semvec/pypi-packages huggingface dataset:
drf_health_check 0.0.12
Various health check view for the Django Framework
Requires Python: >=3.9

# drf_health_check
Various health check extensions for the Django Rest Framework

[![PyPI Version][pypi-image]][pypi-url]

[pypi-image]: https://img.shields.io/pypi/v/drf_health_check
[pypi-url]: https://pypi.org/project/drf_health_check/

# Installation

Using pip

`pip install drf_health_check`

Using pipenv

`pipenv install drf_health_check`

# Quick start
In your project’s `settings.py` add `HEALTH_CHECK_PROVIDERS`.

``` 
HEALTH_CHECK_PROVIDERS = {
    ...
    'drf_health_check.providers.DBHealthCheckProvider',
    ...
}
```

Add `drf_health_check` to `INSTALLED_APPS` 
```
INSTALLED_APPS = [
    ...
    "drf_health_check",
]
```

Add urls to you project for health-view
```
urlpatterns = [
    ...
    url("health/", include('django_health_check_view.urls')),
    ...
]
```
digicomm 0.0.3
Tools for digital communications simulations
Requires Python: >=3.6

# digicomm

Tools for digital communications simulations.

## Organization

``digicomm.py`` is the main workhorse that contains the relevant functions. This script can be imported to have access to
- functions that can add noise, phase offsets, frequency offsets to complex values representing symbols
- symbol decision functions
- perform frequency offset estimation
- derivative filters
- a MATLAB-style rcosdesign
- ...and more to come.

Folders contain example applications of the ``digicomm.py`` script, like bit error rate simulations, derivative filters, symbol synchronization, etc. The ``test\`` contains code that I used to develop functionality for a given function.
image-comparer 1.1.3
Compares two images using siamese networks
Keywords: pytorch,torch,machine,learning,image,compare,comparer,siamese,network,networks

py-image-comparer
=================

Compares two images using `Siamese Network <https://www.cs.cmu.edu/~rsalakhu/papers/oneshot1.pdf>`_ (Machine Learning) trained from a `Pytorch Implementation <https://github.com/joeyism/siamese-pytorch>`_

Installation
------------

To install, run

.. code-block:: bash

   pip install image-comparer

Usage
-----

CLI
^^^

.. code-block:: bash

   image-compare

which wil show the follow help screen

.. code-block::

   usage: image-compare [-h] [--threshold THRESHOLD] Image1-Path Image2-Path

For example, you can compare two images with

.. code-block:: bash

   image-compare tests/images/kobe.jpg tests/images/kobe2.jpg

which gives the result

.. code-block::

   kobe.jpg and kobe2.jpg are not similar

Programmatically
^^^^^^^^^^^^^^^^

With PIL

.. code-block:: python

   import image_comparer
   from PIL import Image

   image = Image.open("test/kobe.jpg")
   image2 = Image.open("test/kobe2.jpg")
   image_comparer.is_similar(image, image2, threshold=0.5)

or with OpenCV

.. code-block:: python

   import image_comparer
   import cv2

   image = cv2.imread("test/kobe.jpg")
   image2 = cv2.imread("test/kobe2.jpg")
   image_comparer.is_similar(image, image2, threshold=0.5)

API
---

Methods
^^^^^^^

``is_similar(image1: Union[Image.Image, np.ndarray], image2: Union[Image.Image, np.ndarray], threshold=0.5)``\ : Checks if the two images are similar based on the reshold passed

``calculate_score(image1: Union[Image.Image, np.ndarray], image2: Union[Image.Image, np.ndarray])``\ : Calculates the score between the two images. The higher the score, the more closely the two images are related.

Development
-----------

Installation
^^^^^^^^^^^^

.. code-block:: bash

   pip install -r requirements-test.txt

Tests
^^^^^

To run tests, run

.. code-block:: bash

   pytest