AI Image Classifier

This repository contains an AI-based image classification project built using TensorFlow/Keras and OpenCV. The model is trained to classify images into different categories and can be used for various applications, such as object recognition and automated tagging.

Features

• Uses Convolutional Neural Networks (CNNs) for image classification
• Preprocessing and augmentation using OpenCV
• Training and evaluation using TensorFlow/Keras
• Supports model saving and loading
• Simple command-line interface for predictions

Installation

To get started, clone the repository and install the required dependencies:

git clone https://github.com/imskylab/ai-image-classifier.git
cd ai-image-classifier
pip install -r requirements.txt

Dataset Preparation

Ensure you have a dataset of images organized into labeled folders:

/dataset/
    /class_1/
        image1.jpg
        image2.jpg
    /class_2/
        image1.jpg
        image2.jpg

You can modify the dataset path in the script accordingly.

Training the Model

To train the model, run the following command:

python train.py --dataset ./dataset --epochs 10 --batch_size 32

Adjust parameters as needed.

Making Predictions

To classify an image using the trained model:

python predict.py --image sample.jpg

Model Evaluation

Evaluate the trained model on a test dataset:

python evaluate.py --test_dataset ./test_dataset

Saving and Loading Models

The model is saved in the models/ directory after training. You can load a saved model for inference:

from tensorflow.keras.models import load_model
model = load_model('models/image_classifier.h5')

Contributing

Contributions are welcome! Feel free to fork this repository and submit a pull request with improvements.

License

This project is licensed under the MIT License.

Contact

For any queries, reach out to yentraj@gmail.com.