- Introduction
Source image by Machinethink.net
This dataset contains images of hand gestures from the Rock-Paper-Scissors game. The images were captured as part of a hobby project where I developped a Rock-Paper-Scissors game using computer vision and machine learning on the Raspberry Pi. You can download dataset to (https://github.com/DrGFreeman/rps-cv). This project is the final project of my submission at Dicoding Indonesia.
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Dataset
In this dataset, there are 3 data classes namely Rock, Paper, and Scissors with 2188 images. The dataset you use in the .zip format to download it and you can extract it depends on how you use the dataset in the image classification. The dataset you use has a 300x200 pixel image size in PNG format. You can download it at the Kaggle site or DrGFreeman's GitHub repository in (https://github.com/DrGFreeman/rps-cv).
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Usage
For the use of this dataset with the methods, you have applied such as Deep Learning or other methods in Computer Vision and Image Processing. You can use the code execution tool with Google Collaboratory, Jupyter Notebook, Spyder, PyCharm, RStudio, Microsoft Visual Studio Code, and others.
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Method
In this method, I am using the Deep Learning method for image classification, the Convolutional Neural Network (CNN) model. If you don't understand CNN algorithm theory. You can see how this method works on the Medium or Towards Data Science website in (https://towardsdatascience.com/covolutional-neural-network-cb0883dd6529).