Mario Klingemann Quasimondo

Stream WAV Files as Bluetooth Mic Input from Raspberry Pi Zero W

Author: Mario Klingemann

Description

This guide configures a Raspberry Pi Zero W to stream WAV files (8kHz, mono PCM) to a phone via Bluetooth Hands-Free Profile (HFP), simulating a microphone for calls. Tested on Raspbian Bullseye with a Pixel 8 Pro and Pixel 6 Pro, it should work with similar setups.

Note: due to restrictions of Android it seems that headset microphones are not allowed to use certain features like voice assistant or voice typing on the keyboard. This seems to be an ongoing nuisance and I have not found a solution for it.

Note: this might not work on a Raspberry Zero 2 W, since it is using a different bluetooth chip which seems to have certain quirks.

	Designing a fair and implementable compensation model for artists in the age of AI is indeed complex, but here's a proposed framework that attempts to balance various interests:

	1. Training Data Licensing:

	- Establish a system where artists can opt-in to license their work for AI training.

	- Companies using artworks for AI training pay into a collective licensing pool.

	- Payment rates based on factors like usage frequency, uniqueness, and influence on AI outputs.

	# After a lot of searching and false or complicated leads I found this brilliant method
	# that allows to use a numpy array to get direct read/write access to the rpi framebuffer
	# https://stackoverflow.com/questions/58772943/how-to-show-an-image-direct-from-memory-on-rpi
	# I thought it is worth sharing again since so it might someone else some research time
	#
	# The only caveat is that you will have to run this as root (sudo python yourscript.py),
	# But you can get around this if you add the current user to the "video" group like this:
	# usermod -a -G video [user]
	# source: https://medium.com/@avik.das/writing-gui-applications-on-the-raspberry-pi-without-a-desktop-environment-8f8f840d9867
	#

	import torch

	#USE AT YOUR OWN RISK

	#local path to runwayML SD 1.5 checkpoint (https://huggingface.co/runwayml/stable-diffusion-v1-5)
	ckpt_15 = "./v1-5-pruned-emaonly.ckpt"

	#local path to StabilityAI finetuned autoencoder (https://huggingface.co/stabilityai/sd-vae-ft-mse)
	ckpt_vae = "./vae-ft-mse-840000-ema-pruned.ckpt"

	import json
	from urllib.request import urlopen

	def get_query_result(query, timeout=10):
	with urlopen(query, timeout=timeout) as request:
	if request.status == 200:
	return json.loads(request.read().decode())

	# Get the list of users allowed to vote
	hen_users = get_query_result("https://vote.hencommunity.quest/hen-users-snapshot-16-01-2022.json")

	sudo add-apt-repository ppa:graphics-drivers/ppa
	sudo apt update
	sudo apt upgrade

	wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin
	sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600
	wget https://developer.download.nvidia.com/compute/cuda/11.1.0/local_installers/cuda-repo-ubuntu2004-11-1-local_11.1.0-455.23.05-1_amd64.deb
	sudo dpkg -i cuda-repo-ubuntu2004-11-1-local_11.1.0-455.23.05-1_amd64.deb
	sudo apt-key add /var/cuda-repo-ubuntu2004-11-1-local/7fa2af80.pub
	sudo apt-get update

	I am attesting that this GitHub handle quasimondo is linked to the Tezos account tz1hb9PiWxQEf6J9xevPsUM6dkuCLnhDMvsp for tzprofiles

	sig:edsigtoekSaBkHWoVT4WcedEWrgHS2jfG1tsaqUGH3o9ULoFn8yzEMsAa7JsZbXwu4iKPepv98hKX2QSwi1KMkn1YX8B3tSC4be

	import os
	import pickle
	import requests

	#download cached token data here:
	#https://drive.google.com/file/d/1g_4w_Re5Y0NmcS2Y55WQzESWDeL2dey6/view?usp=sharing
	#and put it into the same folder as this file

	cachedTokenData = {"maxTokenID":-1,"knownTokenIds":{},"data":[]}
	if os.path.exists("cached_token_data.pickle"):

	import requests
	import os
	import ipfsApi

	api = ipfsApi.Client(host='https://ipfs.infura.io', port=5001)

	url = "https://better-call.dev/v1/contract/mainnet/KT1RJ6PbjHpwc3M5rw5s2Nbmefwbuwbdxton/tokens"

	r = requests.get(url)
	data = r.json()

	'''
	Usage:
	python quickwatermark.py [path to folder that contains images to waternark]

	This will go through all the files in that folder, try to open them and add
	the filename as text on top of the image. The watermarked images will be stored
	in a subfolder of the chosen folder called "watermarked"

	'''