https://github.com/snenenenenenene/pet-classification
The goal of the project is to provide a practical and easy-to-use tool for pet enthusiasts to identify and learn about different breeds of pets by using Machine Learning.
https://github.com/snenenenenenene/pet-classification
classification-model h5 prediction-model react tensorflow
Last synced: 2 months ago
JSON representation
The goal of the project is to provide a practical and easy-to-use tool for pet enthusiasts to identify and learn about different breeds of pets by using Machine Learning.
- Host: GitHub
- URL: https://github.com/snenenenenenene/pet-classification
- Owner: snenenenenenene
- Created: 2021-10-08T09:43:55.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2023-03-23T19:35:09.000Z (over 3 years ago)
- Last Synced: 2025-02-02T16:42:13.372Z (over 1 year ago)
- Topics: classification-model, h5, prediction-model, react, tensorflow
- Language: Jupyter Notebook
- Homepage: https://pet-prediction.vercel.app/
- Size: 84.6 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## Pet Classification
It happens more often than not - especially to animal & pet lovers such as myself - that you come across the most beautiful dog while going for a walk in the park -- or whenever you're mindlessly scrolling Facebook for hours.
This project is a digitalised manifestation of your gung ho pet breed connoisseur from around the corner. How? Through the means of **Machine Learning** (ML).
Nevertheless, to take into account the target audience and pragmatism of this implementation, I have chosen to pair the aforementioned notebook with [a frontend developed in React](https://pet-prediction.vercel.app/) in order to evade the convoluted process of having to manually import images into the model -- which is still an option if you're into self-loathing.
The dataset used in this project is the [Animal Breed - Cats and Dogs](https://www.kaggle.com/imsparsh/animal-breed-cats-and-dogs) dataset from Kaggle.
### Contents
- **app**: This contains the React project which makes the user experience a lot more intuitive and accessible as oppose to look at the Jupyter Notebook. It was was last updated on 23/03/2023.
- **models**: The collection of h5-exported tensorflow models which are used inside of the React app.
- **notebook.ipynb**: The notebook which contains the entire documentation of the creation of the exported model.
### Getting Started
#### Prerequisites
- Node.js v18 or later
- Python 3.0
- Tensorflow
- Jupyter Notebook
#### Installation
- Clone this repository: `git clone https://github.com/snenenenenenene/pet-classification`
- Run the jupyter notebook with the data from [Animal Breed - Cats and Dogs](https://www.kaggle.com/imsparsh/animal-breed-cats-and-dogs) in the `/breeds` folder.
- Change into the directory: `cd ./pet-classification`
- Install dependencies: `npm install`
#### Running the Application
- Change into the React app: `cd app`
- Start the development server: `npm run dev`
- Open the application in your browser at http://localhost:3000
### Data Source
This dataset was created using publicly available data from the Kaggle. The original data was obtained from [Animal Breed - Cats and Dogs](https://www.kaggle.com/imsparsh/animal-breed-cats-and-dogs)