Baskara agtbaskara

Ubuntu 24.04 Installation Recipe

A guide to setting up Ubuntu 24.04

Operating System Install

Download the Ubuntu ISO (https://releases.ubuntu.com/24.04/).
Build a bootable USB using Rufus (https://rufus.ie/) or balenaEtcher (https://etcher.balena.io/).
Boot from the USB and start the installation.
Fill in your name, username, and password.
Do not change the location (use New York / US).
Restart after the install completes.
Log in.

Using Docker

Before building the docker image go to the cloned whill-robot directory

cd ~/catkin_ws/src/whill-robot

Build Docker images

Place the python scripts on ~/.custom_scripts/msi-mystic-1562-rgb-off.py then add this to Ubuntu Startup to turnoff keyboard light at boot (change agtbaskara to your username)

Name:

msi-mystic-1562-rgb-off

Command:

	My recommendation is to start with RTL basics in verilog using one of the online platforms.

	https://hdlbits.01xz.net/wiki/Main_Page

	https://chipdev.io/question-list

	https://www.edaplayground.com/

	And verilog docs:

	import os

	import cv2
	from enlighten_inference import EnlightenOnnxModel
	from tqdm import tqdm

	# Set input and output path
	input_path = 'image_rgb'
	output_path = 'image_enlighten'

	import os
	import shutil

	from tqdm import tqdm
	from natsort import natsorted

	if __name__ == '__main__':
	dirlist = ['tut-sync/tut-ringroad/day/image_depth', 'tut-sync/tut-ringroad/night/image_depth',
	'tut-sync/tut-backyard/day/image_depth', 'tut-sync/tut-backyard/night/image_depth']

	import os
	import argparse

	import cv2


	# Setup Argument Parser
	parser = argparse.ArgumentParser()

	parser.add_argument('-i', '--image_dir', type=str, default='', help='input directory')

	import os

	import cv2
	import skvideo.io
	import numpy as np
	import pandas as pd
	from tqdm import tqdm

	if __name__ == '__main__':
	reference_file_path = os.path.join('town07.csv')

	# Just adding example if noob like me came here to find how to calculate the Cosine similarity from scratch
	# Source https://github.com/facebookresearch/faiss/issues/95

	import numpy as np
	import faiss

	dataSetI = [.1, .2, .3]
	dataSetII = [.4, .5, .6]
	#dataSetII = [.1, .2, .3]