included training dataset is very simple and only contains 6 people: tupac shakur, 21 savage, 50 Cent, donald trump, joe biden, and eminem (as stored in face_db_cache.pkl).

1. Clone the repository:

   git clone https://github.com/awiones/SeaDat.git
   cd SeaDat

2. Install Python (recommended: Python 3.8 or newer).

3. Install dependencies:

   pip install -r requirements.txt

Run the main program:

python main.py

• All sample data is randomly generated and stored in the data/ directory.
• You can convert your own .xlsx files to .csv using the provided script.

This project is licensed under the MIT License.

SeaDat
Created by awiones