| #!/bin/sh | |
| # see https://codeberg.org/whitequark/nixos-bite | |
| curl https://codeberg.org/whitequark/nixos-bite/raw/branch/main/nixos-bite.sh | bash -s "$@" |
| // 3D Dom viewer, copy-paste this into your console to visualise the DOM as a stack of solid blocks. | |
| // You can also minify and save it as a bookmarklet (https://www.freecodecamp.org/news/what-are-bookmarklets/) | |
| (() => { | |
| const SHOW_SIDES = false; // color sides of DOM nodes? | |
| const COLOR_SURFACE = true; // color tops of DOM nodes? | |
| const COLOR_RANDOM = false; // randomise color? | |
| const COLOR_HUE = 190; // hue in HSL (https://hslpicker.com) | |
| const MAX_ROTATION = 180; // set to 360 to rotate all the way round | |
| const THICKNESS = 20; // thickness of layers | |
| const DISTANCE = 10000; // ¯\\_(ツ)_/¯ |
| """ | |
| Built on top of this gist by @karpathy: | |
| https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355 | |
| stable diffusion dreaming over text prompts | |
| creates hypnotic moving videos by smoothly walking randomly through the sample space | |
| example way to run this script: | |
| $ python stable_diffusion_walk.py --prompts "['blueberry spaghetti', 'strawberry spaghetti']" --seeds 243,523 --name berry_good_spaghetti |
| """ | |
| stable diffusion dreaming | |
| creates hypnotic moving videos by smoothly walking randomly through the sample space | |
| example way to run this script: | |
| $ python stablediffusionwalk.py --prompt "blueberry spaghetti" --name blueberry | |
| to stitch together the images, e.g.: | |
| $ ffmpeg -r 10 -f image2 -s 512x512 -i blueberry/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p blueberry.mp4 |
| #!/usr/bin/python3 | |
| # Solution to the challenge at https://gist.github.com/ehmo/7f515ac6461c1c4d3e5a74f12e6eb5ea | |
| # Sample solution: https://twitter.com/marcan42/status/1428933147660492800 | |
| # | |
| # Given an input base image, computes two derivative images that have different | |
| # perceptual hashes, yet differ by only one pixel. | |
| # | |
| # Usage: hash_bisector.py <input.png> <output_a.png> <output_b.png> | |
| # | |
| # Licensed under the terms of the STRONGEST PUBLIC LICENSE, Draft 1: |
This list contains repositories of libraries and approaches for knowledge graph embeddings, which are vector representations of entities and relations in a multi-relational directed labelled graph. Licensed under CC0.
| #!/bin/bash | |
| # Stolen from http://answers.microsoft.com/en-us/mac/forum/macoffice2011-macoutlook/office-for-mac-mavericks-high-performance-gpu/e1a6aff0-e36e-40ae-ab62-aa7e3e0c6b10 | |
| # Enable for Lync | |
| AppName="/Applications/Microsoft Lync.app" | |
| defaults write "$AppName/Contents/Info.plist" "NSSupportsAutomaticGraphicsSwitching" -bool true | |
| if [ $? -eq 0 ]; then | |
| chmod 664 "$AppName/Contents/Info.plist" | |
| # Code sign Lync again |
| (ns react-cljs.core | |
| (:require React)) | |
| (declare render) | |
| (defn handle-change [e] | |
| (render {:text (.. e -target -value)})) | |
| (defn render [{:keys [text]}] | |
| (React/renderComponent |
| ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | |
| ;; SMOOTHING | |
| ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; | |
| (defn exponential-smooth | |
| " | |
| Smooths a sequence with an exponentially decreasing weight. | |
| Arguments: | |
| x -- a sequence of numbers |
