semvec/pypi-packages huggingface dataset:
charticle 0.0.3
Charticle combines best (worst?) of charts and articles.
License: MIT
Keywords: chart,labels,thinkpiece

=============================================================
charticle: Combine the best (or worst) charts for thinkpieces
=============================================================

.. image:: https://readthedocs.org/projects/charticle/badge/?version=latest
   :target: http://charticle.readthedocs.io/en/latest/?badge=latest
   :alt: Documentation Status

.. image:: https://travis-ci.org/jkahn/charticle.svg
   :target: https://travis-ci.org/jkahn/charticle
   :alt: CI status

.. image:: https://codecov.io/github/jkahn/charticle/coverage.svg?branch=master
   :target: https://codecov.io/github/jkahn/charticle?branch=master
   :alt: Coverage

.. teaser-begin

``charticle`` is an `MIT
<http://choosealicense.com/licenses/mit/>`_-licensed Python package
designed to make it very easy to build new diagrams like the Drew
Conway Data Science diagram.

This may not be wise.


Release Information
===================

0.0.3 (3 July 2016)
-------------------

Changes:
^^^^^^^^

Add `charticle.hierarchy` diagrams and examples.

Supports general text and polygon arguments for outer triangle & layers.

Cleanups:

- wishlist, release procedures added to repo.
- Jupyter notebooks removed from repo.
- py27 testing included in `tox.ini`.
- refactoring validators.
- cleaned up release procedure.

----


0.0.2 (30 June 2016)
--------------------

Changes:
^^^^^^^^

Support Venn2 diagrams (and Venn3).

Improve documentation examples and testing.

`Full changelog <https://charticle.readthedocs.io/en/latest/changelog.html>`_.

Credits
=======

``charticle`` is written and maintained by `Jeremy G. Kahn
<https://trochee.net/>`_.

Collaboration and kibitzing due to `Bill McNeill
<https://cornercases.wordpress.net/>`_.

A full list of contributors can be found in `GitHub's overview
<https://github.com/jkahn/charticle/graphs/contributors>`_.
processpathway 0.3.11
A nifty little toolkit to create stress-free, frustrationless image processing pathways from your webcam for computer vision experiments. Or observing your cat.
License: MIT
Keywords: image processing,computer vision,opencv

ProcessPathway
--------------

ProcessPathway is a nifty little tool that lets you play with image processing algorithms instead of wiring up your test
bench all day. It is designed to feed a video camera input (a webcam, usually) through any functions that can digest and
return a numpy matrix (think OpenCV).

How to use
==========

The `example_threshold.py` example, which - as the name suggests - thresholds the the webcam input, is a good example 
for what a typical ProcessPathway pipeline would look like:

```python
import cv2
from processpathway import LiveProcess
```
First, import the LiveProcess object from processpathway. You might want to also import whatever processing functions
you need.

```
def convert_to_grayscale(_frame):
    _frame = cv2.cvtColor(_frame, cv2.COLOR_BGR2GRAY)
    return _frame

def threshold(_frame):
    _, _frame = cv2.threshold(_frame, 128, 255, cv2.THRESH_BINARY)
    return _frame

def reconvert_to_bgr(_frame):
    _frame = cv2.cvtColor(_frame, cv2.COLOR_GRAY2BGR)
    return _frame
```

Write your functions. The only constraint is that they should take and emit a numpy.ndarray image. Of course, that does 
not mean you can't code whatever side effects you need them to generate!

```
if __name__ == '__main__':
    processor = LiveProcess(fps=True)
    processor.bind_process(convert_to_grayscale, threshold, reconvert_to_bgr)
    processor.initialise_capture_device(0)
    processor.loop()
```

Upon call, attach `LiveProcess` to a variable, then bind the processing functions to it, *in the order you want them to 
be performed*! Then, bind a capture device and initialise it. Finally, start the loop.

Built-in functionalities
========================

* FPS calculation (use `fps=True` when constructing your `LiveProcess` instance)
* Screenshotting (bound to the `s` key, on by default but can be disabled using `screencap=False` in the `LiveProcess`
constructor
* Automatic clean-up and closedown (using the `esc` key by default)
* And lots more...

Todos
=====

* Tests!
* Documentation!
polycircles 0.3.7
Polycircles: WGS84 Circle approximations using polygons
License: MIT

polycircles
===========

Polycircles: KML (WGS84) circle approximation using polygons with many vertices.

`Build Status <https://travis-ci.org/adamatan/polycircles>`_

.. image:: https://travis-ci.org/adamatan/polycircles.svg?branch=master
   :target: https://travis-ci.org/adamatan/polycircles
   :alt: Build Status

.. image:: https://badge.fury.io/py/polycircles.svg
   :target: https://pypi.python.org/pypi/polycircles

.. image:: https://raw.githubusercontent.com/adamatan/polycircles/master/docs/_static/kml_manhattan.png
    :width: 500px
    :align: center
    :alt: Example: A circle around Columbus Circle, Manhattan


[![Downloads](https://pypip.in/download/polycircles/badge.png)](https://pypi.python.org/pypi/polycircles/)

[![Manhattan example]()

Approximate a circle using a 36-vertices polygon:

.. code-block:: python

	>>> from polycircles import polycircles
	>>> polycircle = polycircles.Polycircle(latitude = 32.074322, longitude=34.792081, radius=100, number_of_vertices=36)
	>>> polycircle.to_lat_lon()
	((32.075223809870174, 34.792081), (32.075210109219384, 34.79226491831068),
	 (32.07516942356622, 34.792443248196115), (32.07510298915787, 34.792610571051924),
	 (32.075012824622526, 34.79276180275308), (32.074901669628204, 34.792892348145145),
	 (32.07477290163153, 34.792998240672475), (32.07463043324713, 34.793076262899916),
	 (32.074478593357114, 34.79312404426628), (32.07432199557388, 34.79314013310001),
	 (32.0741653980537, 34.79312404071046), (32.07401355892112, 34.793076256217155),
	 (32.07387109169717, 34.79299823166882), (32.073742325123995, 34.792892337906565),
	 (32.073631171644536, 34.79276179251449), (32.07354100853271, 34.79261056204826),
	 (32.073474575284784, 34.792443241513354), (32.07343389038906, 34.79226491475485),
	 (32.07342019000133, 34.792081), (32.07343389038906, 34.791897085245154),
	 (32.073474575284784, 34.79171875848665), (32.07354100853271, 34.791551437951746),
	 (32.073631171644536, 34.791400207485516), (32.073742325123995, 34.79126966209344),
	 (32.07387109169717, 34.79116376833119), (32.07401355892112, 34.79108574378285),
	 (32.0741653980537, 34.79103795928955), (32.07432199557388, 34.791021866899996),
	 (32.074478593357114, 34.79103795573373), (32.07463043324713, 34.79108573710009),
	 (32.07477290163153, 34.79116375932753), (32.074901669628204, 34.79126965185486),
	 (32.075012824622526, 34.79140019724693), (32.07510298915787, 34.79155142894808),
	 (32.07516942356622, 34.79171875180389), (32.075210109219384, 34.79189708168933),
	 (32.075223809870174, 34.792081))

Documentation: http://polycircles.readthedocs.org/en/latest/
Code: https://github.com/adamatan/polycircles