First set up a project directory to hold your work:
cd ~/projects
mkdir mapnik-ios-test
cd mapnik-ios-test
#!/usr/bin/env bash | |
rm -rf "${HOME}/Library/Caches/CocoaPods" | |
rm -rf "`pwd`/Pods/" | |
pod update |
#!/usr/bin/env bash | |
# Reset routing table on OSX | |
# display current routing table | |
echo "********** BEFORE ****************************************" | |
netstat -r | |
echo "**********************************************************" | |
for i in {0..4}; do | |
sudo route -n flush # several times |
if __name__ == "__main__": | |
reactor_args = {} | |
def run_twisted_wsgi(): | |
from twisted.internet import reactor | |
from twisted.web.server import Site | |
from twisted.web.wsgi import WSGIResource | |
resource = WSGIResource(reactor, reactor.getThreadPool(), app) | |
site = Site(resource) |
var AWS = require('aws-sdk'); | |
exports.handler = function(event, context) { | |
var cloudsearchdomain = new AWS.CloudSearchDomain({endpoint: 'doc-dev-cinch-accounts-ltmqj5gt5mjb5hg5eyqaf2v5hu.us-east-1.cloudsearch.amazonaws.com'}); | |
var documents = event.Records.map(function(record) { | |
var data = {id : record.dynamodb.Keys.id.S}; | |
if (record.eventName === 'REMOVE') { | |
data.type = 'delete' |
Convolutional neural networks for emotion classification from facial images as described in the following work:
Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, Nov. 2015
Project page: http://www.openu.ac.il/home/hassner/projects/cnn_emotions/
If you find our models useful, please add suitable reference to our paper in your work.
// Create an `Observable` of Optional<Int> | |
let values: Observable<Int?> = [1, 2, .None, 3, .None, 4, 5].toObservable() | |
// Method 1: using a free function | |
// Requires passing the function to `flatMap` | |
func ignoreNil<A>(x: A?) -> Observable<A> { | |
return x.map { Observable.just($0) } ?? Observable.empty() | |
} |