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🐱 Abyssinian Cat Classifier and Captioning Project 🎉

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Welcome to the Abyssinian Cat Classifier and Captioning Project! 🚀 This open-source initiative aims to develop robust machine learning models to classify Abyssinian cats 🐈 from images and generate captions describing their actions and features. Our goal is to create a high-quality, diverse dataset of cat images that can be used to train models to detect and describe Abyssinian cats accurately.

Ruby

🌟✨ Meet Ruby, Our Muse 🐾🎉

Meet "Ruby," a dazzling Abyssinian cat 🐈 born on October 21, 2020, who has become the inspiration 💡 behind this project. Ruby is a female who absolutely adores people. Her eyes sparkle ✨ like rubies💎, which is how she got her name—not from the programming language, Ruby, mind you! (Just a little joke 😄).

Ruby is like a beloved little sister in our home 🏡, incredibly cute 🥰 and beautiful. It's our hope that many cat lovers ❤️ and owners will join and contribute to this project, sharing the joy 🎊 Ruby brings into our lives. If you're a cat enthusiast, let Ruby's story inspire you to participate 🙌 and help advance this project. Together, let's make this a fun 🎉 and fruitful 🍎 endeavor for all!

We believe that by sharing stories like Ruby's, we can create a community 🌐 that not only contributes to this project but also shares in the delight 🎈 of our feline friends.

🎯 Project Objectives

  • 📸 Data Collection: Compile a comprehensive dataset of cat images, focusing on gathering over 1000 images for various predefined poses of Abyssinian cats.
  • 🔍 Classification: Develop a classifier that can accurately distinguish Abyssinian cats from other breeds.
  • 📝 Captioning: Implement a captioning model that can describe the features and behaviors of cats in images, with a focus on Abyssinian specific traits.
  • 🚀 Performance Enhancement: Improve the models' ability to detect and caption Abyssinian cats from low-resolution images and enhance the detection capabilities to recognize cats from as small pixel dimensions as feasible.

Contributing

We welcome contributions from cat enthusiasts, AI researchers, and developers. Here's how you can contribute:

  1. Data Collection: Upload your cat images to the designated dataset folder. Ensure the images meet the quality standards outlined in our contribution guidelines.
  2. Model Development: Contribute to developing and refining the classification and captioning models.
  3. Testing and Feedback: Test the models and provide feedback on model accuracy and performance, especially in handling low-resolution images.

🌟 Getting Started

Prerequisites

  • Python 3.8 or higher 🐍
  • TensorFlow 2.x 🧠
  • PyTorch 1.x 🔥
  • PIL for image processing 🖼️
  • NumPy for numerical operations 🔢

🛠 Installation

Clone the repository and install the required packages:

git clone https://github.com/jamesjang26/Cat-Saves-the-World.git
cd Cat-Saves-the-World
pip install -r requirements.txt