Madhav Jha maddyonline

Transcribing Cardi B's political speech with AWS Transcribe and command-line tools

Inspired by the following exchange on Twitter, in which someone captures and posts a valuable video onto Twitter, but doesn't have the resources to easily transcribe it for the hearing-impaired, I thought it'd be fun to try out Amazon's AWS Transcribe service to help with this problem, and to see if I could do it all from the bash command-line like a Unix dork.

The instructions and code below show how to use command-line tools/scripting and Amazon's Transcribe service to transcribe the audio from online video. tl;dr: AWS Transcribe is a pretty amaz

	import asyncio
	import base64
	import json
	import os
	import pyaudio
	import shutil
	import websockets


	class AudioStreamer:

	"""
	stable diffusion dreaming
	creates hypnotic moving videos by smoothly walking randomly through the sample space

	example way to run this script:

	$ python stablediffusionwalk.py --prompt "blueberry spaghetti" --name blueberry

	to stitch together the images, e.g.:
	$ ffmpeg -r 10 -f image2 -s 512x512 -i blueberry/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p blueberry.mp4

	<!DOCTYPE html>
	<html>
	<head>
	<meta charset="utf-8" />
	<title>Remote terminal</title>

	<link rel="stylesheet" href="xterm.css" />

	<script src="terminal.class.js"></script>

	# Fast reading from the raspberry camera with Python, Numpy, and OpenCV
	# Allows to process grayscale video up to 124 FPS (tested in Raspberry Zero Wifi with V2.1 camera)
	#
	# Made by @CarlosGS in May 2017
	# Club de Robotica - Universidad Autonoma de Madrid
	# http://crm.ii.uam.es/
	# License: Public Domain, attribution appreciated

	import cv2
	import numpy as np

	import UIKit
	import AVFoundation

	class ViewController: UIViewController, AVCaptureMetadataOutputObjectsDelegate {

	@IBOutlet weak var myView: UIView!

	var session: AVCaptureSession?
	var device: AVCaptureDevice?
	var input: AVCaptureDeviceInput?

	/**
	* Fancy ID generator that creates 20-character string identifiers with the following properties:
	*
	* 1. They're based on timestamp so that they sort after any existing ids.
	* 2. They contain 72-bits of random data after the timestamp so that IDs won't collide with other clients' IDs.
	* 3. They sort lexicographically (so the timestamp is converted to characters that will sort properly).
	* 4. They're monotonically increasing. Even if you generate more than one in the same timestamp, the
	* latter ones will sort after the former ones. We do this by using the previous random bits
	* but "incrementing" them by 1 (only in the case of a timestamp collision).
	*/

	set-option -g status-utf8 on

	set -g status-interval 1
	set -g status-justify left # center align window list
	set -g status-left-length 75
	set -g status-right-length 150

	set -g status-fg white
	set -g status-bg black
	set -g status-attr bright

	// Copyright 2015 Google Inc. All Rights Reserved.
	//
	// Licensed under the Apache License, Version 2.0 (the "License");
	// you may not use this file except in compliance with the License.
	// You may obtain a copy of the License at
	//
	// http://www.apache.org/licenses/LICENSE-2.0
	//
	// Unless required by applicable law or agreed to in writing, software
	// distributed under the License is distributed on an "AS IS" BASIS,

	/*

	This example shows how you can use your data structure as a basis for
	your Firebase security rules to implement role-based security. We store
	each user by their Twitter uid, and use the following simplistic approach
	for user roles:

	0 - GUEST
	10 - USER
	20 - MODERATOR