uncrazy

Dmitriy Popkov's starred repositories

This repository contains a comprehensive computer vision/machine learning football project that uses YOLO for object detection, Kmeans for pixel segmentation, optical flow for motion tracking, and perspective transformation to analyze player movements in football videos

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datalens

A modern, scalable analytics system

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python-pyodata

Enterprise-ready Python OData client

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1c_odata_python

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radar

🎯 A simple Python package for creating radar charts.

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Soccermatics

A template for creating a course with readthedocs.

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AppFlowy

Bring projects, wikis, and teams together with AI. AppFlowy is an AI collaborative workspace where you achieve more without losing control of your data. The best open source alternative to Notion.

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GlickoSoccer

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ml-course

Open Machine Learning course

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pycaret

An open-source, low-code machine learning library in Python

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pl-fantasy-bot-public

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streamlit-on-Hover-tabs

Custom tabs for on hover streamlit navigation bar created by custom css

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quantifying_soccer_players_decision_making

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FootballPassPrediction

Football/Soccer Pass Receiver Prediction using Object Detection/Graph Neural Networks (GNNs)

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soccer_player_tracking

An implementation to track Soccer players on any random video. The model also detects background such as crowd and hoardings.

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Soccer-Analyses

The code here is pretty much everything I use to create my datasets (from FBRef) or visuals. Most my scatter plots are made in Tableau, though, using the dataset created from the FBRef dataset download

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