willmasters

# 

sudo su -

cd /usr/local/bin
mkdir ffmpeg

cd ffmpeg
wget https://www.johnvansickle.com/ffmpeg/old-releases/ffmpeg-4.2.1-amd64-static.tar.xz
tar xvf ffmpeg-4.2.1-amd64-static.tar.xz

hijak

#!/bin/bash

_usage() {
  echo "Usage: $0 CHECKNAME PROFILE"
  echo "Checks: infra, os, keys, vol"
  echo "you might want to output stdout to a .tsv file"
}


_infra () {

AAber

#!/bin/bash

# Parse df selected output
df -h|egrep -v 'File|tmpfs|docker|udev'| \
while read LINE; do
         USED_NUMBER=`echo $LINE |awk '{print $5}'|sed 's/\%//'|sed 's/ //g'`
        USED_PERCENT=`echo $LINE |awk '{print $5}'|sed 's/ //g'`
         MOUNT_POINT=`echo $LINE |awk '{print $6}'|sed 's/ //g'`
        if [ $USED_NUMBER -gt 80 ]; then
                # Create message without spaces

kylehounslow

from __future__ import print_function
import requests
import json
import cv2

addr = 'http://localhost:5000'
test_url = addr + '/api/test'

# prepare headers for http request
content_type = 'image/jpeg'

monkut

# docker build -t ubuntu1604py36
FROM ubuntu:16.04

RUN apt-get update && \
  apt-get install -y software-properties-common && \
  add-apt-repository ppa:jonathonf/python-3.6
RUN apt-get update

RUN apt-get install -y build-essential python3.6 python3.6-dev python3-pip python3.6-venv
RUN apt-get install -y git

flyyufelix

ResNet-152 in Keras

This is an Keras implementation of ResNet-152 with ImageNet pre-trained weights. I converted the weights from Caffe provided by the authors of the paper. The implementation supports both Theano and TensorFlow backends. Just in case you are curious about how the conversion is done, you can visit my blog post for more details.

ResNet Paper:

Deep Residual Learning for Image Recognition.
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
arXiv:1512.03385

pv8

#!/usr/bin/env bash
#
# Fix virtualenv symlinks after upgrading python with Homebrew and then running
# `cleanup`.
#
# After upgrading Python using Homebrew and then running `brew cleanup` one can
# get this message while trying to run python:
# dyld: Library not loaded: @executable_path/../.Python
#   Referenced from: /Users/pablo/.venv/my-app/bin/python
#   Reason: image not found

PurpleBooth

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

githubutilities

Mac Uninstall pkg Manually

• using pkgutil

# list all your installed packages
pkgutil --pkgs

# show your package info
pkgutil --pkg-info 

vladignatyev

# The MIT License (MIT)
# Copyright (c) 2016 Vladimir Ignatev
#
# Permission is hereby granted, free of charge, to any person obtaining 
# a copy of this software and associated documentation files (the "Software"), 
# to deal in the Software without restriction, including without limitation 
# the rights to use, copy, modify, merge, publish, distribute, sublicense, 
# and/or sell copies of the Software, and to permit persons to whom the Software 
# is furnished to do so, subject to the following conditions:
#