From 27674d586a8c2236dee4f51fdd63f309b245fd98 Mon Sep 17 00:00:00 2001 From: monj <monj@dtu.dk> Date: Thu, 5 Aug 2021 15:10:13 +0000 Subject: [PATCH] Binder link --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 31925e4..7336003 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ **Structure tensor tutorials** for the implementation in https://github.com/Skielex/structure-tensor. This implementation is compatible with the python package `cupy`. Therefore, if you have large volumes to process and a graphical processing unit (GPU), you can speed up your computations simply by having a working installation of [cupy](https://docs.cupy.dev/en/stable/install.html). -Run the tutorials online on Binder by pressing this link, if you want to run the tutorials locally, check our instructions for [getting started](https://lab.compute.dtu.dk/QIM/tutorials/getting-started). +Run the tutorials online on [](https://mybinder.org/v2/gl/https%3A%2F%2Flab.compute.dtu.dk%2FQIM%2Ftutorials%2Fstructuretensor/HEAD) by pressing this link, if you want to run the tutorials locally, check our instructions for [getting started](https://lab.compute.dtu.dk/QIM/tutorials/getting-started). The tutorials demonstrate the use of the structure tensor tool for the analysis of 2D and 3D data. The tutorials come with a set of utils (helper functions) to inspect 2D and 3D data, and analyse the structure tensor output. The 2D and 3D examples come as python scripts (.py) and Jupyter Notebooks (.ipynb), the latter is more complete and pedagogical, as it comes with explanations. With these tutorials we would like you to 1) learn how to choose the parameters to obtain desirable results, 2) see different options for visualising the output of the structure tensor, and 3) get inspiration for scientific questions that you could answer with the structure tensor tool. -- GitLab