Giter Site home page Giter Site logo

guibrandt / osulearn Goto Github PK

View Code? Open in Web Editor NEW
60.0 3.0 6.0 33.76 MB

An attempt at using machine learning to create a neural network that learns how to play osu! like a human from replay data

License: MIT License

Jupyter Notebook 98.55% Python 1.45%
machine-learning neural-network osugame keras jupyter-notebook

osulearn's Introduction

OsuLearn

An attempt at creating a Neural Network that learns how to play osu!std like a human from replays

(Plz don't judge me too much I'm new to machine learning and i can't english)

Introduction

osu! is a free and open-source rhythm game developed and published by Australian-based company PPY Developments PTY, created by Dean Herbert (also known as peppy). Originally released for Microsoft Windows on September 16, 2007, the game has also been ported to macOS (this version might be unstable), and Windows Phone. Its gameplay is based on titles including Osu! Tatakae! Ouendan, Elite Beat Agents, Taiko no Tatsujin, Beatmania IIDX, O2Jam, and DJMax.

-- Wikipedia

The goal here is to model and train a Neural Network to generate replays for any osu beatmap it is given based on a dataset of recorded human replays (.osr files) and their respective beatmap (.osu) file.

To accomplish that, I've trained a Recurrent Neural Network with my replays and beatmaps.

Results

This is a preview for a replay generated for a map the AI had never seen before:

IA Generated Replay

Pretty good, actually!

It has figured out how to aim without looking like a robot and can even hit some jumps. Of course it is not perfect, but neither is the data set it has been trained on, so I am considering this a success.

Future

The next step is to transform this into a GAN, so it can generate multiple different replays for a given map, mimicking a human play style.

This might take some time though, so that's it for now x).

osulearn's People

Contributors

guibrandt avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar  avatar

osulearn's Issues

.osr support?

Hello, I got this to work all nicely and was wondering if you would make it able to generate .osr files to watch the replay ingame

please explain if it's not difficult

I'm just getting started in this area myself, and your code is amazing to learn from. If you still go to GitHub and look at the questions, then it would be very interesting for me to know what exactly needs to be entered in replays = glob(os.path.join(".generated", "* () [[][]]. npy") instead of generated and * () [[][]].npy
I would be VERY grateful if you could answer

i keep geting the same error

im new to machine learning and i was trying to run the program but when i try to run it i get this error:

ModuleNotFoundError Traceback (most recent call last)
Cell In[15], line 13
10 import pandas as pd
11 import matplotlib.pyplot as plt
---> 13 import osu.rulesets.beatmap
14 import osu.rulesets.replay
15 import osu.rulesets.hitobjects as hitobjects

ModuleNotFoundError: No module named 'osu'

any ideas how to fix this ? or im doing something wrong ?

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.