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Pesplanus Image Classification Using CNN

Requirements

  • Python 3.11
  • PyTorch 2.1.2
  • OpenCV (cv2)
  • Tensorboard
  • NumPy

Introduction

This project implements a Convolutional Neural Network (CNN) for image classification, specifically designed for classifying images related to Pesplanus.

Usage

  1. Ensure you have all the necessary requirements installed.
  2. Clone this repository to your local machine.
  3. Navigate to the project directory.
  4. Run the Python script responsible for training and testing the CNN.
  5. Monitor the training process using Tensorboard.
  6. Evaluate the model's performance on test data.

About Pesplanus

Pesplanus is a term used to describe a certain category of images. More information about the dataset and its characteristics can be found here.

Training

  • For training the CNN, use the provided training script (train.py).
  • Adjust hyperparameters and network architecture as needed.
  • Monitor the training process using Tensorboard for insights into loss and accuracy trends.

Testing

  • After training, evaluate the model on test data using the testing script (test.py).
  • Analyze performance metrics such as accuracy, precision, and recall.

Contributing

Contributions are welcome! Please fork this repository and submit pull requests with any improvements or additional features.

License

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