Let's say you want to host domains first.com and second.com.
Create folders for their files:
| /** | |
| * Created by leo6104 (github.com/leo6104) | |
| * You can use this nodejs script on angular v5/v4/v2 project. | |
| * 1. Place this gist file `ng-update-v6.js` to angular project's root path | |
| * 2. use command `node ng-update-v6.js .angular-cli.json` | |
| * 3. check angular.json file (created by ng-update-v6.js) | |
| **/ | |
| const fs = require('fs'); | |
| const path = require('path'); | 
| const Web3 = require('web3'); | |
| const ZeroEx = require('0x.js').ZeroEx; | |
| const BigNumber = require('bignumber.js'); | |
| // Default provider for TestRPC | |
| const provider = new Web3.providers.HttpProvider('http://localhost:8545') | |
| // Calling constructor | |
| const zeroEx = new ZeroEx(provider); | 
| sendSigned(txData,wallet_privatekey, cb) { | |
| var web3 = this.web3; | |
| const tx = new Tx(txData) | |
| var _pk = wallet_privatekey.slice(2); | |
| var privateKey = new Buffer(_pk, 'hex'); | |
| tx.sign(privateKey) | |
| const serializedTx = tx.serialize() | |
| web3.eth.sendSignedTransaction('0x' + serializedTx.toString('hex'), cb) | |
| } | 
| var Web3 = require('web3'); | |
| var util = require('ethereumjs-util'); | |
| var tx = require('ethereumjs-tx'); | |
| var lightwallet = require('eth-lightwallet'); | |
| var txutils = lightwallet.txutils; | |
| var web3 = new Web3( | |
| new Web3.providers.HttpProvider('https://rinkeby.infura.io/') | |
| ); | |
| var address = '0x8D68583e625CAaE969fA9249502E105a21435EbF'; | |
| var key = '1ce642301e680f60227b9d8ffecad474f15155b6d8f8a2cb6bde8e85c8a4809a'; | 
| pragma solidity ^0.4.0; | |
| contract Ballot { | |
| struct Voter { | |
| uint weight; | |
| bool voted; | |
| uint8 vote; | |
| address delegate; | |
| } | |
| struct Proposal { | 
| # -*- coding: UTF-8 -*- | |
| import cv2 | |
| import numpy as np | |
| import os | |
| import random | |
| def car_position(input_file): | |
| position = [] | |
| img_gray = cv2.imread(input_file,cv2.IMREAD_GRAYSCALE) | 
| 53.380827, -2.975304 | |
| 53.385516, -2.981218 | |
| 53.385041, -2.980835 | |
| 53.384792, -2.980543 | |
| 53.384661, -2.982629 | |
| 53.384059, -2.981964 | |
| 53.383523, -2.981326 | |
| 53.383448, -2.979853 | |
| 53.383102, -2.979456 | |
| 53.383349, -2.978617 | 
| ''' | |
| texture image path are relative to the blend file directory. run from command line like this: | |
| texture=img/2012720989_c.jpg blender -b mug.blend --python texture_change.py -F PNG -s 1 -e 1 -j 1 -t 0 -a | |
| '''' | |
| import os | |
| image_file = os.getenv('texture') | |
| if not image_file: | |
| image_file="img/2012720989_c.jpg" | 
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman