Skip to main content

Ownage of ESPI image inference

Project description

espiownage

Ownage (domination) of ESPI image inference. (Pronounced like "espionage" but with a little "own" in the middle.)

Welcome to the new phase of SPNet developement -- IN PROGRESS.
In this incarnation, we'll be making it an image-segmentation code instead of an object detector, and we'll use fast.ai.

Install

Preliminaries

Ubuntu (& probably other Linuxes):

sudo apt-get install python3-tk

Mac (with Homebrew)

brew install python-tk

Then on all systems, let's set up a virtual environment called espi. I like to put my environments in ~/envs:

mkdir ~/envs; python3 -m venv ~/envs/espi; source ~/envs/espi/bin/activate

And then you want/need to update pip in case it gave you an ancient version:

python3 -m pip install pip --upgrade

Pip install

pip install espiownage

Note: the requirements on this package follow a "kitchen sink" approach so that everything a student might need gets installed, e.g. jupyter and more. (And wheel because it speeds up the installations...I think.)

How to use

If you're reading this, you probably have access to the "real" data, which sits (on my machine) in ~/Dropbox/Data/espiownage-data. So cd to that directory, i.e.,

$ cd ~/Dropbox/Data/espiownage-data

...(or whereever you've got it) for what follows.

AND THEN, so we don't "clobber" each other's work, make your own copy (~17MB) of the main annotations directory, as in append your last name (hawley, morrison, morgan, etc):

cp -r annotations annotations_yourlastname

and then we'll each edit our own copy just to avoid...confusion.

Note:If you don't have access to the real data, you can still grab the fake SPNet data and then, for each of those datasets: Move (or symlink) all the images to a directory called images/, and all the .csv files to a directory called annotations/, and proceed.

Console Scripts

See the separate page on console scripts

Contributing / Development

You'll want to install more things:

pip install nbdev twine 

Fork this repo. When you want to update your repo, one macro does it all (see Makefile):

make git_update

Asides

Handy tips for students

I can never remember how to start up virtual environments / or I don't want to remember. So in my ~/.bashrc file (you may have a ~/.zshrc) I put in a line where I define an alias/function I call gimme, that reads like so:

gimme() { source ~/envs/"$1"/bin/activate;  }

(note that in order for this alias to be recognized, you need to either logout and log back in or else run $ source ~/.bashrc)

Then when I want to load environment like espi I just type...

gimme espi

--Scott H. Hawley, September 2021

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

espiownage-0.0.36.tar.gz (30.8 kB view details)

Uploaded Source

Built Distribution

espiownage-0.0.36-py3-none-any.whl (30.8 kB view details)

Uploaded Python 3

File details

Details for the file espiownage-0.0.36.tar.gz.

File metadata

  • Download URL: espiownage-0.0.36.tar.gz
  • Upload date:
  • Size: 30.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.9.5

File hashes

Hashes for espiownage-0.0.36.tar.gz
Algorithm Hash digest
SHA256 ca66ac27dfc554188d77c5961662837703e4162f534c8b843cad474ee29c0bff
MD5 e9fbdf8588f716012780c63a2779ba97
BLAKE2b-256 f139fb075cb4f576b7541bd2b9684750bd2891b3f77a5fa8e35d9b4112032857

See more details on using hashes here.

File details

Details for the file espiownage-0.0.36-py3-none-any.whl.

File metadata

  • Download URL: espiownage-0.0.36-py3-none-any.whl
  • Upload date:
  • Size: 30.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.2 CPython/3.9.5

File hashes

Hashes for espiownage-0.0.36-py3-none-any.whl
Algorithm Hash digest
SHA256 32927db16d8f21de96ac4fc5a312a3d7a570d2ff6c11368ac9d203237fa2af0e
MD5 d5dec76301bc0b730ba3692f6fcb8aca
BLAKE2b-256 8b2a4d4a5c66f00431e8d710ac953e019a794983e286584a9290035def16c023

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page