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25 lines
1.4 KiB
ReStructuredText
25 lines
1.4 KiB
ReStructuredText
Image Matching
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==============
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Image matching is a process of finding pixel and region correspondences between two images of the same scene.
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Such correspondences are useful for 3D reconstruction of the scene and relative camera pose estimation.
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It is also known as "Wide baseline stereo" and you can read more about it at `Wide Baseline Stereo Blog <https://ducha-aiki.github.io/wide-baseline-stereo-blog/2021/01/09/wxbs-in-simple-terms.html>`_
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We provide many modules and functions for the image matching: from building blocks like `local feature detectors <https://kornia.readthedocs.io/en/latest/feature.html#detectors>`_, `descriptors <https://kornia.readthedocs.io/en/latest/feature.html#descriptors>`_,
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`descriptor matching <https://kornia.readthedocs.io/en/latest/feature.html#matching>`_, `geometric model estimation <https://kornia.readthedocs.io/en/latest/geometry.epipolar.html#fundamental>`_
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However we recommend to start with high-level API, such as :py:class:`~kornia.feature.LoFTR` you can use to find correspondence between two images.
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.. code:: python
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from kornia.feature import LoFTR
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matcher = LoFTR(pretrained="outdoor")
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input = {"image0": img1, "image1": img2}
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correspondences_dict = matcher(input)
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.. image:: https://raw.githubusercontent.com/kornia/data/main/matching/matching_loftr.jpg
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You also can go through or full tutorial using Colab found `here <https://kornia.github.io/tutorials/nbs/image_matching.html>`_.
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