sudo apt-get install python3-pip
sudo pip3 install virtualenv
| #!/bin/bash | |
| ################################################################################ | |
| ### OpenCV2 Installation Script ### | |
| ################################################################################ | |
| # Source code at https://github.com/arthurbeggs/scripts # | |
| ################################################################################ | |
| # # | |
| # Feel free to copy and modify this file. Giving me credit for it is your # | |
| # choice, but please keep references to other people's work, which I don't # |
| def validation_required(validator_function): | |
| def decorator(function): | |
| async def error(websocket, err): | |
| await websocket.send(err) | |
| async def wrapper(websocket, data): | |
| status, err = validator_function(data) | |
| if status: |
| # https://conda.io/docs/user-guide/tasks/manage-environments.html | |
| conda create --name myenv | |
| # how install a sepcific version of package | |
| # https://github.com/lopatovsky/HMMs/issues/4 | |
| conda install cython=0.25.2 | |
| conda env list |
| from flask import Flask, escape, url_for, request, redirect, session | |
| from werkzeug.utils import secure_filename | |
| #Instancier une application Flask | |
| app = Flask(__name__) | |
| # Set the secret key to some random bytes. Keep this really secret! | |
| app.secret_key = b'_5#y2L"F4Q8z\n\xec]/' | |
| ########################## |
| import logging | |
| import pika | |
| import configparser | |
| LOG_FORMAT = ('%(levelname) -10s %(asctime)s %(name) -30s %(funcName) ' | |
| '-35s %(lineno) -5d: %(message)s') | |
| LOGGER = logging.getLogger(__name__) | |
| class RabbitmqManager: |
| from threading import Thread, Event | |
| event = Event() | |
| def worker(number, outputs, exit_code): | |
| msg = "=== Table de mulitiplication par {}".format(number) | |
| outputs.append(msg) |
| import os, argparse | |
| import tensorflow as tf | |
| from tensorflow.python.tools import freeze_graph as freeze_tool | |
| def freeze_graph(sess, input_checkpoint_path): | |
| saver = tf.train.Saver() # or your own Saver | |
| saver.restore(sess, input_checkpoint_path) | |
| absolute_model_dir = 'absolute_model_dir1111' | |
| graph_file_name = 'tf-model_graph' |
Typing vagrant from the command line will display a list of all available commands.
Be sure that you are in the same directory as the Vagrantfile when running these commands!
vagrant init -- Initialize Vagrant with a Vagrantfile and ./.vagrant directory, using no specified base image. Before you can do vagrant up, you'll need to specify a base image in the Vagrantfile.vagrant init <boxpath> -- Initialize Vagrant with a specific box. To find a box, go to the public Vagrant box catalog. When you find one you like, just replace it's name with boxpath. For example, vagrant init ubuntu/trusty64.vagrant up -- starts vagrant environment (also provisions only on the FIRST vagrant up)