Update known issue

Signed-off-by: Wendell Hom <[email protected]>

applications/body_pose_estimation/README.md

@@ -121,3 +121,15 @@ To mount RTI Connext into the container, ensure that the `NDDSHOME` and
 ```sh
 ./dev_container launch --img holohub:bpe --docker_opts "-v $NDDSHOME:/opt/dds -e NDDSHOME=/opt/dds -e CONNEXTDDS_ARCH=$CONNEXTDDS_ARCH"
 ```
+
+### Known Issues
+
+There is a known issue running this application on IGX w/ iGPU and on Jetson AGX (see [#500](https://github.com/nvidia-holoscan/holohub/issues/500)).
+The workaround is to update the device to avoid picking up the libnvv4l2.so library.
+
+```bash
+cd /usr/lib/aarch64-linux-gnu/
+ls -l libv4l2.so.0.0.999999
+sudo rm libv4l2.so.0.0.999999
+sudo ln -s libv4l2.so.0.0.0.0  libv4l2.so.0.0.999999
+```

applications/florence-2-vision/README.md

@@ -50,7 +50,16 @@ Note: The first build will take **~1.5 hours** if you're on ARM64. This is large
 ## 💻 Supported Hardware
 - IGX w/ dGPU
 - x86 w/ dGPU
-> Note: iGPU is not yet supported. This app can be built on iGPU devices and the florence2_app.py will run, however, the full QT UI app is not yet supported for iGPU.
+- IGX w/ iGPU and Jetson AGX supported with workaround<br>
+  There is a known issue running this application on IGX w/ iGPU and on Jetson AGX (see [#500](https://github.com/nvidia-holoscan/holohub/issues/500)).
+  The workaround is to update the device to avoid picking up the libnvv4l2.so library.
+
+  ```bash
+  cd /usr/lib/aarch64-linux-gnu/
+  ls -l libv4l2.so.0.0.999999
+  sudo rm libv4l2.so.0.0.999999
+  sudo ln -s libv4l2.so.0.0.0.0  libv4l2.so.0.0.999999
+  ```
 
 
 ## Dev Container

applications/tao_peoplenet/README.md

@@ -46,3 +46,15 @@ To launch the application using the Video Stream Replayer as the input source, r
 ```sh
 ./dev_container build_and_run tao_peopelnet --run_args "--source replayer"
 ```
+
+### Known Issues
+
+There is a known issue running this application on IGX w/ iGPU and on Jetson AGX (see [#500](https://github.com/nvidia-holoscan/holohub/issues/500)).
+The workaround is to update the device to avoid picking up the libnvv4l2.so library.
+
+```bash
+cd /usr/lib/aarch64-linux-gnu/
+ls -l libv4l2.so.0.0.999999
+sudo rm libv4l2.so.0.0.999999
+sudo ln -s libv4l2.so.0.0.0.0  libv4l2.so.0.0.999999
+```

applications/video_deidentification/README.md

@@ -53,3 +53,15 @@ To launch the application using the Video Stream Replayer as the input source, r
 ```sh
 ./dev_container build_and_run video_deidentification --run_args "--source replayer"
 ```
+
+### Known Issues
+
+There is a known issue running this application on IGX w/ iGPU and on Jetson AGX (see [#500](https://github.com/nvidia-holoscan/holohub/issues/500)).
+The workaround is to update the device to avoid picking up the libnvv4l2.so library.
+
+```bash
+cd /usr/lib/aarch64-linux-gnu/
+ls -l libv4l2.so.0.0.999999
+sudo rm libv4l2.so.0.0.999999
+sudo ln -s libv4l2.so.0.0.0.0  libv4l2.so.0.0.999999
+```

applications/vila_live/README.md

@@ -49,10 +49,19 @@ Once the main LMM-based app is running, you will see a link for the app at `http
 
 ## 💻 Supported Hardware
 - IGX w/ dGPU
-- IGX w/ iGPU
 - x86 w/ dGPU
+- IGX w/ iGPU and Jetson AGX supported with workaround<br>
+  There is a known issue running this application on IGX w/ iGPU and on Jetson AGX (see [#500](https://github.com/nvidia-holoscan/holohub/issues/500)).
+  The workaround is to update the device to avoid picking up the libnvv4l2.so library.
+
+  ```bash
+  cd /usr/lib/aarch64-linux-gnu/
+  ls -l libv4l2.so.0.0.999999
+  sudo rm libv4l2.so.0.0.999999
+  sudo ln -s libv4l2.so.0.0.0.0  libv4l2.so.0.0.999999
+  ```
 
 ## 🙌 Acknowledgements
 - Jetson AI Lab, [Live LLaVA](https://www.jetson-ai-lab.com/tutorial_live-llava.html): for the inspiration to create this app
 - [Jetson-Containers](https://github.com/dusty-nv/jetson-containers/tree/master/packages/llm/llamaspeak) repo: For the Flask web-app with WebSockets
-- [LLM-AWQ](https://github.com/mit-han-lab/llm-awq) repo: For the example code to create AWQ-powered LLM servers
+- [LLM-AWQ](https://github.com/mit-han-lab/llm-awq) repo: For the example code to create AWQ-powered LLM servers