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shuokay / Activate Office 2019 for macOS VoL.md
Created Mar 30, 2021 — forked from zthxxx/Activate Office 2019 for macOS VoL.md
crack activate office on mac with license file
View Activate Office 2019 for macOS VoL.md

Activate MS Office 2019/2016 for macOS - Microsoft_Office_2019_VL_Serializer

Office 2019 above

2019-06-03

Note that Office2019 DO NOT support activate via simple copy/paste plist license file which is the simplest way to activate Office 2016. Fortunately, you can also use the VL Serializer tool, just install Office 2019 and Serializer, then run Serializer to activate.

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@shuokay
shuokay / mac zshrc
Created Jan 22, 2018
mac zshrc config
View mac zshrc
# If you come from bash you might have to change your $PATH.
# export PATH=$HOME/bin:/usr/local/bin:$PATH
# Path to your oh-my-zsh installation.
export ZSH=/Users/didi/.oh-my-zsh
# Set name of the theme to load. Optionally, if you set this to "random"
# it'll load a random theme each time that oh-my-zsh is loaded.
# See https://github.com/robbyrussell/oh-my-zsh/wiki/Themes
# ZSH_THEME="robbyrussell"
View tmux.conf
# remap prefix from 'C-b' to 'C-a'
# set -g default-terminal "screen-256color"
unbind C-b
set-option -g prefix C-a
bind-key C-a send-prefix
# split panes using | and -
bind / split-window -h -c "#{pane_current_path}"
bind - split-window -v -c "#{pane_current_path}"
unbind '"'
@shuokay
shuokay / detect.cc
Last active Feb 15, 2019
SSD inference using MXNet C API
View detect.cc
#include <stdio.h>
// Path for c_predict_api
#include <mxnet/c_predict_api.h>
#include <iostream>
#include <fstream>
#include <string>
#include <vector>
View MXNet config.mk
#-------------------------------------------------------------------------------
# Template configuration for compiling mxnet
#
# If you want to change the configuration, please use the following
# steps. Assume you are on the root directory of mxnet. First copy the this
# file so that any local changes will be ignored by git
#
# $ cp make/config.mk .
#
# Next modify the according entries, and then compile by
@shuokay
shuokay / log.txt
Last active Oct 19, 2016
mxnet wavenet training log
View log.txt
[tts] python train.py master ✭ ✱ [78/1825]
2016-10-19 14:34:39,821 Start training with [gpu(3)]
2016-10-19 14:35:02,437 Epoch[0] Batch [10] Speed: 8.75 samples/sec Train-mymae=57.056759
2016-10-19 14:35:22,736 Epoch[0] Batch [20] Speed: 7.88 samples/sec Train-mymae=30.858146
2016-10-19 14:35:42,603 Epoch[0] Batch [30] Speed: 8.05 samples/sec Train-mymae=29.581398
2016-10-19 14:36:03,529 Epoch[0] Batch [40] Speed: 7.65 samples/sec Train-mymae=28.388074
2016-10-19 14:36:23,578 Epoch[0] Batch [50] Speed: 7.98 samples/sec Train-mymae=29.426588
2016-10-19 14:36:44,323 Epoch[0] Batch [60] Speed: 7.71 samples/sec Train-mymae=29.216556
2016-10-19 14:37:06,312 Epoch[0] Batch [70] Speed: 7.28 samples/sec Train-mymae=27.873466
2016-10-19 14:37:26,722 Epoch[0] Batch [80] Speed: 7.84 samples/sec Train-mymae=29.810743
View C++ Predict with caffe
#include <cuda_runtime.h>
#include <cstring>
#include <cstdlib>
#include <vector>
#include <string>
#include <iostream>
#include <stdio.h>
#include "caffe/caffe.hpp"
View C++ Predict with caffe
#include <cuda_runtime.h>
#include <cstring>
#include <cstdlib>
#include <vector>
#include <string>
#include <iostream>
#include <stdio.h>
#include "caffe/caffe.hpp"