🤖 AI-Trainer

AI-Trainer is a comprehensive project designed to develop and deploy an AI-powered trainer. This repository includes scripts for dataset creation, data cleaning, and model training to facilitate the building and training of AI models. 📋 Table of Contents

Project Overview
Installation
Usage
    Data Preparation
    Data Cleaning
    Model Training
Repository Structure
Contributing
License

🌟 Project Overview

The AI-Trainer project aims to create a robust AI system for training purposes. It involves:

Creating datasets.
Cleaning and preprocessing data.
Implementing and training AI models.

🛠️ Installation

Follow these steps to set up the project locally:

Clone the repository:

bash

git clone https://github.com/showMiko/AI-Trainer.git cd AI-Trainer

Install the required dependencies:

bash

pip install -r numpy
pip install -r pandas
pip install -r opencv
pip install -r mediapipe

🚀 Usage 📂 Data Preparation

Generate your datasets using the DataSetCreation.py script:

bash

python DataSetCreation.py

🧹 Data Cleaning

Clean your data using the dataclean.ipynb notebook. Open it in Jupyter Notebook or any compatible environment and run the cells step-by-step to clean your dataset. 🏋️ Model Training

Train your AI models using the provided training scripts. For example:

bash

python Sample2.py

📁 Repository Structure

DataSetCreation.py: Script for generating datasets.
dataclean.ipynb: Notebook for data cleaning.
landmarks.py: Script for processing landmarks in data.
data.csv, Cleaneddata.csv, Final.csv: Various datasets.
Rajo.mp4, Rajo2.mp4: Sample video files for model training.
Sample2.py: Example script for training models.

🤝 Contributing

Contributions are welcome! Please fork this repository and submit pull requests. For major changes, open an issue first to discuss what you would like to change. 📜 License

This project is licensed under the MIT License.