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@KylePDavis
KylePDavis / sh_env_var_opts.sh
Last active September 14, 2023 01:26
Simple bash shell script templates. There are two versions: 1) simple env var based options, and 2) with added command line argument parsing and error handling.
#!/bin/bash -e
# A SHORT DESCRIPTION OF YOUR SCRIPT GOES HERE
# USAGE:
# DESCRIPTION OF ENV VARS HERE
###############################################################################
set -e # exit on command errors (so you MUST handle exit codes properly!)
set -o pipefail # capture fail exit codes in piped commands
#set -x # execution tracing debug messages
# Get command info
@sloria
sloria / bobp-python.md
Last active May 12, 2024 06:54
A "Best of the Best Practices" (BOBP) guide to developing in Python.

The Best of the Best Practices (BOBP) Guide for Python

A "Best of the Best Practices" (BOBP) guide to developing in Python.

In General

Values

  • "Build tools for others that you want to be built for you." - Kenneth Reitz
  • "Simplicity is alway better than functionality." - Pieter Hintjens
# Hello, and welcome to makefile basics.
#
# You will learn why `make` is so great, and why, despite its "weird" syntax,
# it is actually a highly expressive, efficient, and powerful way to build
# programs.
#
# Once you're done here, go to
# http://www.gnu.org/software/make/manual/make.html
# to learn SOOOO much more.
@jeffbass
jeffbass / zmqimage.py
Last active November 6, 2022 16:59
zmqimage.py -- classes to send, receive and display OpenCV images from a headless computer to a display computer using cv2.imshow()
# zmqimage.py -- classes to send, receive and display cv2 images via zmq
# based on serialization in pyzmq docs and pyzmq/examples/serialization
'''
PURPOSE:
These classes allow a headless (no display) computer running OpenCV code
to display OpenCV images on another computer with a display.
For example, a headless Raspberry Pi with no display can run OpenCV code
and can display OpenCV images on a Mac with a display.
USAGE:
@eerwitt
eerwitt / load_jpeg_with_tensorflow.py
Created January 31, 2016 05:52
Example loading multiple JPEG files with TensorFlow and make them available as Tensors with the shape [[R, G, B], ... ].
# Typical setup to include TensorFlow.
import tensorflow as tf
# Make a queue of file names including all the JPEG images files in the relative
# image directory.
filename_queue = tf.train.string_input_producer(
tf.train.match_filenames_once("./images/*.jpg"))
# Read an entire image file which is required since they're JPEGs, if the images
# are too large they could be split in advance to smaller files or use the Fixed
@yrevar
yrevar / imagenet1000_clsidx_to_labels.txt
Last active May 10, 2024 05:27
text: imagenet 1000 class idx to human readable labels (Fox, E., & Guestrin, C. (n.d.). Coursera Machine Learning Specialization.)
{0: 'tench, Tinca tinca',
1: 'goldfish, Carassius auratus',
2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
3: 'tiger shark, Galeocerdo cuvieri',
4: 'hammerhead, hammerhead shark',
5: 'electric ray, crampfish, numbfish, torpedo',
6: 'stingray',
7: 'cock',
8: 'hen',
9: 'ostrich, Struthio camelus',
@ipbastola
ipbastola / clean-up-boot-partition-ubuntu.md
Last active May 22, 2024 19:07
Safest way to clean up boot partition - Ubuntu 14.04LTS-x64, Ubuntu 16.04LTS-x64

Safest way to clean up boot partition - Ubuntu 14.04LTS-x64, Ubuntu 16.04LTS-x64

Reference

Case I: if /boot is not 100% full and apt is working

1. Check the current kernel version

$ uname -r 
@pratos
pratos / condaenv.txt
Created November 30, 2016 07:01
To package a conda environment (Requirement.txt and virtual environment)
# For Windows users# Note: <> denotes changes to be made
#Create a conda environment
conda create --name <environment-name> python=<version:2.7/3.5>
#To create a requirements.txt file:
conda list #Gives you list of packages used for the environment
conda list -e > requirements.txt #Save all the info about packages to your folder
@mjdietzx
mjdietzx / waya-dl-setup.sh
Last active March 13, 2024 15:08
Install CUDA Toolkit v8.0 and cuDNN v6.0 on Ubuntu 16.04
#!/bin/bash
# install CUDA Toolkit v8.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-get update
sudo apt-get -y install cuda
@peterhellberg
peterhellberg / ffserver.conf
Last active December 2, 2022 06:30
MJPEG stream from Webcam using FFServer and FFMpeg
HTTPPort 8090
HTTPBindAddress 0.0.0.0
MaxHTTPConnections 200
MaxClients 100
MaxBandWidth 500000
CustomLog -
<Feed camera.ffm>
File /tmp/camera.ffm
FileMaxSize 200M