Classify Apple Pytorch 1.7

This project for classify green and red apples by using Pytorch 1.7 and test model and print confusion matrix parameters.

Data Set

Fruits 360 dataset: A dataset of images containing fruits and vegetables https://www.kaggle.com/datasets/moltean/fruits

Only used green and red apple data set in this project.That means we have two clases. Sample of images:

Clone

We begin by cloning the classify_apple repository and setting up the dependencies required to run. You might need sudo rights to install some of the packages.

In a terminal, type:

git clone https://github.com/kadircosar/classify_apple.git

İnstall requirements

I recommend you create a new conda or a virtualenv environment to run your classify_apple as to not mess up dependencies of any existing project. Once you have activated the new environment, install the dependencies using pip.

Before running this code in terminal make sure activate your venv that you created for this project and run this code in path that you cloned classify_apple.

pip install -r requirements.txt

Run Model

Now you can run model. Activate venv and run this code in path that you cloned classify_apple.

Run with terminal:

python3 model.py

Train Results

Test Results, Confusion Matrix