robhrt7

This is a fork of original gist https://gist.github.com/nrollr/3f57fc15ded7dddddcc4e82fe137b58e, with slight changes on pointing to 5.7 version branch, instead of 8 (latest default of MySQL in Hombrew).

Install MySQL 5.7 on macOS

This procedure explains how to install MySQL using Homebrew on macOS (Sierra 10.12 and up)

Install Homebrew

• Installing Homebrew is effortless, open Terminal and enter :
  $ /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
• Note: Homebrew will download and install Command Line Tools for Xcode 8.0 as part of the installation process.

gauravkaila

# Create stub
host, port = FLAGS.server.split(':')
channel = implementations.insecure_channel(host, int(port))
stub = prediction_service_pb2.beta_create_PredictionService_stub(channel)

# Create prediction request object
request = predict_pb2.PredictRequest()

# Specify model name (must be the same as when the TensorFlow serving serving was started)
request.model_spec.name = 'obj_det'

5ZSQ

/**
 * Copyright (C) 2009-2010 Yichuan, Fuchun All rights reserved.
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements. See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License. You may obtain a copy of the License at
 * http://www.apache.org/licenses/LICENSE-2.0
 * Unless required by applicable law or agreed to in writing, software

AshikNesin

import React from 'react'
import axios, { post } from 'axios';

class SimpleReactFileUpload extends React.Component {

  constructor(props) {
    super(props);
    this.state ={
      file:null
    }

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

maraoz

{
 0: 'tench, Tinca tinca',
 1: 'goldfish, Carassius auratus',
 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
 3: 'tiger shark, Galeocerdo cuvieri',
 4: 'hammerhead, hammerhead shark',
 5: 'electric ray, crampfish, numbfish, torpedo',
 6: 'stingray',
 7: 'cock',
 8: 'hen',

xiangst0816

<a href="">
  <div class="cbCoorBox_e">
    <img src="img/index/hanya.png" alt="合作机构">
  </div>
</a>

pjb3

$ cat ~/.irbrc
cat: /Users/pbarry/.irbrc: No such file or directory
$ rails c
Loading development environment (Rails 4.0.0)
irb(main):001:0> Subscription.first
  Subscription Load (2.5ms)  SELECT "subscriptions".* FROM "subscriptions" ORDER BY "subscriptions"."id" ASC LIMIT 1
=> nil
irb(main):002:0> puts ENV.keys.sort
Apple_PubSub_Socket_Render
Apple_Ubiquity_Message

hydra35

# 1. Make sure you have nginx sub module compiled in
# nginx -V  2>&1 | grep --color=always '\-\-with\-http_sub_module'

# 2. add two directives below at HTTP level

# nginx.conf
http {
        # ......

        sub_filter  '</head>' '<style type="text/css">html{ filter: progid:DXImageTransform.Microsoft.BasicImage(grayscale=1); -webkit-filter: grayscale(100%); filter: url("data:image/svg+xml;utf8,<svg xmlns=\'http://www.w3.org/2000/svg\'><filter id=\'grayscale\'><feColorMatrix type=\'matrix\' values=\'0.3333 0.3333 0.3333 0 0 0.3333 0.3333 0.3333 0 0 0.3333 0.3333 0.3333 0 0 0 0 0 1 0\'/></filter></svg>#grayscale"); /* Firefox 10+, Firefox on Android */

nbibler

if [ -f "$rvm_path/scripts/rvm" ]; then
  source "$rvm_path/scripts/rvm"

  if [ -f ".rvmrc" ]; then
    source ".rvmrc"
  fi

  if [ -f ".ruby-version" ]; then
    rvm use `cat .ruby-version`
  fi