Install tensorflow with virtualenv
$ virtualenv --system-site-packages -p python3 .
$ pip install tensorflowPlace next alias to ~/.profile
alias rstudio='open -a Rstudio'| @keyframes :local(fadeIn) { | |
| 0% { | |
| background-color: rgba(0, 0, 0, 0); | |
| } | |
| 100% { | |
| background-color: rgba(0, 0, 0, 0.3); | |
| } | |
| } |
| typedef void (*callback_helper_cb)(void* self, v8::Isolate* isolate, const v8::Persistent<v8::Function>& callback); | |
| struct callback_helper_data { | |
| v8::Persistent<v8::Function> callback; | |
| void* self; | |
| callback_helper_cb cb; | |
| }; | |
| #define CALLBACK_HELPER_CALL(A, B) v8::Local<v8::Function>::New(isolate, callback)->Call(isolate->GetCurrentContext()->Global(), A, B) |
Install tensorflow with virtualenv
$ virtualenv --system-site-packages -p python3 .
$ pip install tensorflowPlace next alias to ~/.profile
alias rstudio='open -a Rstudio'| #!/bin/bash | |
| # http://jimhoskins.com/2013/07/27/remove-untagged-docker-images.html | |
| docker rmi $(docker images | grep "^<none>" | awk "{print $3}") |
| // http://stackoverflow.com/questions/7616461/generate-a-hash-from-string-in-javascript-jquery | |
| export function hashCode(str) { | |
| let hash = 0, i, chr; | |
| if (str.length === 0) return hash; | |
| for (i = 0; i < str.length; i++) { | |
| chr = str.charCodeAt(i); | |
| hash = ((hash << 5) - hash) + chr; | |
| hash |= 0; // Convert to 32bit integer | |
| } | |
| return (hash + 2147483647) + 1; |
| declare var wcs_add; | |
| declare var wcs_do; | |
| export function setup() { | |
| const naverAnalyticsJsUrl = 'https://wcs.naver.net/wcslog.js'; | |
| $.getScript(naverAnalyticsJsUrl, function() { | |
| wcs_add = wcs_add || {}; | |
| wcs_add['wa'] = '395c28a8f51174'; | |
| wcs_do(); |
| ReactDOM.render(( | |
| <Provider store={store}> | |
| <IntlProvider {...getIntlProviderParam()}> | |
| <Router history={history as any}> | |
| <Route component={Pattern} onChange={redirector()}> | |
| <Route path={PATH_INPUT} component={Input}/> | |
| <Route path={PATH_LIST} component={List}/> | |
| <Route path={PATH_EDITOR} component={Editor}/> | |
| <Route path='/tableinput' component={TableInput}/> | |
| <Route path='/itemlist' component={ItemList}/> |
| function CControl() { | |
| }; | |
| CControl.prototype = new CObject(); | |
| CControl.prototype.init = function (elementId, focusableClassName, focusedClassName, focusChangedEventHandler) { | |
| //DBG('CControl.init [' + this.getName() + ']'); | |
| var a = this; | |
| a._app = gApp; | |
| a._shown = false; | |
| a._isGlobal = false; |
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta charset="utf-8"> | |
| <title>Face Emotion Detection</title> | |
| <meta name="viewport" content="width=device-width,initial-scale=1.0,maximum-scale=1.0,minimum-scale=1.0,user-scalable=no"> | |
| <link rel="stylesheet" href="//cdnjs.cloudflare.com/ajax/libs/meyer-reset/2.0/reset.css"> | |
| <link rel="stylesheet" href="//cdn.jsdelivr.net/xeicon/2/xeicon.min.css"> | |
| <script src="//cdnjs.cloudflare.com/ajax/libs/less.js/2.7.2/less.min.js"></script> |