kettanaito

Chromium on Vercel (serverless)

This is an up-to-date guide on running Chromium in Vercel serverless functions in 2022. What you will read below is the result of two days of research, debugging, 100+ failed deployments, and a little bit of stress.

Getting started

Step 1: Install dependencies

Use chrome-aws-lambda that comes with Chromium pre-configured to run in serverless, and puppeteer-core due to the smaller size of Chromium distributive.

ryleu

This guide is completely irrelevant! You no longer need to follow anything here—doing so may actually harm performance rather than helping it. Please tell whoever linked you here that they need to maintain their own guide, if they want to help people set up newer versions of DXVK / etc.

quietsy

Moved to https://virtualize.link/secure/

Webreaper

# Docker compose to set up containers for all services you need:
# VPN
#   Sonarr, Radarr, Lidarr, Qbittorrent
# Non-VPN
#   Plex, get_iplayer
# Before running docker-compose, you should pre-create all of the following folders.
# Folders for Docker State:
#  /volume1/dockerdata.             - root where this docker-compose.yml should live
#  /volume1/dockerdata/plex         - Plex config and DB
#  /volume1/dockerdata/sonarr       - Sonarr config and DB

ryardley

# https://plantuml.com/text-encoding
# https://github.com/dougn/python-plantuml/blob/master/plantuml.py#L64

import zlib
import base64

maketrans = bytes.maketrans

plantuml_alphabet = string.digits + string.ascii_uppercase + string.ascii_lowercase + '-_'
base64_alphabet   = string.ascii_uppercase + string.ascii_lowercase + string.digits + '+/'

aondio

Here's a step by step guide to convert a Virtualbox .ova to a Vagrant box.

1. List your VMs to find the VM id you want to convert:

$ VBoxManage list vms
"testing" {a3f59eed-b9c5-4a5f-9977-187f8eb8c4d4}

2. You can now package the .ova VM as Vagrant box:

swipswaps

Building Tensorflow from source on Ubuntu 16.04LTS for maximum performance:

TensorFlow is now distributed under an Apache v2 open source license on GitHub.

On Ubuntu 16.04LTS+:

Step 1. Install NVIDIA CUDA:

To use TensorFlow with NVIDIA GPUs, the first step is to install the CUDA Toolkit as shown:

KrustyHack

Cloud-Init Support

Cloud-Init is the defacto multi-distribution package that handles early initialization of a virtual machine instance. Using Cloud-Init, one can configure network

drscotthawley

#! /usr/bin/env python
'''
greenscreen.py:  Greenscreen effect without a physical green screen
This performs background subtraction, and sets the background to "green" for use with "key frame" video editing software
Author: Scott Hawley, https://github.com/drscotthawley


Requirements:
Python, NumPy and OpenCV
I got these via Macports, but Homebrew, etc. work.  

PurpleBooth

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites