Features Libraries

16 Components & Libraries

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Features Libraries

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Install CatBoost by following the guide for the Next you may want to investigate: If you cannot open documentation in your browser try adding yastatic.net and yastat.net to the list of allowed domain…

Feature Store for Machine Learning

Feast allows ML platform teams to: The list below contains the functionality that contributors are planning to develop for Feast. We welcome contribution to all items in the roadmap! Feast is a commu…

Anaconda turns your Sublime Text 3 in a full featured Python development IDE including autocompletion, code linting, IDE features, autopep8 formating, McCabe complexity checker Vagrant and Docker support for Sublime Text 3 using Jedi, PyFlakes, pep8, MyPy, PyLint, pep257 and McCabe that will never freeze your Sublime Text 3

The plugins ecosystem in Sublime Text have improved by a lot in the past few years, there are many alternatives to anaconda that might work better for you Anaconda works out of the box but there are …

A library for audio and music analysis, feature extraction.

You can use multiple dimensional feature combinations, select different deep learning networks training, study various tasks in the audio field such as Classification, Separation, MIR etc. In the tim…

Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support: https://discourse.slicer.org/c/community/radiomics

This is an open-source python package for the extraction of Radiomics features from medical imaging. With this package we aim to establish a reference standard for Radiomic Analysis, and provide a te…

Deep facial expressions recognition using Opencv and Tensorflow. Recognizing facial expressions from images or camera stream

Using a Convolutional Neural Network (CNN) to recognize facial expressions from images or video/camera stream. The goal is to get a quick baseline to compare if the CNN architecture performs better w…

:sound: spafe: Simplified Python Audio Features Extraction

Simplified Python Audio Features Extraction spafe requires: if you want to use the visualization module/ functions of spafe, you will need to install: Once you have the Dependencies installed, use on…

Command line C++ and Python VSTi Host library with MFCC, FFT, RMS and audio extraction and .wav writing.

Here are some quick gifs demonstrating a miniscule amount of the availble features, go towards the bottom of the README to see the full API: Next, get the boost headers. Now just open the Xcode proje…

Python library for management for geospatial data in GeoServer.

Geoserver-rest is the open source library written in python and contributors are needed to keep this library moving forward. Any kind of contributions are welcome. Here are the basic rule for the new…

Python scripts accompanying the book "An Introduction to Audio Content Analysis" (www.AudioContentAnalysis.org)

All implementations are also available in: The top-level functions are (alphabetical): The names of the additional functions follow the following conventions: Consistent variable naming and formattin…

Interactive code for image similarity using SIFT algorithm

This repo provides a working interactive code to use SIFT algorithm for image similarity. I have also presented some of the results. Check them out and let me know if you need something more. Anyone …

Extract minutiae features from fingerprint images

The important fingerprint minutiae features are the ridge endpoints (a.k.a. Terminations) and Ridge Bifurcations. The feature set for the image consists of the location of Terminations and Bifurcatio…

Package for automatic beat-mixing of music files in Python 🐻🎚

Mix two WAV files - Tested on Python 3.6 or later

This repository contains works on a computer vision software pipeline built on top of Python to identify Lanes and vehicles in a video. This project is not part of Udacity SDCND but is based on other free courses and challanges provided by Udacity. It uses Computer vision and Deep Learrning Techniques. Few pipelines have been tried on SeDriCa, IIT Bombay.

To run the lane detection script for any video files, update the last few lines of 'lanedetect.py'. The final calibration matrices are saved in the pickle file 'calibrate_camera.p' The following desc…

Computer Vision Essentials in Python Programming Language :tada:

Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks t…