semvec/pypi-packages huggingface dataset:
qt-wsi-registration 0.0.14
Robust quad-tree based registration on whole slide images
Requires Python: >=3.6

# Robust quad-tree based registration on whole slide images

[![PyPI version fury.io](https://badge.fury.io/py/qt-wsi-registration.svg)](https://pypi.python.org/pypi/qt-wsi-registration/)
[![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://lbesson.mit-license.org/)



This is a library that implements a quad-tree based registration on whole slide images.


## Core features

* Whole Slide Image support
* Robust and fast
* Rigid and non-rigid transformation

## Additional Requirements

[Install OpennSlide](https://openslide.org/download/)


## Notebooks

Example notebooks are in the demo folder or  [![Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github//ChristianMarzahl/WsiRegistration).


## Ho-To:


Import package and create Quad-Tree.
```python
import qt_wsi_reg.registration_tree as registration

parameters = {
    # feature extractor parameters
    "point_extractor": "sift",  #orb , sift
    "maxFeatures": 512, 
    "crossCheck": False, 
    "flann": False,
    "ratio": 0.6, 
    "use_gray": False,

    # QTree parameter 
    "homography": True,
    "filter_outliner": False,
    "debug": False,
    "target_depth": 1,
    "run_async": True,
    "num_workers: 2,
    "thumbnail_size": (1024, 1024)
}

qtree = registration.RegistrationQuadTree(source_slide_path=Path("examples/4Scanner/Aperio/Cyto/A_BB_563476_1.svs"), target_slide_path="examples/4Scanner/Aperio/Cyto/A_BB_563476_1.svs", **parameters)

```

Show some registration debug information.

```python
qtree.draw_feature_points(num_sub_pic=5, figsize=(10, 10))
```

Show annotations on the source and target image in the format:

[["center_x", "center_y", "anno_width", "anno_height"]] 
```python
annos = np.array([["center_x", "center_y", "anno_width", "anno_height"]])
qtree.draw_annotations(annos, num_sub_pic=5, figsize=(10, 10))

```


Transform coordinates

```python
box = [source_anno.center_x, source_anno.center_y, source_anno.anno_width, source_anno.anno_height]

trans_box = qtree.transform_boxes(np.array([box]))[0]

```
stactools-goes 0.1.8
stactools package for working with NOAA''s GOES data
Keywords: stactools, pystac, catalog, STAC

# stactools-goes

[![PyPI](https://img.shields.io/pypi/v/stactools-goes)](https://pypi.org/project/stactools-goes/)

- Name: goes
- Package: `stactools.goes`
- [stactools-goes on PyPI](https://pypi.org/project/stactools-goes/)
- Owner: @gadomski
- [Dataset homepage](https://www.goes.noaa.gov/)
- STAC extensions used:
  - [eo](https://github.com/stac-extensions/eo/)
  - [processing](https://github.com/stac-extensions/processing/)
  - [projection](https://github.com/stac-extensions/projection/)
  - [raster](https://github.com/stac-extensions/raster/)
- Extra fields:
  - `goes:system-environment`: The environment, e.g. operational real-time, operational test, or simulated data
  - `goes:image-type`: Full disk, mesoscale, or CONUS data
  - `goes:processing-level`: The processing level of the data
  - `goes:mesoscale-image-number`: The image number of the mesoscale data (1 or 2)
- [Browse the example in human-readable form](https://radiantearth.github.io/stac-browser/#/external/raw.githubusercontent.com/stactools-packages/goes/main/examples/collection.json)

A short description of the package and its usage.

## STAC Examples

- [Collection](./examples/collection.json)
- [Item](./examples/OR_ABI-L2-M1-M6_G16_s20211231619248/OR_ABI-L2-M1-M6_G16_s20211231619248.json)

## Installation

```shell
pip install stactools-goes
```

## Command-line Usage

```shell
stac goes create-item source destination
```

Use `stac goes --help` to see all subcommands and options.

## Contributing

We use [pre-commit](https://pre-commit.com/) to check any changes.
To set up your development environment:

```shell
pip install -e .
pip install -r requirements-dev.txt
pre-commit install
```

To check all files:

```shell
pre-commit run --all-files
```

To run the tests:

```shell
pytest -vv
```
pyspeller 1.0.0
Библиотека для проверки орфографии с использованием API Яндекс Спеллер. Обертка Python для Яндекс.Спеллер.
Requires Python: >=3.12
Keywords: api, speller, yandex

# pyspeller

Библиотека для проверки орфографии с использованием [API Яндекс Спеллер][я]. Обертка Python для [Яндекс.Спеллер][я].

## Установка

```bash
pip install pyspeller
```

```bash
pip install git+https://github.com/austnv/pyspeller.git
```

## Использование

```python
from pyspeller import *

result = check_text('масква', 'ru', 'plain', ['IGNORE_URLS', 'IGNORE_DIGITS'])
print(result)

result = check_texts(['синхрафазатрон', 'олексей'])
print(result)
```

## Документация

- [Страница][1] для демонстрации работы метода `check_text`.
- [Документация][3] для метода `check_text`.
- [Страница][2] для демонстрации работы метода `check_texts`.
- [Документация][4] для метода `check_texts`.
- [Условия использования][5] сервиса «API Яндекс.Спеллер»


## Контакты

- [GitVerse][6]
- [GitHub][11]
- [Email][7]
- [Telegram][8]

## Лицензия

[The MIT License (MIT)][9]



[я]: https://yandex.ru/dev/speller/
[1]: https://speller.yandex.net/services/spellservice?op=checkText
[2]: https://speller.yandex.net/services/spellservice?op=checkTexts
[3]: https://yandex.ru/dev/speller/doc/dg/reference/checkText-docpage/
[4]: https://yandex.ru/dev/speller/doc/dg/reference/checkTexts-docpage/
[5]: https://yandex.ru/legal/speller_api/
[6]: https://gitverse.ru/ustinov
[7]: mailto:lesin2798@mail.ru?subject=pyspeller
[8]: https://t.me/austnv?text=pyspeller
[9]: LICENSE
[10]: https://ustinov.mit-license.org/
[11]: https://github.com/austnv