Christiana Olusegun's repositories

fm4a

Repository for the AI Foundation Models for the Atmosphere workshop

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Springer_Reviewer_Certificates

Springer Nature Reviewer Certificates

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geeagri

Python tools for agricultural analysis powered by Google Earth Engine.

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flood-insurance-maps

Exploring FEMA's National Flood Insurance Program (NFIP) Data

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stationbench

Benchmarking of weather forecasts based on station observations

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real_time_weather_data

Orchestration of streamlit application with airflow

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pytoon

PyToon is a Python based animation library for automatically animating a cartoon character's mouth movements and bodily expressions to sync with an audio recording of someone talking. PyToon uses machine learning based audio analysis techniques to automatically generate lip-synced character animations (see "Example Output Video" in README).

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Wav2Lip

This repository contains the codes of "A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild", published at ACM Multimedia 2020. For HD commercial model, please try out Sync Labs

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world-geojson

GeoJson for all the countries, areas (regions) and some states.

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pyClim-SDM

Statistical Downscaling for Climate Change Projections with a Graphical User Interface

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FLOODPY

Flood Python Toolbox

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daily_BCSD

Code used for daily Bias Correction/Spatial Disaggregation (BCSD) method

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py-dreambooth

Easily create your own AI avatar images!

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basd

Bias adjustment and statistical downscaling capabilities

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lafferty-sriver_2023_npjCliAtm

Repository for 2023 paper in npj Climate & Atmospheric Science

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Bias-correction_and_CMIP_downscaling

Code used in Potter et al., 2022 to bias-correct the WRF code, and statistically downscale CMIP models

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eCLM

Fork of Community Land Model v5.0

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python_class

This repository contains all the scripts used for the python class for JRFs at IITM

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DeepDownscaling

Deep learning approaches for statistical downscaling in climate

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ATLAS

Datasets, code and virtual workspace for the Climate Change ATLAS

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ML-Notebooks

:fire: A series of code examples for all sorts of machine learning tasks and applications.

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