How to Make Rock Paper Scissor Game in Python?

Looking for a fun way to kill some time? Check out this tutorial on how to make your own rock paper scissor game in Python. In this tutorial, we’ll cover everything you need to know to create a simple but fun game that can be used as a learning tool or for entertainment.

Description:-

I am sure y’all know about the cool Rock Paper Scissors game that kids are commonly seen playing. It’s a classic two-player game. Each player chooses either rock, paper, or scissors.

Rock beats scissors, Scissors beats paper, Paper beats rock!!

To play Rock Paper Scissors, two players must stand facing each other. They then make their move at the same time. The player who chooses the shape that beats the other player wins that round. If both players choose the same item, then the game is a tie.

Ever wondered if you could create your own AI-based Rock Paper Scissors Game? Yes, it is possible to create your own AI-based Rock Paper Scissors game. To create this game, you will need to use a programming language such as Python or Java to create the game logic. You will also need to use a machine learning library to create the AI model that will make decisions based on the game data. Thereafter, you will need to create a user interface to allow the user to play the game. Once the game is ready, you can use it to test different AI models and compare their performance.

So, what’s the wait for why not build an AI-based Rock Paper Scissor Game that you can play with whenever you want? Let’s begin! Gather Data, for rock, and paper scissors classes and follow the steps given below.

Steps to Make Rock Paper Scissor Game in Python

The task can mainly be divided into three major steps viz.

• Collect and Process the Data
• Build a suitable AI Model
• Deploy for use/Test on Live Webcam Feed
• Let us now discuss these steps in detail.

Collect and Process Data:

It’s important to collect and process the data in order to create a successful model. First, it is important to collect the data from reliable sources. Then, the data needs to be cleaned and organized so that it can be used in the model. Additionally, the data needs to be split into training, validation, and testing datasets. Finally, the data must be processed and transformed into a format that can be used by the Deep Learning model.

Step 1. Capture and gather sample images from a webcam.

Note: We have used Python’s OpenCV library for camera-related operations. A key point to note is that all my images are of 500 x 500 dimensions.

(II) Build a suitable AI Mode

Step 2. Now, make a model to train our data set.

2.Define file path & map classes which are saved in image data

3.Define file path & map classes which are saved in image data

What is Convolutional Neural Network (ConvNet/CNN)?

CNN is a Deep Learning algorithm which can take in an input image, assign importance (learnable weights and biases) to various aspects/objects in the image and be able to differentiate one from the other. The architecture of CNN works on the principle of ‘receptive fields’ which are the area of the image being considered for further processing.

The convolutional layers are made up of a set of filters which pick up the patterns from the image and pass it on to the next layer.

The pooling layers help reduce the spatial size of the representation to reduce the amount of parameters and computation in the network.

The fully connected layers include all the neurons from the previous layers to compute the probabilities of the various classes.

This architecture is used for computer vision tasks such as object detection, recognition, segmentation etc.

4. Collect images from the dataset to train the model to predict pictures in the real-time camera.

5. A computer understands numbers; thus we have to convert these images into their vector representation using one hot encoding.

6. Call the model function with the model variable and train the model with the respective data set.

(III) Test on Live Webcam Feed

Step 3. Now, use trained models to play games with AI.

1. Import Keras model function and OpenCV.

2. Define mapping classes.

3. Make a function for returning winning conditions for the user and computer.

4. Predict the move from the trained model.

Output:-

Conclusion:-

Creating a Rock Paper Scissors game in Python is a great way to learn the fundamentals of programming. By following the steps outlined in this guide, you can create a game that is fun, challenging, and easy to understand. You can customize the game to your specifications with a few modifications. With some practice, you can have a great game of Rock Paper Scissors in no time!