Skip to content

Latest commit

 

History

History
35 lines (26 loc) · 2.06 KB

README.md

File metadata and controls

35 lines (26 loc) · 2.06 KB

Minecraft-Mob-Detection

Description

This project aims to develop a classification model using TensorFlow and Convolutional Neural Networks (CNN) to distinguish between hostile and passive creatures of the game Minecraft.

Dataset

The dataset can be obtained from : https://universe.roboflow.com/minecraft-object-detection/minecraft-mob-detection/dataset/10

After downloading the dataset, extract it and place the three folders (train, valid, test) inside the data directory. The workspace structure should resemble the following :

data
 |- train
 |- valid
 |- test

Setup the Project

  1. Ensure you have Python installed on your system.

  2. Clone the repository:

    git clone [email protected]:Antoine-ValentinCharpentier/Minecraft-Mob-Detection.git
cd Minecraft-Mob-Detection

  3. Initialise the venv:

    python -m venv .venv
.venv\Scripts\activate OU source .venv/bin/activate
pip install -r requirements.txt

  4. Execute the script cnn.ipynb