ryanholbrook

import numpy as np

import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers

import matplotlib.pyplot as plt
from matplotlib import animation, rc
rc('animation', html='html5')
plt.style.use('seaborn-whitegrid')

seanjtaylor

seanjtaylor

smeschke

import cv2, numpy as np, os

#parameters
working_dir = '/home/stephen/Desktop/keras_demo/'
cap = cv2.VideoCapture(0)

org, font, scale, color, thickness, linetype = (50,50), cv2.FONT_HERSHEY_SIMPLEX, 1.2, (234,12,123), 2, cv2.LINE_AA
#chromakey values
h,s,v,h1,s1,v1 = 16,0,64,123,111,187 #green
h,s,v,h1,s1,v1 = 0,74,53,68,181,157 #skin tone

gka

#!/bin/bash
cd $( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )

blue=$(tput setaf 4)
green=$(tput setaf 2)
normal=$(tput sgr0)

while ./update.sh
do
	printf "\n${blue}>>> sleeping a little bit before running again... ${normal}\n"

emanuelfeld

#!/bin/bash

# set max file size to include (in MB)
max_size_mb=100

max_size_b="$(($max_size_mb * 1000000))c"
git_dir="$(git rev-parse --show-toplevel)"
git_exclude=$git_dir/.git/info/exclude

files="$(find $git_dir -path $git_dir/.git -prune -o -type f -size +$max_size_b -print  | sed "s%$git_dir/%%g" | sed "s/\ /\\\ /g")"

Rich-Harris

Stuff I wish I'd known sooner about service workers

I recently had several days of extremely frustrating experiences with service workers. Here are a few things I've since learned which would have made my life much easier but which isn't particularly obvious from most of the blog posts and videos I've seen.

I'll add to this list over time – suggested additions welcome in the comments or via twitter.com/rich_harris.

Use Canary for development instead of Chrome stable

Chrome 51 has some pretty wild behaviour related to console.log in service workers. Canary doesn't, and it has a load of really good service worker related stuff in devtools.

veltman

// Pipe to ffmpeg with something like:
// node draw.js | ffmpeg -y -c:v png -f image2pipe -r 20 -i - -an -c:v libx264 -pix_fmt yuv420p -movflags +faststart myvideo.mp4

var Canvas = require("canvas"),
    d3 = require("d3"),
    topojson = require("topojson"),
    rw = require("rw"),
    world = require("./world-110m.json");

var width = 1280,

alykat

/*
 * Wrap a block of text to a given width
 * via http://bl.ocks.org/mbostock/7555321
 */
var wrapText = function(texts, width, lineHeight) {
    texts.each(function() {
        var text = d3.select(this);
        var words = text.text().split(/\s+/).reverse();

        var word = null;

kingjr

# Author: Jean-Remi King <jeanremi.king@gmail.com>
"""
    Illustrate how a hinge loss and a log loss functions 
    typically used in SVM and Logistic Regression 
    respectively focus on a variable number of samples.
    For simplification purposes, we won't consider the
    regularization or penalty (C) factors.
"""
import numpy as np
import matplotlib.animation as animation