Removed optimistic benchmark table.

Author: Jaybro

README.md

@@ -4,27 +4,8 @@
 
 PicoTree is a C++ header only library with [Python bindings](https://github.com/pybind/pybind11) for nearest neighbor searches and range searches using a KdTree.
 
-See the table below to get an impression of the performance provided by the [KdTree](https://en.wikipedia.org/wiki/K-d_tree) of this library versus several other implementations:
-
-|                                     | Build C++ | Build Python  | Knn C++   | Knn Python  |
-| ----------------------------------- | --------- | ------------- | ----------| ----------- |
-| [nanoflann][nano] v1.3.2            | 3.6s      | ...           | 3.9s      | ...         |
-| [SciPy KDTree][sppk] v1.5.0         | ...       | 117.9s        | ...       | +inf        |
-| [SciPy cKDTree][spck] v1.5.0        | ...       | 9.6s          | ...       | 14.1s       |
-| [Scikit-learn KDTree][skck] 0.22.2  | ...       | 27.1s         | ...       | 55.4s       |
-| [OpenCV FLANN][cvfn] 4.5.1          | 4.1s      | ...           | 7.0s      | ...         |
-| PicoTree KdTree v0.7.1              | 1.8s      | 2.0s          | 3.1s      | 4.1s        |
-
-The comparison was generated using 13729039 3d points from a [LiDAR](./docs/benchmark.md) scan, float64, with k=1 for queries and OMP_NUM_THREADS=1. Note that a different C++ back-end was used for each of the `Knn C++` and `Knn Python` benchmarks. This means that they shouldn't be compared directly. See the [Python comparison](./examples/python/kd_tree.py) for more details. A more detailed [C++ comparison](./docs/benchmark.md) of PicoTree is available with respect to [nanoflann][nano].
-
 Available under the [MIT](https://en.wikipedia.org/wiki/MIT_License) license.
 
-[nano]: https://github.com/jlblancoc/nanoflann
-[sppk]: https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.KDTree.html
-[spck]: https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.cKDTree.html
-[skck]: https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KDTree.html
-[cvfn]: https://github.com/opencv/opencv
-
 # Capabilities
 
 * KdTree
@@ -56,7 +37,7 @@ Optional:
 * [Google Test](https://github.com/google/googletest). Used for running unit tests.
 * [Eigen](http://eigen.tuxfamily.org). To run the example that shows how Eigen data types can be used in combination with PicoTree.
 * [OpenCV](https://opencv.org/). To run the OpenCV example that shows how to work with OpenCV data types.
-* [nanoflann](https://github.com/jlblancoc/nanoflann), [Google Benchmark](https://github.com/google/benchmark) and a compiler that is compliant with the C++17 standard are needed to run the comparison [benchmark](./docs/benchmark.md) between nanoflann and PicoTree.
+* [nanoflann](https://github.com/jlblancoc/nanoflann), [Google Benchmark](https://github.com/google/benchmark) and a compiler that is compliant with the C++17 standard are needed to run the comparison benchmark between nanoflann and PicoTree.
 
 Python bindings:
 * [Python](https://www.python.org/). Version 3.5 or higher.