- Bluenoise in the game INSIDE (dithering, raymarching, reflections)
- Dithering, Ray marching, shadows etc
- A Survery of Blue Noise and Its Applications
- Moments In Graphics (void-and-cluster)
- Bart Wronski Implementation of Solid Angle algorithm
// float->half variants. | |
// by Fabian "ryg" Giesen. | |
// | |
// I hereby place this code in the public domain, as per the terms of the | |
// CC0 license: | |
// | |
// https://creativecommons.org/publicdomain/zero/1.0/ | |
// | |
// float_to_half_full: This is basically the ISPC stdlib code, except | |
// I preserve the sign of NaNs (any good reason not to?) |
# "Colorizing B/W Movies with Neural Nets", | |
# Network/Code Created by Ryan Dahl, hacked by samim.io to work with movies | |
# BACKGROUND: http://tinyclouds.org/colorize/ | |
# DEMO: https://www.youtube.com/watch?v=_MJU8VK2PI4 | |
# USAGE: | |
# 1. Download TensorFlow model from: http://tinyclouds.org/colorize/ | |
# 2. Use FFMPEG or such to extract frames from video. | |
# 3. Make sure your images are 224x224 pixels dimension. You can use imagemagicks "mogrify", here some useful commands: | |
# mogrify -resize 224x224 *.jpg | |
# mogrify -gravity center -background black -extent 224x224 *.jpg |
// How to download telegram sticker images | |
/* | |
1. Go to Telegram Web; | |
2. Open console (F12); | |
3. Paste the code below in the console and press Enter; | |
4. Open your stickers menu and make sure you see the sticker pack you want to download (so Telegram will load it). | |
5. At the console paste and run "downloadStickers()" any time you want to download a pack. | |
6. [Convert .webm to another format](http://www.freewaregenius.com/convert-webp-image-format-jpg-png-format/); | |
7. Happy hacking. |
*update: TBC, but this new might affect how easy it is to use this technique past August 2024: Authy is shutting down its desktop app | The 2FA app Authy will only be available on Android and iOS starting in August
This gist, based in part on a gist by Brian Hartvigsen, allows you to export from Authy your TOTP tokens you have stored there.
Those can be "standard" 6-digits / 30 secs tokens, or Authy's own version, the 7-digits / 10 secs tokens.
import torch | |
import torch.nn as nn | |
import torch.nn.init as init | |
class MinibatchDiscrimination(nn.Module): | |
def __init__(self, in_features, out_features, kernel_dims, mean=False): | |
super().__init__() | |
self.in_features = in_features | |
self.out_features = out_features | |
self.kernel_dims = kernel_dims |
Yesterday I posted a problem to math stack exchange that bothered me for a while now, and right after I've had a few exchanges on Twitter, I got inspired to attempt a solution.
Here it goes. It's 100% untested but I'm fairly certain that it will work.
The problem is about a form of refining raytracing where we render a big list of convex 3D brushes (and I decided to start with Ellipsoids, since they're so useful) to the screen or a shadow map, without any prebuilt accelleration structure. How does it work? Well, if we had a way to figure out for a portion of the frustum whether it contained a brush, we could
My Dear Imgui render loop looks a bit unusual because I want to reduce calls to WebGL as much as possible, especially buffer update calls.
This means:
In shader programming, you often run into a problem where you want to iterate an array in memory over all pixels in a compute shader | |
group (tile). Tiled deferred lighting is the most common case. 8x8 tile loops over a light list culled for that tile. | |
Simplified HLSL code looks like this: | |
Buffer<float4> lightDatas; | |
Texture2D<uint2> lightStartCounts; | |
RWTexture2D<float4> output; | |
[numthreads(8, 8, 1)] |