🐶 Dog AI

https://user-images.githubusercontent.com/30840709/133912996-73859a5d-dd06-4c92-a964-ba5dd2773b66.mp4

💡 Project

Recognize over 100 dog breeds by drag and drop an image using Tensorflow.js and Teachable Machine.

🛠 Tools

• React
• React Dropzone
• Tensorflow.js
• Teachable Machine

💻Demo

https://dogai.netlify.com

🚀Quick start

Installation

$ git clone git@github.com:jeferson-sb/dogAI.git && cd dogAI
$ npm install

Usage

$ npm run start

Tests

$ npm run test

Linting

$ npm run lint:js
$ npm run lint:css

How to Train your own model

1. Gather a dataset with a bunch of images
2. Resize and minify all the images
3. Separate dogs image by breed and rename all the files
4. Upload to Teachable Machine
5. Train your model
6. Export your trained model

Dataset Reference

Primary: Aditya Khosla, Nityananda Jayadevaprakash, Bangpeng Yao and Li Fei-Fei. Novel dataset for Fine-Grained Image Categorization. First Workshop on Fine-Grained Visual Categorization (FGVC), IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011.

Secondary: J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li and L. Fei-Fei, ImageNet: A Large-Scale Hierarchical Image Database. IEEE Computer Vision and Pattern Recognition (CVPR), 2009.

📝License

This project is licensed under the MIT License