Easily pull telemetry data and create beautiful visualizations for analysis.

Related tags

Deep Learningformula1data-analysismotorsport
Overview

  This repository is a work in progress. Anything and everything is subject to change.

Porpo

Table of Contents

General Information

Porpo is a python application that utilizes the FastF1 package to easily pull specific data and generate visualizations for analysis.

Note: Python3 (v.3.8 or greater) is required.

Getting Started

Currently, there is not a simple way to run the program. However, getting it up and running is very easy, regardless of platform.

Install Dependencies:

pip3 install fastf1
pip3 install PySimpleGUI

There are 2 methods of execution:

/scripts/gui.py to begin using the application with a GUI. (Recommended)

/scripts/main.py to begin using the application in CLI.

Usage

Porpo allows you to individually set all the variables for evaluation.

You start by selecting the year the Grand Prix took place.

Then select the Grand Prix you want.

Then select the session from the Grand Prix.

Note: No GP has all sessions.

Next, select the driver you'd like to evaluate.

Now decide if you're going to evaluate the full session, or a specific lap, or easily select the fastest lap set by your chosen driver.

Check the FastF1 documentation to see everything that is available for each option.

The last step is to select which variables you want displayed on the axes (X and Y).

Be aware that although you can select any available data as either variable, some combinations may not perform as expected - or at all.

The plot will show up in a new window, and automatically save to your export directory when the graph is closed.

If you're unsure where your export directory is, the default is:

~/Documents/F1 Data Analysis/Export/

 

To change this directory, edit the save_path variable in scripts/gui.py

  save_path = '~/Documents/F1 Data Analysis/Export/'

Specific Lap

You can easily pull and visualize data for a single lap of a session.

VER_SpeedL_Bah

Max Verstappen speed on Lap 54 of the 2022 Bahrain GP. We can see he was losing power throughout the lap, up until the moment he completely lost power, and went into the pitlane.

Fastest Lap

By default, you can quickly do analysis of the fastest lap set by the selected driver during a session.

VER_SpeedF_Bah

Max Verstappen speed on the fastest lap he set in 2022 Bahrain GP. We can the difference between this lap and lap 54, when he retired.

Session

You can also quickly do an analysis of a driver's performance through an entire session.

VER_SpeedF_Bah

Max Verstappen laptime over the course of the Imola GP. We can see as the track began to dry, laptimes began to fall very quickly.
You might also like...
A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.
A Sklearn-like Framework for Hyperparameter Tuning and AutoML in Deep Learning projects. Finally have the right abstractions and design patterns to properly do AutoML. Let your pipeline steps have hyperparameter spaces. Enable checkpoints to cut duplicate calculations. Go from research to production environment easily.

Neuraxle Pipelines Code Machine Learning Pipelines - The Right Way. Neuraxle is a Machine Learning (ML) library for building machine learning pipeline

Neuraxio 555 Dec 24, 2022
sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code
sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code

sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ

Jonathan Shobrook 305 Dec 21, 2022
A project which aims to protect your privacy using inexpensive hardware and easily modifiable software
A project which aims to protect your privacy using inexpensive hardware and easily modifiable software

Protecting your privacy using an ESP32, an IR sensor and a python script This project, which I personally call the "never-gonna-catch-me-in-the-act-ev

null 8 Oct 10, 2022
Easily benchmark PyTorch model FLOPs, latency, throughput, max allocated memory and energy consumption

⏱ pytorch-benchmark Easily benchmark model inference FLOPs, latency, throughput, max allocated memory and energy consumption Install pip install pytor

Lukas Hedegaard 21 Dec 22, 2022
Create Data & AI apps in 20 lines of code with Shimoku

Install with: pip install shimoku-api-python Start with: from os import getenv import shimoku_api_python.client as Shimoku

Shimoku 5 Nov 7, 2022
IPATool-py: download ipa easily

IPATool-py Python version of IPATool! Installation pip3 install -r requirements.txt Usage Quickstart: download app with specific bundleId into DIR: p

null 159 Dec 30, 2022
Tracking Pipeline helps you to solve the tracking problem more easily
Tracking Pipeline helps you to solve the tracking problem more easily

Tracking_Pipeline Tracking_Pipeline helps you to solve the tracking problem more easily I integrate detection algorithms like: Yolov5, Yolov4, YoloX,

VNOpenAI 32 Dec 21, 2022
This application explain how we can easily integrate Deepface framework with Python Django application

deepface_suite This application explain how we can easily integrate Deepface framework with Python Django application install redis cache install requ

Mohamed Naji Aboo 3 Apr 18, 2022
A Python script that creates subtitles of a given length from text paragraphs that can be easily imported into any Video Editing software such as FinalCut Pro for further adjustments.
A Python script that creates subtitles of a given length from text paragraphs that can be easily imported into any Video Editing software such as FinalCut Pro for further adjustments.

Text to Subtitles - Python This python file creates subtitles of a given length from text paragraphs that can be easily imported into any Video Editin

Dmytro North 9 Dec 24, 2022
Comments
  • UnboundLocalError: local variable 'self' referenced before assignment

    UnboundLocalError: local variable 'self' referenced before assignment

    Gets a error code. How can i look at the exported data? Only thing i find under the exported track is filenames that ends with .ff1pkl Example: cardata.ff1pkl, driverinfo.ff1pkl And the error code is: UnboundLocalError: local variable 'self' referenced before assignment

    opened by jeveli 12
  • Cache directory does not exist

    Cache directory does not exist

    This is what I'm getting.

    C:\Users\james\Desktop\GitHub\porpo\scripts>python gui.py Traceback (most recent call last): File "C:\Users\james\Desktop\GitHub\porpo\scripts\gui.py", line 9, in class Dirs(): File "C:\Users\james\Desktop\GitHub\porpo\scripts\gui.py", line 28, in Dirs fastf1.Cache.enable_cache(cache_path) File "C:\Users\james\AppData\Local\Programs\Python\Python310\lib\site-packages\fastf1\api.py", line 133, in enable_cache raise NotADirectoryError("Cache directory does not exist! Please check for typos or create it first.") NotADirectoryError: Cache directory does not exist! Please check for typos or create it first.

    C:\Users\james\Desktop\GitHub\porpo\scripts>python main.py Traceback (most recent call last): File "C:\Users\james\Desktop\GitHub\porpo\scripts\main.py", line 8, in fastf1.Cache.enable_cache('venv/F1/Cache/') File "C:\Users\james\AppData\Local\Programs\Python\Python310\lib\site-packages\fastf1\api.py", line 133, in enable_cache raise NotADirectoryError("Cache directory does not exist! Please check for typos or create it first.") NotADirectoryError: Cache directory does not exist! Please check for typos or create it first.

    opened by DrMurgz 1
Releases(v1.4.2-beta.stable)

  • v1.4.2-beta.stable(Jul 28, 2022)

  • v1.4.1-beta.stable(Jul 27, 2022)

  • v1.4.0-beta.stable(Jul 27, 2022)

    What's Changed

    • fixed cache error by @dawesry in https://github.com/dawesry/porpo/pull/26
    • fixed driver spec lap error by @dawesry in https://github.com/dawesry/porpo/pull/27
    • fixed export error by @dawesry in #29

    Full Changelog: https://github.com/dawesry/porpo/compare/v1.3.0-beta.stable...v1.4.0-beta.stable

    Source code(tar.gz)
    Source code(zip)

  • v2.3.0-alpha.nightly(May 24, 2022)

    What's Changed

    • Nightly by @dtech-auto in https://github.com/dtech-auto/porpo/pull/23
    • fixed single driver full session error by @dtech-auto in https://github.com/dtech-auto/porpo/pull/24
    • stability update by @dtech-auto in https://github.com/dtech-auto/porpo/pull/25

    Full Changelog: https://github.com/dtech-auto/porpo/compare/v1.2.2-beta.stable...v2.3.0-alpha.nightly

    Source code(tar.gz)
    Source code(zip)

  • v1.3.0-beta.stable(May 24, 2022)

    What's Changed

    • Nightly by @dtech-auto in https://github.com/dtech-auto/porpo/pull/23
    • fixed single driver full session error by @dtech-auto in https://github.com/dtech-auto/porpo/pull/24
    • stability update by @dtech-auto in https://github.com/dtech-auto/porpo/pull/25

    Full Changelog: https://github.com/dtech-auto/porpo/compare/v1.2.2-beta.stable...v1.3.0-beta.stable

    Source code(tar.gz)
    Source code(zip)

  • v2.2.1-alpha.nightly(May 23, 2022)

    What's Changed

    • Fixed single driver plot error by @dtech-auto

    Full Changelog: https://github.com/dtech-auto/porpo/compare/v2.2.0-alpha.nightly...v2.2.1-alpha.nightly

    Source code(tar.gz)
    Source code(zip)

  • v2.2.0-alpha.nightly(May 23, 2022)

    What's Changed

    • drivercomp working - fastest only by @dtech-auto in https://github.com/dtech-auto/porpo/pull/19

    Full Changelog: https://github.com/dtech-auto/porpo/compare/v2.1.2-alpha.nightly...v2.2.0-alpha.nightly

    Source code(tar.gz)
    Source code(zip)

  • v2.1.2-alpha.nightly(May 23, 2022)

    Added compare - non functioning

    What's Changed

    • update README.md by @dtech-auto in https://github.com/dtech-auto/porpo/pull/15
    • Update gui.py by @dtech-auto in https://github.com/dtech-auto/porpo/pull/18

    Full Changelog: https://github.com/dtech-auto/porpo/compare/v1.0.2-beta.stable...v2.1.2-alpha.nightly

    Source code(tar.gz)
    Source code(zip)

  • v1.2.2-beta.stable(May 23, 2022)

    What's Changed

    GUI Updates

    • GUI Stability Updates by @dtech-auto in https://github.com/dtech-auto/porpo/pull/16

    New Features

    • NEW! Compare every driver, or a custom few, using the new Driver Compare feature! by @dtech-auto in https://github.com/dtech-auto/porpo/pull/21

    Bug Fixes

    • General bug fixes by @dtech-auto in https://github.com/dtech-auto/porpo/pull/22

    Full Changelog: https://github.com/dtech-auto/porpo/compare/v2.2.1-alpha.nightly...v1.2.2-beta.stable

    Source code(tar.gz)
    Source code(zip)

  • v1.1.0-beta.stable(May 21, 2022)

    What's Changed

    • update README.md by @dtech-auto in https://github.com/dtech-auto/porpo/pull/15
    • update gui --STABLE by @dtech-auto in https://github.com/dtech-auto/porpo/pull/16

    Full Changelog: https://github.com/dtech-auto/porpo/compare/v1.1.2-alpha.stable...v1.1.0-beta.stable

    Source code(tar.gz)
    Source code(zip)

  • v1.0.2-beta.stable(May 21, 2022)

    What's Changed

    • Nightly by @dtech-auto in https://github.com/dtech-auto/porpo/pull/10
    • Nightly by @dtech-auto in https://github.com/dtech-auto/porpo/pull/13
    • fixed issue #11 by @dtech-auto in https://github.com/dtech-auto/porpo/pull/14

    Full Changelog: https://github.com/dtech-auto/porpo/compare/v2.1.1-alpha.nightly...v1.1.2-alpha.stable

    Source code(tar.gz)
    Source code(zip)

  • v2.1.1-alpha.nightly(May 20, 2022)

    What's Changed

    • updated directory by @dtech-auto in https://github.com/dtech-auto/porpo/pull/6

    Full Changelog: https://github.com/dtech-auto/porpo/compare/v2.1.0-alpha.nightly...v2.1.1-alpha.nightly

    Source code(tar.gz)
    Source code(zip)

  • v2.1.0-alpha.nightly(May 20, 2022)

  • v2.0.0-alpha.nightly(May 20, 2022)

  • v1.0.1-beta.stable(May 20, 2022)

  • v1.0.0-beta.stable(May 20, 2022)

  • v1.1.0-alpha.stable(May 19, 2022)

  • v1.1.0-alpha.nightly(May 19, 2022)

  • v1.0.0-alpha.nightly(May 18, 2022)

    What's Changed

    • Nightly by @dtech-auto in https://github.com/dtech-auto/porpo/pull/5

    Full Changelog: https://github.com/dtech-auto/porpo/compare/v1.0.0-alpha...v1.0.0-alpha.nightly

    Source code(tar.gz)
    Source code(zip)

  • v1.0.0-alpha(May 17, 2022)

    What's Changed

    • Directory cleaning by @dtech-auto in https://github.com/dtech-auto/F1DataAnalysis/pull/3
    • Nightly by @dtech-auto in https://github.com/dtech-auto/F1DataAnalysis/pull/4

    New Contributors

    • @dtech-auto made their first contribution in https://github.com/dtech-auto/F1DataAnalysis/pull/3

    Full Changelog: https://github.com/dtech-auto/F1DataAnalysis/commits/v1.0.0-alpha

    Source code(tar.gz)
    Source code(zip)
Owner
Ryan Dawes
Ryan Dawes
GitHub Repository
Car Price Predictor App used to predict the price of the car based on certain input parameters created using python's scikit-learn, fastapi, numpy and joblib packages.

Pricefy Car Price Predictor App used to predict the price of the car based on certain input parameters created using python's scikit-learn, fastapi, n

Siva Prakash 1 May 10, 2022
Refactoring dalle-pytorch and taming-transformers for TPU VM

Text-to-Image Translation (DALL-E) for TPU in Pytorch Refactoring Taming Transformers and DALLE-pytorch for TPU VM with Pytorch Lightning Requirements

Kim, Taehoon 61 Nov 07, 2022
Efficient Multi Collection Style Transfer Using GAN

Proposed a new model that can make style transfer from single style image, and allow to transfer into multiple different styles in a single model.

Zhaozheng Shen 2 Jan 15, 2022
The Power of Scale for Parameter-Efficient Prompt Tuning

The Power of Scale for Parameter-Efficient Prompt Tuning Implementation of soft embeddings from https://arxiv.org/abs/2104.08691v1 using Pytorch and H

Kip Parker 208 Dec 30, 2022
A different spin on dataclasses.

dataklasses Dataklasses is a library that allows you to quickly define data classes using Python type hints. Here's an example of how you use it: from

David Beazley 752 Nov 18, 2022
Exploring Visual Engagement Signals for Representation Learning

Exploring Visual Engagement Signals for Representation Learning Menglin Jia, Zuxuan Wu, Austin Reiter, Claire Cardie, Serge Belongie and Ser-Nam Lim C

Menglin Jia 9 Jul 23, 2022
Deep deconfounded recommender (Deep-Deconf) for paper "Deep causal reasoning for recommendations"

Deep Causal Reasoning for Recommender Systems The codes are associated with the following paper: Deep Causal Reasoning for Recommendations, Yaochen Zh

Yaochen Zhu 22 Oct 15, 2022
Breast-Cancer-Prediction

Breast-Cancer-Prediction Trying to predict whether the cancer is benign or malignant using REGRESSION MODELS in Python. Team Members NAME ROLL-NUMBER

Shyamdev Krishnan J 3 Feb 18, 2022
In this project we predict the forest cover type using the cartographic variables in the training/test datasets.

Kaggle Competition: Forest Cover Type Prediction In this project we predict the forest cover type (the predominant kind of tree cover) using the carto

Marianne Joy Leano 1 Mar 15, 2022
An Straight Dilated Network with Wavelet for image Deblurring

SDWNet: A Straight Dilated Network with Wavelet Transformation for Image Deblurring(offical) 1. Introduction This repo is not only used for our paper(

FlyEgle 41 Jan 04, 2023
Platform-agnostic AI Framework 🔥

🇬🇧 TensorLayerX is a multi-backend AI framework, which can run on almost all operation systems and AI hardwares, and support hybrid-framework progra

TensorLayer Community 171 Jan 06, 2023
DA2Lite is an automated model compression toolkit for PyTorch.

DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. ⭐ Star us on GitHub — it helps!! Frameworks & Librari

Sinhan Kang 7 Mar 22, 2022
Kaggle-titanic - A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstrates basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.

Kaggle-titanic This is a tutorial in an IPython Notebook for the Kaggle competition, Titanic Machine Learning From Disaster. The goal of this reposito

Andrew Conti 800 Dec 15, 2022
The official code of Anisotropic Stroke Control for Multiple Artists Style Transfer

ASMA-GAN Anisotropic Stroke Control for Multiple Artists Style Transfer Proceedings of the 28th ACM International Conference on Multimedia The officia

Six_God 146 Nov 21, 2022
Robust Instance Segmentation through Reasoning about Multi-Object Occlusion [CVPR 2021]

Robust Instance Segmentation through Reasoning about Multi-Object Occlusion [CVPR 2021] Abstract Analyzing complex scenes with DNN is a challenging ta

Irene Yuan 24 Jun 27, 2022
3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans.

3DMV 3DMV jointly combines RGB color and geometric information to perform 3D semantic segmentation of RGB-D scans. This work is based on our ECCV'18 p

Владислав Молодцов 0 Feb 06, 2022
Pyramid addon for OpenAPI3 validation of requests and responses.

Validate Pyramid views against an OpenAPI 3.0 document Peace of Mind The reason this package exists is to give you peace of mind when providing a REST

Pylons Project 79 Dec 30, 2022
Source code for our paper "Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash"

Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash Abstract: Apple recently revealed its deep perceptual hashing system NeuralHash to

<a href=[email protected]"> 11 Dec 03, 2022
Unofficial TensorFlow implementation of the Keyword Spotting Transformer model

Keyword Spotting Transformer This is the unofficial TensorFlow implementation of the Keyword Spotting Transformer model. This model is used to train o

Intelligent Machines Limited 8 May 11, 2022
Reverse engineer your pytorch vision models, in style

🔍 Rover Reverse engineer your CNNs, in style Rover will help you break down your CNN and visualize the features from within the model. No need to wri

Mayukh Deb 32 Sep 24, 2022