/coffee-ai

Primary LanguagePython

This is how you should structure your data models.

dataset/
    train/
        unripe/
            unripe_image1.jpg
            unripe_image2.jpg
            ...
        semi-ripe/
            semi_ripe_image1.jpg
            semi_ripe_image2.jpg
            ...
        ripe/
            ripe_image1.jpg
            ripe_image2.jpg
            ...
        overripe/
            overripe_image1.jpg
            overripe_image2.jpg
            ...
    test/
        unripe/
            unripe_image1.jpg
            unripe_image2.jpg
            ...
        semi-ripe/
            semi_ripe_image1.jpg
            semi_ripe_image2.jpg
            ...
        ripe/
            ripe_image1.jpg
            ripe_image2.jpg
            ...
        overripe/
            overripe_image1.jpg
            overripe_image2.jpg
            ...

This works best with NVIDIA GPUs that supports CUDA.

Installation

  • Install the required packages 
    pip install -r requirements.txt
  • Install CUDA and cuDNN if you have an NVIDIA GPU

Usage

  • Inorder to get accurate results, run trainer.py and strucutre your dataset as shown above
  • To run the model on your own dataset, change the path in trainer.py to your dataset path
  • To use the trained model replace the model variable as below 
      from keras.models import load_model

  # Load the saved model from the .h5 file
  model = load_model('path/to/model.h5')

  # Use the loaded model to make predictions
  predictions = model.predict(data)

Setup

  • Open a terminal inside the directory and run the python venv module to create a virtual environment 
    python -m venv venv
    • Activate the virtual environment
      • Windows 
        venv\Scripts\activate
      • Linux 
        source venv/bin/activate
  • Install the required packages 
    pip install -r requirements.txt
  • Install CUDA and cuDNN if you have an NVIDIA GPU (OPTIONAL)
  • Run the trainer.py file 
    cd trainer && python trainer_gui.py
  • After training the models you can run the main file 
    cd .. && python main.py