Realistic lighting in ursina!

Last update: Jul 07, 2022

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Overview

Ursina Lighting

Realistic lighting in ursina!

If you want to have realistic lighting in ursina, import the UrsinaLighting.py in your project and use the LitObject class instead of the Enity class. If you need help, ask me (https://discord.gg/JpBPbcKJ) or look in UrsinaLighting.py where you can find the source code and an example.

You can use my code in your projects and make private changes to it, but you are not allowed without permission to re-distribute my code to the internet and taking credit for it.

Owner

GitHub Repository

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1k Jan 07, 2023

Realistic lighting in ursina!

Related tags

Overview

Ursina Lighting

Owner

DilatedNet in Keras for image segmentation

Official pytorch implement for “Transformer-Based Source-Free Domain Adaptation”

Cross-Document Coreference Resolution

Tackling Obstacle Tower Challenge using PPO & A2C combined with ICM.

Code for "My(o) Armband Leaks Passwords: An EMG and IMU Based Keylogging Side-Channel Attack" paper

code and models for "Laplacian Pyramid Reconstruction and Refinement for Semantic Segmentation"

Semi-supervised Video Deraining with Dynamical Rain Generator (CVPR, 2021, Pytorch)

ColossalAI-Benchmark - Performance benchmarking with ColossalAI

Answer a series of contextually-dependent questions like they may occur in natural human-to-human conversations.

DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks

Face and Body Tracking for VRM 3D models on the web.

A PyTorch Image-Classification With AlexNet And ResNet50.

ML From Scratch

Code, final versions, and information on the Sparkfun Graphical Datasheets

An implementation of the WHATWG URL Standard in JavaScript

Code from the paper "High-Performance Brain-to-Text Communication via Handwriting"

Prml - Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

Some useful blender add-ons for SMPL skeleton's poses and global translation.

Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR

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