Mufaddal Kapasi's Projects
Cut and paste your surroundings using AR
Block Matching algorithm to identify moviment in sequence images
A library of clear-sky irradiance models
Cloud Detection using Mask RCNN on satellite images (INSAT 3D) on infrared and visible channels provided by ISRO. Project for SIH 2020. Problem statement by ISRO
Python 3 package for Fully Convolutional Network development, specifically for cloud masking
Ultimate Solidity, Blockchain, and Smart Contract - Beginner to Expert Full Course | Python Edition
GenX: a configurable power system capacity expansion model for studying low-carbon energy futures. More details at : https://genx.mit.edu
Config files for my GitHub profile.
This repository contains code for cloud detection and motion prediction algorithms developed during SIH 2020.
Project developed under Problem Statement NM373, for MHRD and the Indian Space Research Organization (ISRO), at the Smart India Hackathon 2020
Mycroft Core, the Mycroft Artificial Intelligence platform.
Python Scripts to forecast solar radiation through Scikit-Learn, Keras and Arch.
Implement Lucas-Kanade optical flow estimation, and test it for the two-frame data sets provided in Python from scratch
a set of functions to compute solar irradiance under clear sky conditions
The plugin uses the phase correlation method to compute cloud motion vectors from the Waggle sky camera images.
The Prognostic Algorithm Package is a python framework for model-based prognostics (computation of remaining useful life) of engineering systems, and provides a set of algorithms for state estimation and prediction, including uncertainty propagation. The algorithms take as inputs prognostic models (from NASA's Prognostics Model Package), and perform estimation and prediction functions. The library allows the rapid development of prognostics solutions for given models of components and systems. Different algorithms can be easily swapped to do comparative studies and evaluations of different algorithms to select the best for the application at hand.
The NASA Prognostic Model Package is a Python framework focused on defining and building models for prognostics (computation of remaining useful life) of engineering systems, and provides a set of prognostics models for select components developed within this framework, suitable for use in prognostics applications for these components.
The NASA Prognostics As-A-Service (PaaS) Sandbox is a simplified implementation of a Software Oriented Architecture (SOA) for performing prognostics (estimation of time until events and future system states) of engineering systems. The PaaS Sandbox is a wrapper around the Prognostics Algorithms Package and Prognostics Models Package, allowing one or more users to access the features of these packages through a REST API. The package is intended to be used as a research tool to prototype and benchmark Prognostics As-A-Service (PaaS) architectures and work on the challenges facing such architectures, including Generality, Communication, Security, Environmental Complexity, Utility, and Trust.
Python version of the FMask Landsat Cloud Masking code
PyMPDATA usage examples reproducing results from literature and depicting how to use PyMPDATA in Python from Jupyter notebooks
An application that displays a map and graphs showing solar irradiance forecasts in solar farms in Georgia using data from the National Solar Radiation Database.
Software Record SWR-18-36 "A Physics-based Smart Persistent Model for Intra-hour Solar Forecasting"
Solar irradiance forecasting using INSAT-3D satellite images.
A supplementary module to tobac containing functions for the detection, segmentation and tracking of clouds using optical flow techniques
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent