Easily pull telemetry data and create beautiful visualizations for analysis.

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. 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

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

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

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

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

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,

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

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

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
🔅 Shapash makes Machine Learning models transparent and understandable by everyone

🎉 What's new ? Version New Feature Description Tutorial 1.6.x Explainability Quality Metrics To help increase confidence in explainability methods, y

MAIF 2.1k Dec 27, 2022
PyTorch code for DriveGAN: Towards a Controllable High-Quality Neural Simulation

PyTorch code for DriveGAN: Towards a Controllable High-Quality Neural Simulation

76 Dec 24, 2022
[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.

[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.

BCMI 49 Jul 27, 2022
Data and Code for ACL 2021 Paper "Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning"

Introduction Code and data for ACL 2021 Paper "Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning". We cons

Pan Lu 81 Dec 27, 2022
The Face Mask recognition system uses AI technology to detect the person with or without a mask.

Face Mask Detection Face Mask Detection system built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect

Rohan Kasabe 4 Apr 05, 2022
Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle

TF Watcher TF Watcher is a simple to use Python package and web app which allows you to monitor 👀 your Machine Learning training or testing process o

Rishit Dagli 54 Nov 01, 2022
Chinese clinical named entity recognition using pre-trained BERT model

Chinese clinical named entity recognition (CNER) using pre-trained BERT model Introduction Code for paper Chinese clinical named entity recognition wi

Xiangyang Li 109 Dec 14, 2022
Code repo for "RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network" (Machine Learning and the Physical Sciences workshop in NeurIPS 2021).

RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc

Rao Muhammad Umer 6 Nov 14, 2022
Image-Adaptive YOLO for Object Detection in Adverse Weather Conditions

Image-Adaptive YOLO for Object Detection in Adverse Weather Conditions Accepted by AAAI 2022 [arxiv] Wenyu Liu, Gaofeng Ren, Runsheng Yu, Shi Guo, Jia

liuwenyu 245 Dec 16, 2022
Official PyTorch implementation of StyleGAN3

Modified StyleGAN3 Repo Changes Made tied to python 3.7 syntax .jpgs instead of .pngs for training sample seeds to recreate the 1024 training grid wit

Derrick Schultz (he/him) 83 Dec 15, 2022
Simple, efficient and flexible vision toolbox for mxnet framework.

MXbox: Simple, efficient and flexible vision toolbox for mxnet framework. MXbox is a toolbox aiming to provide a general and simple interface for visi

Ligeng Zhu 31 Oct 19, 2019
Tello Drone Trajectory Tracking

With this library you can track the trajectory of your tello drone or swarm of drones in real time.

Kamran Asgarov 2 Oct 12, 2022
Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption

SG-GAN TensorFlow implementation of SG-GAN. Prerequisites TensorFlow (implemented in v1.3) numpy scipy pillow Getting Started Train Prepare dataset. W

lplcor 61 Jun 07, 2022
CondenseNet: Light weighted CNN for mobile devices

CondenseNets This repository contains the code (in PyTorch) for "CondenseNet: An Efficient DenseNet using Learned Group Convolutions" paper by Gao Hua

Shichen Liu 690 Nov 30, 2022
Implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification

CrossViT : Cross-Attention Multi-Scale Vision Transformer for Image Classification This is an unofficial PyTorch implementation of CrossViT: Cross-Att

Rishikesh (ऋषिकेश) 103 Nov 25, 2022
Implementations of LSTM: A Search Space Odyssey variants and their training results on the PTB dataset.

An LSTM Odyssey Code for training variants of "LSTM: A Search Space Odyssey" on Fomoro. Check out the blog post. Training Install TensorFlow. Clone th

Fomoro AI 95 Apr 13, 2022
SNIPS: Solving Noisy Inverse Problems Stochastically

SNIPS: Solving Noisy Inverse Problems Stochastically This repo contains the official implementation for the paper SNIPS: Solving Noisy Inverse Problem

Bahjat Kawar 35 Nov 09, 2022
Java and SHACL code commented in the paper "Towards compliance checking in reified I/O logic via SHACL" submitted to ICAIL 2021

shRIOL The subfolder shRIOL contains Java files to execute the SHACL files on the OWL ontology. To compile the Java files: "javac -cp ./src/;./lib/* -

1 Dec 06, 2022
Few-shot NLP benchmark for unified, rigorous eval

FLEX FLEX is a benchmark and framework for unified, rigorous few-shot NLP evaluation. FLEX enables: First-class NLP support Support for meta-training

AI2 85 Dec 03, 2022
[ACL-IJCNLP 2021] Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning

CLNER The code is for our ACL-IJCNLP 2021 paper: Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning CLNER is a

71 Dec 08, 2022