The project's goal is to show a real world application of image segmentation using k means algorithm

Overview

k-means-real-time-segmentation

The project's goal is to show a real world application of image segmentation using k means algorithm.

image

image

features of the code:

  1. segmentation of an image (can use the webcam class or upload your own)
  2. define which clusters you would like to hide (in black color) --> easy way to reduce noise in an image and make easier detections

example of the results on my data: (different combinations of cluster coloring)

image

image

image

webcam class output: (yea thats me)

image

MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training

MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th

MosaicML 2.8k Jan 06, 2023
Data from "Datamodels: Predicting Predictions with Training Data"

Data from "Datamodels: Predicting Predictions with Training Data" Here we provid

Madry Lab 51 Dec 09, 2022
Apache (Py)Spark type annotations (stub files).

PySpark Stubs A collection of the Apache Spark stub files. These files were generated by stubgen and manually edited to include accurate type hints. T

Maciej 114 Nov 22, 2022
ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, MLOps and Data-Management

ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T

ClearML 4k Jan 09, 2023
A Lucid Framework for Transparent and Interpretable Machine Learning Models.

Currently a Beta-Version lucidmode is an open-source, low-code and lightweight Python framework for transparent and interpretable machine learning mod

lucidmode 15 Aug 12, 2022
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.

TensorFlowOnSpark TensorFlowOnSpark brings scalable deep learning to Apache Hadoop and Apache Spark clusters. By combining salient features from the T

Yahoo 3.8k Jan 04, 2023
Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and t

164 Jan 04, 2023
Quantum Machine Learning

The Machine Learning package simply contains sample datasets at present. It has some classification algorithms such as QSVM and VQC (Variational Quantum Classifier), where this data can be used for e

Qiskit 364 Jan 08, 2023
flexible time-series processing & feature extraction

A corona statistics and information telegram bot.

PreDiCT.IDLab 206 Dec 28, 2022
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.

Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in

Backprop 227 Dec 10, 2022
A Python toolbox to churn out organic alkalinity calculations with minimal brain engagement.

Organic Alkalinity Sausage Machine A Python toolbox to churn out organic alkalinity calculations with minimal brain engagement. Getting started To mak

Charles Turner 1 Feb 01, 2022
Python module for data science and machine learning users.

dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu

Emmanuel ASIFIWE 1 Nov 23, 2021
STUMPY is a powerful and scalable Python library for computing a Matrix Profile, which can be used for a variety of time series data mining tasks

STUMPY STUMPY is a powerful and scalable library that efficiently computes something called the matrix profile, which can be used for a variety of tim

TD Ameritrade 2.5k Jan 06, 2023
ETNA is an easy-to-use time series forecasting framework.

ETNA is an easy-to-use time series forecasting framework. It includes built in toolkits for time series preprocessing, feature generation, a variety of predictive models with unified interface - from

Tinkoff.AI 674 Jan 07, 2023
XManager: A framework for managing machine learning experiments 🧑‍🔬

XManager is a platform for packaging, running and keeping track of machine learning experiments. It currently enables one to launch experiments locally or on Google Cloud Platform (GCP). Interaction

DeepMind 620 Dec 27, 2022
ml4ir: Machine Learning for Information Retrieval

ml4ir: Machine Learning for Information Retrieval | changelog Quickstart → ml4ir Read the Docs | ml4ir pypi | python ReadMe ml4ir is an open source li

Salesforce 77 Jan 06, 2023
Bayesian Additive Regression Trees For Python

BartPy Introduction BartPy is a pure python implementation of the Bayesian additive regressions trees model of Chipman et al [1]. Reasons to use BART

187 Dec 16, 2022
LibTraffic is a unified, flexible and comprehensive traffic prediction library based on PyTorch

LibTraffic is a unified, flexible and comprehensive traffic prediction library, which provides researchers with a credibly experimental tool and a convenient development framework. Our library is imp

432 Jan 05, 2023
LightGBM + Optuna: no brainer

AutoLGBM LightGBM + Optuna: no brainer auto train lightgbm directly from CSV files auto tune lightgbm using optuna auto serve best lightgbm model usin

Rishiraj Acharya 22 Dec 15, 2022