HuggingFace Page for model download: https://huggingface.co/hakurei/waifu-diffusion-v1-3
NetHole
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| Shader "Toon/Lit Swaying" { | |
| Properties { | |
| _Color ("Main Color", Color) = (0.5,0.5,0.5,1) | |
| _MainTex ("Base (RGB)", 2D) = "white" {} | |
| _Ramp ("Toon Ramp (RGB)", 2D) = "gray" {} | |
| _Speed ("MoveSpeed", Range(20,50)) = 25 // speed of the swaying | |
| _Rigidness("Rigidness", Range(1,50)) = 25 // lower makes it look more "liquid" higher makes it look rigid | |
| _SwayMax("Sway Max", Range(0, 0.1)) = .005 // how far the swaying goes | |
| _YOffset("Y offset", float) = 0.5// y offset, below this is no animation | |
NetHole
/ Outline.shader
Created
July 24, 2024 06:04
— forked from ScottJDaley/Outline.shader
Wide Outlines Renderer Feature for URP and ECS/DOTS/Hybrid Renderer
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| // Original shader by @bgolus, modified slightly by @alexanderameye for URP, modified slightly more | |
| // by @gravitonpunch for ECS/DOTS/HybridRenderer. | |
| // https://twitter.com/bgolus | |
| // https://medium.com/@bgolus/the-quest-for-very-wide-outlines-ba82ed442cd9 | |
| // https://alexanderameye.github.io/ | |
| // https://twitter.com/alexanderameye/status/1332286868222775298 | |
| Shader "Hidden/Outline" | |
| { | |
| Properties |
NetHole
/ wd1-3-release.md
Created
March 13, 2023 06:44
— forked from harubaru/wd1-3-release.md
Official Release Notes for Waifu Diffusion 1.3
NetHole
/ InputModeDetector.cpp
Created
February 22, 2023 06:53
— forked from sinbad/InputModeDetector.cpp
UE4 detecting which input method was last used by each player
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| #include "InputModeDetector.h" | |
| #include "Input/Events.h" | |
| FInputModeDetector::FInputModeDetector() | |
| { | |
| // 4 local players should be plenty usually (will expand if necessary) | |
| LastInputModeByPlayer.Init(EInputMode::Mouse, 4); | |
| } | |
| bool FInputModeDetector::HandleKeyDownEvent(FSlateApplication& SlateApp, const FKeyEvent& InKeyEvent) |
NetHole
/ pg-pong.py
Created
May 7, 2020 08:24
— forked from karpathy/pg-pong.py
Training a Neural Network ATARI Pong agent with Policy Gradients from raw pixels
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| """ Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """ | |
| import numpy as np | |
| import cPickle as pickle | |
| import gym | |
| # hyperparameters | |
| H = 200 # number of hidden layer neurons | |
| batch_size = 10 # every how many episodes to do a param update? | |
| learning_rate = 1e-4 | |
| gamma = 0.99 # discount factor for reward |