Adding support for the KR260 (#25)

README.md

@@ -1,19 +1,28 @@
 ![](./kriapynq.png)
 
-This repository contains the install scripts needed to add PYNQ to your Kria KV260 Vision AI Starter Kit's official Ubuntu SDCard Image.  From that installation, a complete Python and Jupyter environment is installed on the Kria SOM along with multiple programmable logic overlays all ready to use.  
+This repository contains the install scripts needed to add PYNQ to the official Ubuntu SDCard Image of your:
+* Kria KV260 Vision AI Starter Kit  
+* Kria KR260 Robotic Starter Kit
+
+From that installation, a complete Python and Jupyter environment is installed on the Kria SOM along with multiple programmable logic overlays all ready to use.  
 
 ## Installation
 
 #### 1. Get the Ubuntu SD Card Image 
-Follow the steps to [Get Started with Kria KV260 Vision AI Starter Kit](https://www.xilinx.com/products/som/kria/kv260-vision-starter-kit/kv260-getting-started-ubuntu/setting-up-the-sd-card-image.html) until you complete the [Booting your Starter Kit](https://www.xilinx.com/products/som/kria/kv260-vision-starter-kit/kv260-getting-started-ubuntu/booting-your-starter-kit.html) section
+
+#### KV260
+Follow the steps to [Get Started with Kria KV260 Vision AI Starter Kit](https://www.xilinx.com/products/som/kria/kv260-vision-starter-kit/kv260-getting-started-ubuntu/setting-up-the-sd-card-image.html) until you complete the [Booting your Starter Kit](https://www.xilinx.com/products/som/kria/kv260-vision-starter-kit/kv260-getting-started-ubuntu/booting-your-starter-kit.html) section.
+
+#### KR260
+Follow the steps to [Get Started with Kria KR260 Robotic Starter Kit](https://www.xilinx.com/products/som/kria/kr260-robotics-starter-kit/kr260-getting-started/setting-up-the-sd-card-image.html) until you complete the [Booting your Starter Kit](https://www.xilinx.com/products/som/kria/kr260-robotics-starter-kit/kr260-getting-started/booting-your-starter-kit.html) section.
 
 #### 2. Install PYNQ
-Then install PYNQ on your Kria KV260 Vision AI Starter Kit.  Simply clone this repository from the KV260 and run the install.sh script.
+Then install PYNQ on your Kria device.  Simply clone this repository from your Kria and run the install.sh script specifying the device with the `-b` flag.
 
 ```bash
 git clone https://github.com/Xilinx/Kria-PYNQ.git
 cd Kria-PYNQ/
-sudo bash install.sh
+sudo bash install.sh -b { KV260 | KR260 } 
 ```
 
 This script will install the required debian packages, create Python virtual environment and configure a Jupyter portal.  This process takes around 25 minutes.
@@ -24,23 +33,39 @@ JupyterLab can now be accessed via a web browser `<ip_address>:9090/lab` or `kri
 
 ## Included Overlays
 
-#### Base Overlay [\[GitHub\]](kv260/base)
+#### Base Overlay [\[GitHub\]](kv260/base) 
 
 This overlay includes support for the KV260's Raspberry Pi camera and PMOD interfaces.  A [Digilent Pcam 5C](https://digilent.com/reference/add-ons/pcam-5c/start?redirect=1) camera can be attached to the KV260 and controlled from Jupyter notebooks.  Additionally, a variety of Grove and PMOD devices are supported on the PMOD interface - all controllable from a Xilinx Microblaze processor in programmable logic.  
 
-#### DPU-PYNQ [\[GitHub\]](https://github.com/Xilinx/DPU-PYNQ) [\[PYPI\]](https://pypi.org/project/pynq-dpu/)
-This overlay contains a Vitis-AI 1.4.0 Deep Learning Processor Unit (DPU) and comes with a variety of notebook examples with pre-trained ML models.
+__Supported boards__: _KV260_ 
 
-#### Composable Pipeline [\[GitHub\]](https://github.com/Xilinx/PYNQ_Composable_Pipeline) 
+#### DPU-PYNQ (v2.5) [\[GitHub\]](https://github.com/Xilinx/DPU-PYNQ) [\[PYPI\]](https://pypi.org/project/pynq-dpu/)
+This overlay contains a Vitis-AI 2.5.0 Deep Learning Processor Unit (DPU) and comes with a variety of notebook examples with pre-trained ML models.
+
+__Supported boards__: _KV260_, _KR260_ 
+
+#### Composable Pipeline (v1.1 soft-release) [\[GitHub\]](https://github.com/Xilinx/PYNQ_Composable_Pipeline) 
 The Composable pipeline is an overlay with a novel and clever architecture that allow us to adapt how the data flows between a series of IP cores.
 
+__Supported boards__: _KV260_ 
+
 #### PYNQ-Helloworld [\[GitHub\]](https://github.com/Xilinx/PYNQ-HelloWorld) [\[PYPI\]](https://pypi.org/project/pynq-helloworld/)
 One of PYNQ's first overlays, the PYNQ-Helloworld overlay includes an image resizer block in programmable logic.  This overlay demonstrates a simple but powerful use of programmable logic HLS blocks to do image processing. 
 
+__Supported boards__: _KV260_, _KR260_ 
+
+## Selftest
+
+A self-test script for each board is generated at the end of the build. This test script runs some of the Overlay tests. To run the self-test navigate to the ``Kria-PYNQ`` install directory and run:
+```bash
+sudo ./selftest.sh
+```
+
 ## References
 
 - [PYNQ](https://www.pynq.io)
 - [KV260 Vision AI Starter Kit](https://www.xilinx.com/products/som/kria/kv260-vision-starter-kit)
+- [KR260 Robotic Starter Kit](https://www.xilinx.com/products/som/kria/kr260-robotics-starter-kit.html)
 - [Canonical Xilinx Ubuntu Images](https://ubuntu.com/download/xilinx)
 
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