Categorical Image Recognition using Fastai

This project is a categorical image recognition model built using Fastai and ResNet architecture. It includes steps to download images, preprocess them, and train a model to classify images into multiple categories.

Project Demo

Project Structure

• categorial-image-recognition-fastai.ipynb: Jupyter Notebook containing the model training and evaluation code.
• requirements.txt: List of Python packages required to run the project.
• .gitignore: Specifies files and directories to be ignored by Git.

Installation

1. Clone the repository:

   git clone https://github.com/waijian1/ImageRecognitionFastAI.git

2. Install the required packages:

   pip install -r requirements.txt

3. Run the notebook:

   jupyter notebook categorial-image-recognition-fastai.ipynb

Usage

• Run the notebook to download images, preprocess data, train the model, and perform categorical image recognition.

License

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