Bot developed in Python that automates races in pegaxy.

Overview

Logo

español | português

About it:

This is a fork from pega-racing-bot. This bot, developed in Python, is to automate races in pegaxy. The game developers do not allow the use of bots. It was developed for study purposes only, not responsible for any penalties that may be incurred for using it. Use it at your own risk.

The software is free and open source and should not be used for commercial purposes. Pull requests are welcome.

How to install it:

1 - Download Python from official website here.

2 - Install Python on your OS. (Remeber to add PYTHON to path)

3 - Open your terminal (Command prompt).

4 - Go to bot folder using following command:

cd c:/pegaxy-runner-bot

Here i recommend you installing virtualenv as a good practice, so you don't fill your computer with packages that you won't use later, or cause bug with other python applications. The processes below are not required. Remember if you do that will always have to activate it before using the bot.

To install virtualenv use pip:

pip install virtualenv

To create a new virtualenv named venv:

pip install virtualenv

To activate virtualenv:

.\venv\Scripts\activate

You can see now a (venv) that is the name of virtualenv you created.

5 - Install all requeriments using following command:

pip install -r requirements.txt

or you can install it manually using following commands:

pip install pillow
pip install opencv-python
pip install pyautogui
pip install mss
pip install colorama

6 - Recommend you take all screenshots from folder screenshots using LightShot

7 - Run bot using following command:

Remember that you must be on the pegaxy's website with your metamask connected.

python main.py

8 - Use CTRL + C to STOP script.

To do 🎯 :

- Organize code.
- Solve start buttom bug.
- Solve expected bug if user has less than three horses (IndexError).
- Make code smarter, work only if energy != 0/0.
- Take horses name.
- Save race data by horse.

Found a bug or questions?

Feel free to open an issue.

Do you like it ? Buy me a coffee or a horse! Wallet (Polygon / BSC):

0xEEf8F8023C3d24276Bd807705C213d6994c064b6
Train Yolov4 using NBX-Jobs

yolov4-trainer-nbox Train Yolov4 using NBX-Jobs. Use the powerfull functionality available in nbox-SDK repo to train a tiny-Yolo v4 model on Pascal VO

Yash Bonde 1 Jan 12, 2022
This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transformers.

TransMix: Attend to Mix for Vision Transformers This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transf

Jie-Neng Chen 130 Jan 01, 2023
Code base for the paper "Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation"

This repository contains code for the paper Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiati

8 Aug 28, 2022
A list of Machine Learning Art Colabs

ML Visual Art Colabs A list of cool Colabs on Machine Learning Imagemaking or other artistic purposes 3D Ken Burns Effect Ken Burns Effect by Manuel R

Derrick Schultz (he/him) 789 Dec 12, 2022
Scaling and Benchmarking Self-Supervised Visual Representation Learning

FAIR Self-Supervision Benchmark is deprecated. Please see VISSL, a ground-up rewrite of benchmark in PyTorch. FAIR Self-Supervision Benchmark This cod

Meta Research 584 Dec 31, 2022
Deep learning for Engineers - Physics Informed Deep Learning

SciANN: Neural Networks for Scientific Computations SciANN is a Keras wrapper for scientific computations and physics-informed deep learning. New to S

SciANN 195 Jan 03, 2023
Official PyTorch Implementation of Embedding Transfer with Label Relaxation for Improved Metric Learning, CVPR 2021

Embedding Transfer with Label Relaxation for Improved Metric Learning Official PyTorch implementation of CVPR 2021 paper Embedding Transfer with Label

Sungyeon Kim 37 Dec 06, 2022
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

Yixuan Su 79 Nov 04, 2022
FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset (CVPR2022)

FaceVerse FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset Lizhen Wang, Zhiyuan Chen, Tao Yu, Chenguang

Lizhen Wang 219 Dec 28, 2022
JittorVis - Visual understanding of deep learning models

JittorVis: Visual understanding of deep learning model JittorVis is an open-source library for understanding the inner workings of Jittor models by vi

thu-vis 182 Jan 06, 2023
Code for the paper "Graph Attention Tracking". (CVPR2021)

SiamGAT 1. Environment setup This code has been tested on Ubuntu 16.04, Python 3.5, Pytorch 1.2.0, CUDA 9.0. Please install related libraries before r

122 Dec 24, 2022
Official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer"

[AAAI2022] UCTransNet This repo is the official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspectiv

Haonan Wang 199 Jan 03, 2023
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks

Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi

Giacomo Arcieri 1 Mar 21, 2022
Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming

Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming. Outperforming `GPT-3` on SuperGLUE Few-Shot text classification.

YerevaNN 75 Nov 06, 2022
Scripts and outputs related to the paper Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings.

Knowledge Graph Embeddings and Chemical Effect Prediction, 2020. Scripts and outputs related to the paper Prediction of Adverse Biological Effects of

Knowledge Graphs at the Norwegian Institute for Water Research 1 Nov 01, 2021
Metrics to evaluate quality and efficacy of synthetic datasets.

An Open Source Project from the Data to AI Lab, at MIT Metrics for Synthetic Data Generation Projects Website: https://sdv.dev Documentation: https://

The Synthetic Data Vault Project 129 Jan 03, 2023
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

BasicVSR BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond Ported from https://github.com/xinntao/BasicSR Dependencie

Holy Wu 8 Jun 07, 2022
Automated Evidence Collection for Fake News Detection

Automated Evidence Collection for Fake News Detection This is the code repo for the Automated Evidence Collection for Fake News Detection paper accept

Mrinal Rawat 2 Apr 12, 2022
Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

Varun Nair 37 Dec 30, 2022
Repository sharing code and the model for the paper "Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes"

Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes Setup virtualenv -p python3 venv source venv/bin/activate pip instal

Planet AI GmbH 9 May 20, 2022