From 2ef580100c8de1bf8acea854607ac1e552e9703f Mon Sep 17 00:00:00 2001 From: Nikhil Raj Date: Wed, 16 Jun 2021 11:06:52 +0100 Subject: Fix broken link to Ndk guide in armnn Readme.md Signed-off-by: Nikhil Raj Change-Id: I1e96c0b15721e522346e2b66f4e3d388225cebde --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 702a011065..0ab6863d6a 100644 --- a/README.md +++ b/README.md @@ -53,7 +53,7 @@ TfLite will then delegate operations, that can be accelerated with Arm NN, to Ar executed with the usual TfLite runtime. This is our **recommended way to accelerate TfLite models**. As with our parsers there are tutorials in our doxygen documentation that can be found in the [wiki section](https://github.com/ARM-software/armnn/wiki/Documentation). -If you would like to use **Arm NN on Android** you can follow this guide which explains [how to build Arm NN using the AndroidNDK](). +If you would like to use **Arm NN on Android** you can follow this guide which explains [how to build Arm NN using the AndroidNDK](BuildGuideAndroidNDK.md). But you might also want to take a look at another repository which implements a hardware abstraction layer (HAL) for Android. The repository is called [Android-NN-Driver](https://github.com/ARM-software/android-nn-driver) and when integrated into Android it will automatically run neural networks with Arm NN. -- cgit v1.2.1