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do androids dream of cooking?

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.

It seems to be in a format intended to be read by a program called Meal-Master, therefore you will see those lines repeated all over:

/*
* OGL_OCV_common.cpp
* Common interop between OpenCV and OpenGL
*
* Created by Roy Shilkrot on 2/16/2015
* Copyright 2015 Roy Shilkrot. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Test that I passed on codility.com for TopTal company
#
# Task #1
def binary_gap(N):
import cv2
import numpy as np
class BagOfFeatures:
"""This is a class of Bag-of-Features by K-means for OpenCV"""
codebookSize=0
classifier=None
def __init__(self, codebookSize):
self.codebookSize=codebookSize
self.classifier=cv2.KNearest()
/* Getopt for GNU.
NOTE: getopt is now part of the C library, so if you don't know what
"Keep this file name-space clean" means, talk to [email protected]
before changing it!
Copyright (C) 1987,88,89,90,91,92,93,94,95,96,98,99,2000,2001
Free Software Foundation, Inc.
This file is part of the GNU C Library.
The GNU C Library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
#include "cv.h"
#include "cvaux.h"
#include "highgui.h"
// for filelisting
#include <stdio.h>
#include <io.h>
// for fileoutput
#include <string>
#include <fstream>
import cv2
import numpy as np
class BagOfFeatures:
"""This is a class of Bag-of-Features by K-means for OpenCV"""
codebookSize=0
classifier=None
def __init__(self, codebookSize):
self.codebookSize=codebookSize
self.classifier=cv2.KNearest()
'''
This is how to track a white ball example using SimpleCV
The parameters may need to be adjusted to match the RGB color
of your object.
The demo video can be found at:
http://www.youtube.com/watch?v=jihxqg3kr-g
'''
print __doc__
<!DOCTYPE html>
<html>
<head>
<script type="text/javascript" src="http://mbostock.github.com/d3/d3.js"></script>
<script type="text/javascript" src="http://mbostock.github.com/d3/d3.layout.js"></script>
<script type="text/javascript" src="http://mbostock.github.com/d3/d3.geom.js"></script>
<style type="text/css">
.link { stroke: #ccc; }
.nodetext { pointer-events: none; font: 10px sans-serif; }
</style>