# Build an ML Rock Paper Scissors Game with Lobe
## Overview
Classify hand gestures to play Rock, Paper, Scissors on your Pi using computer vision and machine learning! Lobe is a free, easy to use app that lets you train custom machine learning (ML) models without any code. [Download Lobe here](https://lobe.ai/).
In this tutorial, we'll build a Rock, Paper, Scissors ML model and play against our Pi. The game will classify your hand gesture using the Pi camera, let the computer randomly pick one, and determine who the winner is.
This is a fun introduction to building interactive ML models with Lobe on the Pi. Use this as a starting point to explore your own ideas!
This tutorial is part of a series which includes:
- [Tutorial 1: Machine Learning 101 with Lobe and Raspberry Pi](https://learn.adafruit.com/lobe-braincraft)
- [Tutorial 3: Build an ML Package Detector with Lobe](https://learn.adafruit.com/build-an-ml-package-detector)
## Background Knowledge
New to using Lobe? Check out our introductory tutorial:
- [Tutorial 1: Machine Learning 101 with Lobe and Raspberry Pi](https://learn.adafruit.com/lobe-braincraft)
We also recommend that you have familiarity with the following topics:
1. Setting up and using the Raspberry Pi
2. Some experience terminal window
3. Some experience with Python
- [Next Page](https://learn.adafruit.com/lobe-rock-paper-scissors/required-parts.md)
## Featured Products
### Microsoft Machine Learning Kit for Lobe - Pi 4 Not Included
[Microsoft Machine Learning Kit for Lobe - Pi 4 Not Included](https://www.adafruit.com/product/4949)
Machine learning is a transformative tool that’s redefining how we build software—but up until now, it was only accessible to a small group of experts. At Adafruit, we think machine learning should be accessible to everyone, that’s why today we are partnering with
No Longer Stocked
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[Related Guides to the Product](https://learn.adafruit.com/products/4949/guides)
### Microsoft Machine Learning Kit for Lobe with Raspberry Pi 4 4GB
[Microsoft Machine Learning Kit for Lobe with Raspberry Pi 4 4GB](https://www.adafruit.com/product/4963)
Machine learning is a transformative tool that’s redefining how we build software—but up until now, it was only accessible to a small group of experts. At Adafruit, we think machine learning should be accessible to everyone, that’s why today we are partnering with
No Longer Stocked
[Buy Now](https://www.adafruit.com/product/4963)
[Related Guides to the Product](https://learn.adafruit.com/products/4963/guides)
### Adafruit BrainCraft HAT - Machine Learning for Raspberry Pi 4
[Adafruit BrainCraft HAT - Machine Learning for Raspberry Pi 4](https://www.adafruit.com/product/4374)
The idea behind the BrainCraft HAT is that you’d be able to “craft brains” for Machine Learning on the EDGE, with Microcontrollers & Microcomputers. On ASK AN ENGINEER, our founder & engineer chatted with Pete Warden, the technical lead of the mobile,...
In Stock
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[Related Guides to the Product](https://learn.adafruit.com/products/4374/guides)
### Raspberry Pi 4 Model B - 4 GB RAM
[Raspberry Pi 4 Model B - 4 GB RAM](https://www.adafruit.com/product/4296)
The Raspberry Pi 4 Model B is the newest Raspberry Pi computer made, and the Pi Foundation knows you can always make a good thing _better_! And what could make the Pi 4 better than the 3? How about a _faster_ processor, USB 3.0 ports, and updated Gigabit Ethernet chip with...
In Stock
[Buy Now](https://www.adafruit.com/product/4296)
[Related Guides to the Product](https://learn.adafruit.com/products/4296/guides)
## Related Guides
- [Raspberry Pi Care and Troubleshooting](https://learn.adafruit.com/raspberry-pi-care-and-troubleshooting.md)
- [Adafruit BrainCraft HAT - Easy Machine Learning for Raspberry Pi](https://learn.adafruit.com/adafruit-braincraft-hat-easy-machine-learning-for-raspberry-pi.md)
- [diy lofi hip hop raspberry pi radio](https://learn.adafruit.com/lofi-hip-hop-raspberry-pi-radio-braincraft.md)
- [Raspberry Pi YouTube Boombox](https://learn.adafruit.com/youtube-radio.md)
- [Basic TensorFlow Object Recognition on any Computer or iOS device with Google Colab](https://learn.adafruit.com/basic-tensorflow-object-recognition-in-the-cloud-google-colab.md)
- [Machine Learning 101 with Lobe and BrainCraft](https://learn.adafruit.com/machine-learning-101-lobe-braincraft.md)
- [Using Google Assistant on the BrainCraft HAT or Voice Bonnet](https://learn.adafruit.com/using-google-assistant-on-the-braincraft-hat.md)
- [BrainCraft Camera Case](https://learn.adafruit.com/braincraft-camera-case.md)
- [Build an ML Package Detector with Lobe](https://learn.adafruit.com/build-an-ml-package-detector.md)
- [Raspberry Pi + Teachable Machine = Teachable Pi](https://learn.adafruit.com/teachable-machine-raspberry-pi-tensorflow-camera.md)
- [Running TensorFlow Lite Object Recognition on the Raspberry Pi 4 or Pi 5](https://learn.adafruit.com/running-tensorflow-lite-on-the-raspberry-pi-4.md)
- [Python Edge Speech Recognition with Voice2JSON](https://learn.adafruit.com/edge-speech-recognition-with-voice2json.md)
- [Adafruit INA219 Current Sensor Breakout](https://learn.adafruit.com/adafruit-ina219-current-sensor-breakout.md)
- [CircuitPython Libraries with the Binho Nova Multi-Protocol USB Host Adapter](https://learn.adafruit.com/circuitpython-with-binho-nova-multi-protocol-usb-host-adapter.md)
- [Adafruit 2.8" and 3.2" Color TFT Touchscreen Breakout v2](https://learn.adafruit.com/adafruit-2-8-and-3-2-color-tft-touchscreen-breakout-v2.md)
- [Working with I2C Devices](https://learn.adafruit.com/working-with-i2c-devices.md)