doc

README.rst

@@ -29,8 +29,8 @@ They are computed based on the eigenvalues and eigenvectors:
 
 It's inspired from a similar tool in `CloudCompare <https://www.danielgm.net/cc/>`_.
 
-It can use multiple cpus, and the performance is quite good 
-(at least twice as fast as CloudCompare).
+It's implemented in cython using the BLAS and LAPACK scipy wrappers. It can use multiple cpus, 
+and the performance is quite good (at least twice as fast as CloudCompare).
 
 .. _`Contour detection in unstructured 3D point clouds`: https://ethz.ch/content/dam/ethz/special-interest/baug/igp/photogrammetry-remote-sensing-dam/documents/pdf/timo-jan-cvpr2016.pdf
 

setup.py

@@ -94,11 +94,11 @@ def build_extensions(self):
 setup(
     name="jakteristics",
     version=version,
-    description="Calcul des features d'un nuage de points, optimisé avec cython.",
+    description="Point cloud geometric properties from python.",
     long_description=readme + "\n\n" + history,
     author="David Caron",
     author_email="[email protected]",
-    # url='https://github.com/jakarto3d/jakteristics',
+    url="https://github.com/jakarto3d/jakteristics",
     packages=["jakteristics"],
     package_dir={"jakteristics": "jakteristics"},
     package_data={"": ["*.pyx", "*.pxd", "*.h", "*.cpp"]},