Smart Irrigation custom component for Home Assistant
Rain Rendering for Evaluating and Improving Robustness to Bad Weather (Tremblay et al., 2020) (S. S. Halder et al., 2019)
[ECCV2024] "Raindrop Clarity: A Dual-Focused Dataset for Day and Night Raindrop Removal", https://arxiv.org/abs/2407.16957
Matrix rain effect using python 3 and curses
[TPAMI 2023] Code for inference of our TPAMI and ECCV papers on model-guided disentanglement for GANs.
Library for rain estimation and detection built with PyTorch. This library provides an implementation of algorithms for extracting rain-rate using data from commercial microwave links (CMLs). Addinaly this project provide an example dataset with data from two CMLs and implementation of performance and robustness metrics
Examples of surface precipitation phase discrimination using open data meteorological observations.
submit urls.txt to web.archive.org using GitHub Actions workflow
Creating a simulation of cloud growth and formation using Pygame
Tools for generating a rainrate composite using Helsinki metropolitean area weather radars.
Access open data gribs at any requested time stamp by efficiently parsing and utilizing optical flow methods to advect relevant parameters via a FastAPI interface.
Determine where water will flow to based on height GIS data
raddo helps you find, download, sort and preprocess RADOLAN weather radar precipitation data for further usage.
RainGAN, a generative model that enables a generation of a realistic, complex rain field that is conditioned on user parameters such as max peak, number of peaks, etc.
Think about your doorbell, it rings when a button is pressed, signifying a person wants to see you. Those times when it is in use, it’s invaluable. Now imagine the person at your door is actually a visiting rain cloud, who has the courtesy to warn you that rain is on the way.
Simulate rain with random lightning strikes and thunder on Philips Hue lamps and Sonos speakers.
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