semvec/pypi-packages huggingface dataset:
ecadataset 0.3.4
Python loader for the Endoscopic Content Area (ECA) dataset.
License: MIT

# Endoscopic Content Area (ECA) dataset
A simple python loader for the [Endoscopic Content Area (ECA) dataset](https://doi.org/10.7303/syn32148000). An implementation of the [hausdorff distance](https://en.wikipedia.org/wiki/Hausdorff_distance), optimised for content areas, is also included in the package.

[![Build Status](https://github.com/charliebudd/eca-dataset/actions/workflows/release.yml/badge.svg)](https://github.com/charliebudd/eca-dataset/actions/workflows/release.yml)

## Installation
To use this dataset, first ensure you have a synapse account, then simply install from pip...
```bash
pip install ecadataset
```
and run the download command...
```bash
ecadataset download -d path/to/dataset
```
You'll be prompted for your synapse credentials and the data will be downloaded. 
You may also check an existing copy of the dataset with the check command...
```bash
ecadataset check -d path/to/dataset
```

## Usage

```python
import matplotlib.pyplot as plt
from ecadataset import ECADataset, DataSource, AnnotationType, content_area_hausdorff

# Create dataset object...
dataset = ECADataset(
  # Path to the directory containing the dataset.
  data_directory="path/to/dataset",
  # Options are: DataSource.CHOLEC, DataSource.ROBUST, and DataSource.BOTH.
  data_source=DataSource.BOTH,
  # Options are: AnnotationType.AREA, AnnotationType.MASK, and AnnotationType.BOTH.
  annotation_type=AnnotationType.BOTH,
  # Whether to use cropping to provide additonal samples without a content area.
  include_cropped=True,
  # Whether to include information about where the frame was taken from.
  include_source_info=True
)

# Iterate through the first 10 samples, slicing is supported...
for image, area, mask, info in dataset[:10]:

    # Circular content area represented as (x, y, r) or None if no area present...
    print("Content area: ", area)
    
    # Origin information in the form (dataset, video, frame)...
    print("Sample source: ", info)
    
    # Image and mask are returned as PIL images...
    plt.subplot(121)
    plt.imshow(image)
    plt.subplot(122)
    plt.imshow(mask)
    plt.show()
    
    # Guessing the content area circle and scoring it against the ground truth...
    width, height = image.size
    area_guess = (width//2, height//2, width//2)
    score, _ = content_area_hausdorff(area_guess, area, (height, width))
    print(score)
```
zop-cms 0.1.0
My short description for my project.
License: MIT
Requires Python: >=3.6.0


📦 setup.py (for humans)
=======================

This repo exists to provide [an example setup.py] file, that can be used
to bootstrap your next Python project. It includes some advanced
patterns and best practices for `setup.py`, as well as some
commented–out nice–to–haves.

For example, this `setup.py` provides a `$ python setup.py upload`
command, which creates a *universal wheel* (and *sdist*) and uploads
your package to [PyPi] using [Twine], without the need for an annoying
`setup.cfg` file. It also creates/uploads a new git tag, automatically.

In short, `setup.py` files can be daunting to approach, when first
starting out — even Guido has been heard saying, "everyone cargo cults
thems". It's true — so, I want this repo to be the best place to
copy–paste from :)

[Check out the example!][an example setup.py]

Installation
-----

```bash
cd your_project

# Download the setup.py file:
#  download with wget
wget https://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.py -O setup.py

#  download with curl
curl -O https://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.py
```

To Do
-----

-   Tests via `$ setup.py test` (if it's concise).

Pull requests are encouraged!

More Resources
--------------

-   [What is setup.py?] on Stack Overflow
-   [Official Python Packaging User Guide](https://packaging.python.org)
-   [The Hitchhiker's Guide to Packaging]
-   [Cookiecutter template for a Python package]

License
-------

This is free and unencumbered software released into the public domain.

Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any means.

  [an example setup.py]: https://github.com/navdeep-G/setup.py/blob/master/setup.py
  [PyPi]: https://docs.python.org/3/distutils/packageindex.html
  [Twine]: https://pypi.python.org/pypi/twine
  [image]: https://farm1.staticflickr.com/628/33173824932_58add34581_k_d.jpg
  [What is setup.py?]: https://stackoverflow.com/questions/1471994/what-is-setup-py
  [The Hitchhiker's Guide to Packaging]: https://the-hitchhikers-guide-to-packaging.readthedocs.io/en/latest/creation.html
  [Cookiecutter template for a Python package]: https://github.com/audreyr/cookiecutter-pypackage