sloev

import ffmpeg
import numpy as np
import cv2
import sys

# pip install ffmpeg-python
# pip install opencv-python
# pip install opencv-contrib-python 

sloev

import Pipe2Pam  from 'pipe2pam';
import process from 'node:process';

import  {spawn}   from 'child_process';
import imghash from 'imghash';

let counter = 0;

const params = [
    '-loglevel',

sloev

1. open up computer and flip write switch to not-write protected
remove battery from chromebook
remove power
add power
hold esc+refresh while powering on computer
go through and press enter
power off
power on
ctrl+d
wait for dev transitioning

sloev

https://www.myfonts.com/products/modern-twenty-atmodern-twenty-342197

https://render.myfonts.net/fonts/font_rend.php?id=329faf6da65317e72cd89ca34784223f&rt=You%20Make%20Me%20Smile&rs=5000&w=40000&rbe=&sc=2&nie=true&fg=94CC65&bg=000000&ft=&nf=1

sloev

import crypto from 'crypto'
import GUN from 'gun';

import 'gun/sea.js';
import 'gun/lib/open.js'
import 'gun/lib/load.js'
import { sha256 } from 'js-sha256';
import Geohash from 'latlon-geohash';

sloev

import crypto from 'crypto'
import GUN from 'gun';
import 'gun/sea.js';
import 'gun/lib/open.js'
import { sha256 } from 'js-sha256';


var SEA = GUN.SEA;
var gun = GUN()

sloev

(async () => {
    const GUN = require('gun');
    const suffix = Date.now()
    require('gun/sea')
    var SEA = GUN.SEA;
    var gun = GUN()
    async function auth( username, password ) {
        return new Promise(( resolve, reject ) => {
          gun.user()
            .auth( username, password, ack =>

sloev

(async () => {
    const GUN = require('gun');
    const dbName = "database" + new Date()
    require('gun/lib/path.js')
    var SEA = GUN.SEA;
    var gun = GUN()

    // 1......
    // create server certificate for database (allowing server to delete all user objects)
    var ServerAdmin = await SEA.pair()

sloev

1. create repo

2. install https://gitjournal.io/ on phone

3. setup gitjournal on phone

4. clone repo on computer

5. install script alias

sloev

import pickle
import json
import tensorflow as tf


from keras.models import load_model
from keras.preprocessing.sequence import pad_sequences
from keras.models import Sequential
from keras.layers import Dense, Embedding, LSTM
import tensorflow as tf