Docs - link to documentation (#1440)

Co-authored-by: Kiriti Gowda <[email protected]>

README.md

@@ -3,6 +3,9 @@
 
 <p align="center"><img width="70%" src="https://raw.githubusercontent.com/ROCm/MIVisionX/master/docs/data/MIVisionX.png" /></p>
 
+> [!NOTE]
+> The published documentation is available at [MIVisionX](https://rocm.docs.amd.com/projects/MIVisionX/en/latest/index.html) in an organized, easy-to-read format, with search and a table of contents. The documentation source files reside in the `docs` folder of this repository. As with all ROCm projects, the documentation is open source. For more information on contributing to the documentation, see [Contribute to ROCm documentation](https://rocm.docs.amd.com/en/latest/contribute/contributing.html).
+
 MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized conformant open-source implementation of the <a href="https://www.khronos.org/openvx/" target="_blank">Khronos OpenVX&trade;</a> and OpenVX&trade; Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting <a href="https://onnx.ai/" target="_blank">ONNX</a>, and <a href="https://www.khronos.org/nnef" target="_blank">Khronos NNEF&trade;</a> exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning inference workloads on a wide range of computer hardware, including small embedded x86 CPUs, APUs, discrete GPUs, and heterogeneous servers.
 
 #### Latest release