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Classification model using TensorFlow and CNN to distinguish hostile/passive creatures of the game Minecraft

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Antoine-ValentinCharpentier/Minecraft-Mob-Detection

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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

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Classification model using TensorFlow and CNN to distinguish hostile/passive creatures of the game Minecraft

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