Metadata-Version: 2.1
Name: kornia_moons
Version: 0.2.9
Summary: Conversions between kornia and other computer vision libraries formats
Home-page: https://github.com/ducha-aiki/kornia_moons/
Author: Dmytro Mishkin
Author-email: ducha.aiki@gmail.com
License: Apache Software License 2.0
Keywords: kornia,python,pytorch,deep learning,computer vision
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: Apache Software License
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
License-File: LICENSE

Kornia_moons
================

<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->

## Install

`pip install kornia_moons`

## How to use

Here is an example how to use kornia-moons for local feature conversion
from OpenCV ORB keypoints

``` python
import matplotlib.pyplot as plt
import cv2
import torch
import kornia as K
from typing import List
import matplotlib.pyplot as plt

from kornia_moons.feature import laf_from_opencv_ORB_kpts, opencv_ORB_kpts_from_laf 
from kornia_moons.viz import visualize_LAF



img = cv2.cvtColor(cv2.imread('data/strahov.png'), cv2.COLOR_BGR2RGB)

det = cv2.ORB_create(500)
kps, descs = det.detectAndCompute(img, None)

out_img = cv2.drawKeypoints(img, kps, None, flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
plt.imshow(out_img)


lafs = laf_from_opencv_ORB_kpts(kps)
visualize_LAF(K.image_to_tensor(img, False), lafs, 0)

kps_back = opencv_ORB_kpts_from_laf(lafs)
out_img2 = cv2.drawKeypoints(img, kps_back, None, flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
plt.imshow(out_img2)
```

    libpng warning: iCCP: known incorrect sRGB profile

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