Christian Engel protortyp

## upload_time_in_days.py
def upload_time_in_days(mbps, tb):
    mbps_in_MBps = mbps / 8
    tb_in_MB = tb * 1000000

    total_seconds = tb_in_MB / mbps_in_MBps
    total_days = total_seconds / (60 * 60 * 24)

    return total_days

## Dockerfile
FROM --platform=linux/amd64 ubuntu:22.04

ENV DEBIAN_FRONTEND=noninteractive

RUN apt-get update && \
    apt-get install -y curl unzip wget zsh \
    libopenblas-dev \
    libjpeg-dev \
    libpng-dev \
    build-essential \

## x2
# Wait for the transform to become available
listener.waitForTransform('/base_link', '/end_effector', rospy.Time(), rospy.Duration(4.0))

# Get the transformation matrix from the robot base to the end effector
(trans, rot) = listener.lookupTransform('/base_link', '/end_effector', rospy.Time(0))

rot_matrix = tf.transformations.quaternion_matrix(rot)

transformation_matrix = tf.transformations.concatenate_matrices(rot_matrix, tf.transformations.translation_matrix(trans))

## x
import rospy
import tf
from geometry_msgs.msg import Quaternion

# Create a quaternion object
quat = Quaternion()
quat.x = 0.1
quat.y = 0.2
quat.z = 0.3
quat.w = 0.4

## gist:614e027facb735f9bcf21ffc9e3ca906
#!/usr/bin/env python
import rospy
import cv2
from sensor_msgs.msg import Image
from cv_bridge import CvBridge
from PyCapture2 import *

def image_publisher():
    rospy.init_node('epiphan_image_publisher', anonymous=True)
    pub = rospy.Publisher('image_topic', Image, queue_size=10)

## daily_note.md

      
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                protortyp
                / daily_note.md
            
            
              Created
              March 5, 2023 10:17
            
              
                Obsidian Daily Note Template
              
          
    <%*
let weekNumber = moment().format('W')
let year = moment().format('Y')
let month = tp.date.now("MM-MMMM")
let yesterday = tp.date.now("YYYY-MM-DD_ddd", -1)
let today = tp.date.now("YYYY-MM-DD_ddd")
let tag = "#cw" + weekNumber + "_" + year
let prevTag = #cw${weekNumber - 1}_${year}
let file_path = A_daily_notes/${year}/${month}/${today}
%>

  
## tum_ds_2022.md

      
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                protortyp
                / tum_ds_2022.md
            
            
              Created
              February 8, 2023 20:34
                — forked from bttger/tum_ds_2022.md
            
              
                My mdfc notes I collected throughout the semester with copied stuff from slides, papers, and the internet. NOT REVIEWED YET answers might be wrong and please don't copy them blindly
              
          
    Overview

Why should you make a distributed system?


The system is inherently distributed (e.g. mobile devices like smartphones)
Reliability (some nodes can fail and the system keeps functioning; fault tolerance)
Performance (process data faster by utilizing multiple nodes or achieve better latency by requesting data from a nearby node)
The capacity of a single machine isn’t enough for the task (e.g. limited memory size, bandwidth, CPU cycles, etc.; scalability)

What are the Characteristics of distributed systems?


## extract_by_sim.py
"""
Copy all images that look similar to a template to a different location.
This script finds similar areas in source images, crops the target area, and
stores the result in a target directory.
"""

import concurrent.futures
import cv2
import os
import multiprocessing

## split_datasets.py
"""
Splits a dataset of png images into train, val, and test sets.
Creates the folders and randomly chooses files.
"""
import os
import random
import argparse

try:
    import termcolor

## .aliases
alias bb='brave-browser'
alias t='tmux'
alias ta='tmux attach'
alias sagi='sudo apt-get install -y'
alias sagu='sudo apt-get update'
alias e='echo'
alias sl='exa'
#alias ls='exa'
alias sls='exa'
alias pwd='pwd -P'
	def upload_time_in_days(mbps, tb):
	mbps_in_MBps = mbps / 8
	tb_in_MB = tb * 1000000

	total_seconds = tb_in_MB / mbps_in_MBps
	total_days = total_seconds / (60 * 60 * 24)

	return total_days
	FROM --platform=linux/amd64 ubuntu:22.04

	ENV DEBIAN_FRONTEND=noninteractive

	RUN apt-get update && \
	apt-get install -y curl unzip wget zsh \
	libopenblas-dev \
	libjpeg-dev \
	libpng-dev \
	build-essential \
	# Wait for the transform to become available
	listener.waitForTransform('/base_link', '/end_effector', rospy.Time(), rospy.Duration(4.0))

	# Get the transformation matrix from the robot base to the end effector
	(trans, rot) = listener.lookupTransform('/base_link', '/end_effector', rospy.Time(0))

	rot_matrix = tf.transformations.quaternion_matrix(rot)

	transformation_matrix = tf.transformations.concatenate_matrices(rot_matrix, tf.transformations.translation_matrix(trans))
	import rospy
	import tf
	from geometry_msgs.msg import Quaternion

	# Create a quaternion object
	quat = Quaternion()
	quat.x = 0.1
	quat.y = 0.2
	quat.z = 0.3
	quat.w = 0.4
	#!/usr/bin/env python
	import rospy
	import cv2
	from sensor_msgs.msg import Image
	from cv_bridge import CvBridge
	from PyCapture2 import *

	def image_publisher():
	rospy.init_node('epiphan_image_publisher', anonymous=True)
	pub = rospy.Publisher('image_topic', Image, queue_size=10)
	"""
	Copy all images that look similar to a template to a different location.
	This script finds similar areas in source images, crops the target area, and
	stores the result in a target directory.
	"""

	import concurrent.futures
	import cv2
	import os
	import multiprocessing
	"""
	Splits a dataset of png images into train, val, and test sets.
	Creates the folders and randomly chooses files.
	"""
	import os
	import random
	import argparse

	try:
	import termcolor
	alias bb='brave-browser'
	alias t='tmux'
	alias ta='tmux attach'
	alias sagi='sudo apt-get install -y'
	alias sagu='sudo apt-get update'
	alias e='echo'
	alias sl='exa'
	#alias ls='exa'
	alias sls='exa'
	alias pwd='pwd -P'