Turning images into '9-pan' palettes using KMeans clustering from sklearn.

Overview

img2palette

Turning images into '9-pan' palettes using KMeans clustering from sklearn.

Requirements

We require:

  • Pillow, for opening and processing images
  • Scikit Learn, for clustering

We use numpy. Since it's a dependency of scikit-learn, we're not specifying it; we're going to use the version that comes with our pinned sklearn version.

On Raspberry Pi, we ran into the error

Original error was: libf77blas.so.3: cannot open shared object file: No such file or directory

So we did the following:

sudo apt-get install libatlas-base-dev

The numpy developer documentation recommended either doing that or installing the version of numpy packaged for raspbian. Since we want to use the version of numpy included with sklearn for the least number of dependency headaches, we install libatlas instead.

If you run into additional issues running the script, please add an Issue with your problem or solution to this repository. If you don't have a solution, I'll do my best to come up with one.

Running

We recommend a virtual environment.

~$ python3 -m venv venv
~$ source venv/bin/activate
~$ python3 -m pip install -r requirements.txt

Once that process is complete, run the program:

python3 img2palette.py -i 
   

   

Samples

The output is OK. We should tweak the options in the future.

For this image by Marco Ferrarin:

A Beautiful Mosque.

We receive this palette:

An OK Palette representing the mosque.

Perhaps the clustering could be adjusted for different / better results? But, for a first attempt, I'm pretty happy.

Owner
Samuel Vidovich
Me like program. Me like write code. Me write code all days.
Samuel Vidovich
Machine Learning Model to predict the payment date of an invoice when it gets created in the system.

Payment-Date-Prediction Machine Learning Model to predict the payment date of an invoice when it gets created in the system.

15 Sep 09, 2022
This is the material used in my free Persian course: Machine Learning with Python

This is the material used in my free Persian course: Machine Learning with Python

Yara Mohamadi 4 Aug 07, 2022
LinearRegression2 Tvads and CarSales

LinearRegression2_Tvads_and_CarSales This project infers the insight that how the TV ads for cars and car Sales are being linked with each other. It i

Ashish Kumar Yadav 1 Dec 29, 2021
Pytools is an open source library containing general machine learning and visualisation utilities for reuse

pytools is an open source library containing general machine learning and visualisation utilities for reuse, including: Basic tools for API developmen

BCG Gamma 26 Nov 06, 2022
Distributed Evolutionary Algorithms in Python

DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru

Distributed Evolutionary Algorithms in Python 4.9k Jan 05, 2023
Price forecasting of SGB and IRFC Bonds and comparing there returns

Project_Bonds Project Title : Price forecasting of SGB and IRFC Bonds and comparing there returns. Introduction of the Project The 2008-09 global fina

Tishya S 1 Oct 28, 2021
Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows.

Auto_TS: Auto_TimeSeries Automatically build multiple Time Series models using a Single Line of Code. Now updated with Dask. Auto_timeseries is a comp

AutoViz and Auto_ViML 519 Jan 03, 2023
Deep Survival Machines - Fully Parametric Survival Regression

Package: dsm Python package dsm provides an API to train the Deep Survival Machines and associated models for problems in survival analysis. The under

Carnegie Mellon University Auton Lab 10 Dec 30, 2022
Built on python (Mathematical straight fit line coordinates error predictor machine learning foundational model)

Sum-Square_Error-Business-Analytical-Tool- Built on python (Mathematical straight fit line coordinates error predictor machine learning foundational m

om Podey 1 Dec 03, 2021
Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )

implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map,

Mohamadreza Rezaei 1 Jan 19, 2022
Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations.

BO-GP Bayesian optimization based on Gaussian processes (BO-GP) for CFD simulations. The BO-GP codes are developed using GPy and GPyOpt. The optimizer

KTH Mechanics 8 Mar 31, 2022
Random Forest Classification for Neural Subtypes

Random Forest classifier for neural subtypes extracted from extracellular recordings from human brain organoids.

Michael Zabolocki 1 Jan 31, 2022
Simple, fast, and parallelized symbolic regression in Python/Julia via regularized evolution and simulated annealing

Parallelized symbolic regression built on Julia, and interfaced by Python. Uses regularized evolution, simulated annealing, and gradient-free optimization.

Miles Cranmer 924 Jan 03, 2023
50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster

[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm

Daniel Han-Chen 1.4k Jan 01, 2023
🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code

Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co

Hugging Face 2.5k Jan 07, 2023
A linear regression model for house price prediction

Linear_Regression_Model A linear regression model for house price prediction. This code is using these packages, so please make sure your have install

ShawnWang 1 Nov 29, 2021
QML: A Python Toolkit for Quantum Machine Learning

QML is a Python2/3-compatible toolkit for representation learning of properties of molecules and solids.

176 Dec 09, 2022
A game theoretic approach to explain the output of any machine learning model.

SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo

Scott Lundberg 18.2k Jan 02, 2023
A visual dataflow programming language for sklearn

Persimmon What is it? Persimmon is a visual dataflow language for creating sklearn pipelines. It represents functions as blocks, inputs and outputs ar

Álvaro Bermejo 194 Jan 04, 2023
Penguins species predictor app is used to classify penguins species created using python's scikit-learn, fastapi, numpy and joblib packages.

Penguins Classification App Penguins species predictor app is used to classify penguins species using their island, sex, bill length (mm), bill depth

Siva Prakash 3 Apr 05, 2022