Fish Species Image Classification

This project focuses on classifying fish species using deep learning techniques. It utilizes a convolutional neural network (CNN) built with TensorFlow and Keras to accurately identify different types of fish from images.

Dataset

The dataset used is sourced from a large-scale fish dataset available on Kaggle. It contains images of various fish species, including:

Hourse Mackerel
Black Sea Sprat
Sea Bass
Red Mullet
Trout
Striped Red Mullet
Shrimp
Gilt-Head Bream
Red Sea Bream

Features

Data preprocessing and augmentation using TensorFlow's ImageDataGenerator.
Neural network built using the Sequential model from Keras.
Performance evaluation using metrics such as accuracy, confusion matrix, and classification report.

Results

The trained model will generate performance metrics such as:

Accuracy
Confusion Matrix
Classification Report

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Acknowledgments

Dataset provided by Kaggle.
Thanks to the contributors of TensorFlow, Keras, and scikit-learn.