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Download Youtube Live streamed video from the start or selected time
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right-click on the playing video, select Copy link
find Wistia video ID in the copied link e.g. wvideo=tra6gsm6rl
alternative: look for e.g. hashedId=tra6gsm6rl in the page source
load http://fast.wistia.net/embed/iframe/ + video ID in your browser
look for "type":"original" in the page source and
copy the URL from the next line
e.g. "url":"http://embed.wistia.com/deliveries/129720d1762175bcd8e06dcab926ec76ad38ff00.bin"
If you are like me you find yourself cloning a repo, making some proposed changes and then deciding to later contributing back using the GitHub Flow convention. Below is a set of instructions I've developed for myself on how to deal with this scenario and an explanation of why it matters based on jagregory's gist.
To follow GitHub flow you should really have created a fork initially as a public representation of the forked repository and the clone that instead. My understanding is that the typical setup would have your local repository pointing to your fork as origin and the original forked repository as upstream so that you can use these keywords in other git commands.
Clone some repo (you've probably already done this step).
Emoji-list with emojis, names, shortcodes, unicode and html entities [massive list]
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[Train Conductor World][tcw] is mobile game (for [iOS][ios] and [Android][and]) by [The Voxel Agents][tva].
The game has several cities on a world map (currently, only European cities).
This project (i.e. this GitHub Gist) is an effort to replicate the game world map outside the game.
For that, I've used [Tiled Map Editor][tiled] to rebuild the map, and [Gimp][gimp] to create the graphics.
This map can be used in the future to help planning in-game routes.
The graphics are based on [in-game screenshots][ss].
As of January 2018, Raspbian does not yet include the latest Python release, Python 3.6. This means we will have to build
it ourselves, and here is how to do it. There is also an ansible role attached that automates it all for you.
Install the required build-tools (some might already be installed on your system).
Takes a screenshot of a selected area, saves to file *and* copies to clipboard.
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The following recipes are sampled from a trained neural net.
You can find the repo to train your own neural net here: https://github.com/karpathy/char-rnn
Thanks to Andrej Karpathy for the great code! It's really easy to setup.
The recipes I used for training the char-rnn are from a recipe collection called ffts.com
And here is the actual zipped data (uncompressed ~35 MB) I used for training.
The ZIP is also archived @ archive.org in case the original links becomes invalid in the future.