Douglas Duhaime duhaime

## seed data
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np

side = 85
n = side * side
np.random.seed(0)
xy = np.random.uniform(low=-1, high=+1, size=(n, 2))
xy = np.cumsum(xy, axis=0)
xy -= xy.min(axis=0)

## separate_points.py
def lat_lon_hex_mesh(bounds, d=3):
    """Creates a hexagonal lat/lon mesh within bounds that has a radial separation of d"""

    lone, lonw, lats, latn = bounds

    # heigt of equilatral triangle from radial distance sqrt(r^2 - (r/2)^2)
    h = np.sqrt(0.75) * d
    w = d / 2

    lat_vals = np.arange(lats, latn, h)

## index.js
const functions = require('firebase-functions');
const axios = require('axios');

exports.helloWorld = functions.https.onRequest((request, response) => {
  response.set('Access-Control-Allow-Origin', '*');
  response.set('Access-Control-Allow-Methods', 'GET, POST');
  const url = 'https://travel-birds-app.firebaseio.com/users/9b74fd7a-1a2b-11ea-9b18-f45c89b66fa9.json';
  return axios.get(url)
    .then(data => response.status(200).json({
      message: data.data,

## .gitignore
matches
ngrams
*.swp
*.pem
*.json

## encode.py
import numpy as np
from scipy.misc import imread
from skimage.transform import resize
import matplotlib.pyplot as plt
import json, glob

#%matplotlib inline

def path_to_string(path):
  '''Given a path to an image, return a string of that image as ascii'''

## index.html
<html>
  <head>
    <meta charset='UTF-8'>
    <title>PoseNet</title>
    <script src='https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.8.0/p5.min.js'></script>
    <script src='https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.8.0/addons/p5.dom.min.js'></script>
    <script src='https://unpkg.com/ml5@0.3.1/dist/ml5.min.js' type='text/javascript'></script>
  </head>

  <body>

## index.html
<!DOCTYPE html>
<html>
  <head>
    <meta charset='UTF-8'>
    <title>title</title>
  </head>
  <body></body>
  <script src='gunzip.min.js'></script>
  <script type='text/javascript'>

## vectorize_image.py
from keras.preprocessing.image import load_img, save_img, img_to_array, array_to_img
from keras.applications import Xception, VGG19, InceptionV3, imagenet_utils
import keras.backend as K
import numpy as np

model = Xception(weights='imagenet')

# VGG16, VGG19, and ResNet take 224×224 images; InceptionV3 and Xception take 299×299 inputs
img = load_img('l.jpg', target_size=(299,299))
arr = img_to_array(img)

## app.py
from flask import Flask, render_template
from smtp_client import send_email
from smtp_server import SMTPServer

app = Flask(__name__)

@app.route('/send_email')
def email():
  server = SMTPServer()
  server.start()

## OrbitControls.js
/**
 * @author qiao / https://github.com/qiao
 * @author mrdoob / http://mrdoob.com
 * @author alteredq / http://alteredqualia.com/
 * @author WestLangley / http://github.com/WestLangley
 */

THREE.OrbitControls = function ( object, domElement ) {

	this.object = object;