Frequently Asked Questions
One possible reason is, that your device and one of the docker instances/containers have the same local ip address.
To resolve this, start by checking the instances' IP addresses:
If one of the IP addresses shown matches your Solution Kit's external IP address, you can run into connection problems. However, it is always a good idea to configure the docker daemon to use an internal IP address pool, which doesn't match your company's subnets. See this docker community forum entry for more details.
NVidia recommends to use a fan when the board is operated under unfavorable conditions (no ventilation, hot environment) under high load.
To check if you need a fan, run the tegrastats command on the nano.
If the listed temperatures reach the limits specified in the official hardware documentation , you can attach a 5V fan to the fan header for improved performance.
This one is recommended by NVidia.
This is a temporary workaround and will be fixed in a future release!
In some cases the image processing container crashes after running for a long period of time.
List the running docker containers by running
from the Jetson's terminal.
Check if the image-processing container is running. If it is not present, you have two options to workaround that problem.
That is not a big deal. You have two options here.
If you need further details on how to flash the Solution Kit, please refer to NVIDIA's manuals on Writing Image to the microSD Card.
Local usage - i.e. directly connecting via HDMI/keyboard/mouse - decreases the amount of computing power and memory available to your application, significantly. So we highly recommend to use it as a remote kit. That implies connecting to the Kit via SSH (for console access) and our provided Web GUI.
Generally, the docker containers will be updated automatically when starting the system. However, this only works with the following prerequisites:
dateon the board.
If the system time cannot be set automatically due to network restrictions, please consider the following options:
sudo date --set, for example:
sudo date --set="23 Dec 2020 10:12:34". after setting the correct time, please execute
ai-vision-solution kit restartto update to the latest released versions of the docker images.
The Office Object Detection contains the following types of objects:
If you plan to extend the model or to change the types of detected objects by retraining it, please refer to our corresponding documentation on How to create, train and deploy a Machine Learning Model or have a look at the sample code.