caoloss Goto Github PK

products-manager-methun

proi_proj1_zbiory

SETS OF THE POINTS IN A CARTESIAN LANDMARK - My very first project in C++ as part of the Object Programming Course at the 2nd semester of the Computer Science degree at Warsaw University of Technology

project-mimic

An Augmented Reality application which allows any Skype for Business user to control (during a video call) a customized "mimic'd" three dimensional and photo-realistic Avatar recorded and optimized using the Structure Sensor and Skanect/Blender Rendering Software. This application leverages several technologies including ['Janus webRTC Multi-Media Server", "Blender Rigging", "Real-Time Face Landmark Tracking (eventually will be full body skeleton), "Real-Time motion control", "Frame Interpolation"]. These technologies are combined and hosted on AWS using a proprietary MEAN (MongoDB, Express, Angular 6, and Node) Stack with User Access control and remote call Replay. Additionally, we are providing Remote Viewer Media Broadcast (RVMB), eg. other signed in users will have the optins to observethe 'active call' and enjoy the experience of eavesdropping on their friends. You must have express permission to copy, modify, distribute, or save this code to any machine.

projects-assignment

proxmox-plugin

pure-bash-bible

📖 A collection of pure bash alternatives to external processes.

px-dev

PX-Developer is scale-out storage for containers. Run Cassandra, Jenkins, or any application in Docker, with enterprise storage functionality on commodity servers

python-flask-restapi-app

python-flask-restapi-mithun

python-opencv-funny-face-filter-

Project uses face detection and landmarks detection technology to implement face filter using python programming language.

pythonprojrepo-vamsi

rabbitmq-cluster-setup-docker

rabbitmq-cluster-setup-docker-mithun

rchidana-hello_java

real-estate-price-prediction-paper

- An application that helps the user to get information on real estate property, with elegant accuracy and accurate output. It predicts the property prices via our datasets and prediction algorithmic. We are using datasets of the landmark was prediction going to process, this landmark can be updated as per as the area we want to predict, for prediction we are using linear regression algorithm, we are using Flask as our framework. We are getting precise results. we found, training data for maximum we were getting absolute results By using the technologies like python, we can predict working in this field we can train and get more amusing data, In real estate properties prices are impracticable as compare to other investments. We can say we can predict the property

repos4

repos5

ruby-app

rubyapp-mithun

sample-web-application

samplewebapp123

SampleWebApp123.war

script.py

scripting

scripts

seaborn-data

Data repository for seaborn examples

semoss_helm

serverless-azure-functionspy

serverless-cloudpy

serverless-examplespy

serverless-netlify-landing-pagepy