Deep Learning Simplified is an Open-source repository, containing beginner to advance level deep learning projects for the contributors, who are willing to start their journey in Deep Learning. Devfolio URL, https://devfolio.co/projects/deep-learning-simplified-f013
Deep Learning Simplified Repository (Proposing new issue)
:red_circle: Project Title : Football Analysis system
:red_circle: Aim : Buliding football analysis system using computer vision
:red_circle: Dataset : https://www.kaggle.com/competitions/dfl-bundesliga-data-shootout/data?select=clips
:red_circle: Approach : using YOlO to detect the players, referees and footballs ,l assign players to teams based on the colors of their t-shirts using Kmeans for pixel segmentation and clustering and use optical flow to measure camera movement between frames, enabling us to accurately measure a player's movemen
📍 Follow the Guidelines to Contribute in the Project :
You need to create a separate folder named as the Project Title.
Inside that folder, there will be four main components.
Images - To store the required images.
Dataset - To store the dataset or, information/source about the dataset.
Model - To store the machine learning model you've created using the dataset.
requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.
:red_circle::yellow_circle: Points to Note :
The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
"Issue Title" and "PR Title should be the same. Include issue number along with it.
Follow Contributing Guidelines & Code of Conduct before start Contributing.
:white_check_mark: To be Mentioned while taking the issue :
Deep Learning Simplified Repository (Proposing new issue)
:red_circle: Project Title : Football Analysis system :red_circle: Aim : Buliding football analysis system using computer vision :red_circle: Dataset : https://www.kaggle.com/competitions/dfl-bundesliga-data-shootout/data?select=clips :red_circle: Approach : using YOlO to detect the players, referees and footballs ,l assign players to teams based on the colors of their t-shirts using Kmeans for pixel segmentation and clustering and use optical flow to measure camera movement between frames, enabling us to accurately measure a player's movemen
📍 Follow the Guidelines to Contribute in the Project :
requirements.txt
- This file will contain the required packages/libraries to run the project in other machines.Model
folder, theREADME.md
file must be filled up properly, with proper visualizations and conclusions.:red_circle::yellow_circle: Points to Note :
:white_check_mark: To be Mentioned while taking the issue :
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎