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Merge pull request #13 from thewtex/ij-link
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DOC: Add Python installation, IJ link
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thewtex committed Dec 15, 2022
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18 changes: 14 additions & 4 deletions README.md
Expand Up @@ -6,12 +6,15 @@ ITKRANSAC

Overview
--------

This is the source code for a C++ templated implementation of the RANSAC
algorithm. The implementation is multi-threaded. This repository is only for
pointset registratation and differs slightly from the original generic implementation due to optimization.
algorithm and associated Python wrapping. The implementation is
multi-threaded. This repository is only for pointset registratation and
differs slightly from the original generic implementation due to optimization.

For implementation related to plane and sphere estimation
please refer https://github.com/midas-journal/midas-journal-769.
please refer https://github.com/midas-journal/midas-journal-769 and the
[associated Insight Journal article](https://doi.org/10.54294/ia6mzx).

The code is "in the style of ITK". That is, it is very similar to the official
ITK style but does not follow all of the required conventions.
Expand All @@ -25,6 +28,12 @@ defines an interface.
3. [itkLandmarkRegistrationEstimator.{h,hxx}](./include/itkLandmarkRegistrationEstimator.hxx) - Estimation code for landmark based pointset registration.
4. [Testing/*.cxx](./test/itkRansacTest_LandmarkRegistration) - Test for the PointSet registration using landmark points.

Python wrapping installation:

```
pip install itk-ransac
```

<br/><br/>
**Sample Usage in Python for 3D PointSet is shown here:**
```python
Expand All @@ -50,13 +59,14 @@ ransacEstimator.SetAgreeData(agreeData)
ransacEstimator.SetMaxIteration(number_of_iterations)
ransacEstimator.SetNumberOfThreads(8)
ransacEstimator.SetParametersEstimator(registrationEstimator)

percentageOfDataUsed = ransacEstimator.Compute( transformParameters, desiredProbabilityForNoOutliers )
for i in transformParameters:
print(i)
```

<br/><br/>

**Landmarks can be obtained by performing feature matching.**

For this one can use the [ITKFPFH](https://github.com/InsightSoftwareConsortium/ITKFPFH) library.

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