Minecraft Ore Detection using YOLOv4-tiny

This implements a real-time ore detection system in Minecraft using the YOLOv4-tiny neural network. The system analyzes the game screen to highlight ores, making resource gathering easier for players.

Features

• Real-time detection of Minecraft ores.
• Utilizes YOLOv4-tiny for fast and efficient object detection.
• Customizable for different Minecraft versions and resource packs.

Prerequisites

• Python 3.6 or higher
• OpenCV
• TensorFlow
• PyTorch
• Other dependencies in requirements.txt

Installation

1. Clone the repository:

   git clone https://github.com/M117n/minecraft_ore_dectect.git

2. Navigate to the project directory:

cd minecraft_ore_dectect

3. Install the required dependencies:

pip install -r requirements.txt

##Usage

1. Start Minecraft in windowed mode.
2. Run the detection script:

python detect.py

3. The script will display a real-time feed with highlighted detected ores.

Configuration

• Edit config.yaml to adjust parameters like confidence thresholds, model paths, or screen capture settings.

Contributing

Contributions are welcome! Please fork the repository, create a new branch, and submit a pull request.

License

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

Acknowledgments

1. YOLOv4-tiny for the base detection model.
2. OpenCV and TensorFlow communities for their tools and documentation.

##Contact For any questions or suggestions, please open an issue or contact the repository owner directly.