https://github.com/chiragsaini/rock-paper-scissors

This is teachable rock paper scissors web app, which is using tensorflowjs and mobilenet to classifiy various actions of hand into rock , paper and scissors.
https://github.com/chiragsaini/rock-paper-scissors

coursera-specialization deep-learning javascript mobilenet tensorflow tensorflowjs

Last synced: 7 months ago
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This is teachable rock paper scissors web app, which is using tensorflowjs and mobilenet to classifiy various actions of hand into rock , paper and scissors.

• Host: GitHub
• URL: https://github.com/chiragsaini/rock-paper-scissors
• Owner: ChiragSaini
• Created: 2019-12-31T07:28:29.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2020-04-26T11:27:15.000Z (over 5 years ago)
• Last Synced: 2025-01-19T10:43:26.627Z (9 months ago)
• Topics: coursera-specialization, deep-learning, javascript, mobilenet, tensorflow, tensorflowjs
• Language: JavaScript
• Homepage:
• Size: 451 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Rock-Paper-Scissors

This is teachable rock paper scissors web app, which i using tensorflowjs and mobilenet to classifiy various action of hand into rock , paper and scissors.

This project is a part of the Deep Learning Specilization course from Coursera.

#### How to use APP:

```bash

  1. Collect Samples of various rock paper scissors images

  2. Train network and wait for the alert

  3. Click on start predicting to start the prediction using webcam

```

##### Watch Live Demo  here  

## Files:

#### Page.html

First is page.html which basically has all the front end related stuff regrading this app.

#### Index.js

Index.js is the main js file which handles the downloading , loading and transfer learning from mobilenet into our application.

We can train this mobilenet and train it according to our need.

#### Webcam.js

This webcam.js is a js file made by Google to handle all the webcam related stuff

#### RPS-Dataset.js

This file is helping to create the dataset of the intermediate images from our mobilenet and labels for our neural network.

## Screenshots:

##### Predicting Paper

![alt-text](paper.PNG)

##### predicting Scissors

![alt-text](scissors.png)