- ARM64 based EC2
- Windows + WSL2 + Ubuntu
Note: MacOS is currently not supported due to model compilation issues.
Pre-Requisites
-
You need to have an already created PEM key in your aws account and downloaded it to your local computer. Instructions on how to create a PEM key
-
An S3 bucket created in the region of your choice that you can use in the Test Utility
Launching the Samples
-
Click the Launch Stack Button below. NOTE : This process will take about
20 minutes
-
Log into the EC2 Instance (See next section) and wait for the file
INSTALLATION-COMPLETE.txt
to appear on your/home/ubuntu
. This marks the end of the EC2 instance set upOPTIONAL STEP : If you would like to monitor the set up progress, log into the EC2 instance (See Next Section), and type
tail -f /var/log/cloud-init-output.log
in a terminal session.
Logging into the EC2 Instance
-
From the AWS EC2 Console, get the Public IPv4 DNS for the instance you launched. It should look something like this
ec2-1-234-567-8.compute-1.amazonaws.com
-
Make sure the PEM key that was created is in the same folder as you are. At this point, you can do this
ssh -i "My_Awesome_Key.pem" ubuntu@ec2-1-234-567-8.compute-1.amazonaws.com
-
Launch Jupyter Lab Session from the Ec2 console
sudo jupyter-lab --no-browser --allow-root
You Should see something like this
http://ip-123-45-678-910:8888/lab?token=e718819a3eb9b464aa81e14fe73439b49337e5d9fdef2676
Note the Port (8888) and the token number
-
Creating a SSH tunnel (May not be necessary).Open an another terminal session on your Computer. Make sure the port number here is the same as the output from
Step 3
ssh -i My_Awesome_Key.pem -NL 8157:localhost:8888 ubuntu@ec2-1-234-567-8.compute-1.amazonaws.com
-
Launch your browser, paste the following address in your browser window
http://localhost:8157/
At this point it should ask for the token number, paste it and click Ok. You are inside your EC2 instance Jupyter Lab session
-
Once logged into Jupyter Lab session, open a terminal session and run
aws configure
. Fill in the Access Key and Secret key and Region for your account.aws configure
-
Install WSL2, Ubuntu and Docker Desktop on your Windows PC, and configure Ubuntu. Please refer to Setting up a development environment in Windows
-
Install DLR in Ubuntu by building from source code. Please refer to Building on Linux - Building for CPU
-
Install additional dependencies
sudo pip3 install boto3 sagemaker matplotlib opencv-python --upgrade
-
Install Jupyter or JupyterLab in Ubuntu
sudo pip3 install jupyterlab
-
Clone the 'aws-panorama-samples' repository in the Ubuntu filesystem.
git clone https://github.com/aws-samples/aws-panorama-samples.git
-
Run jupyter server on Ubuntu
jupyter-lab --no-browser --allow-root --port 8888 --notebook-dir ~
You will see console output like below:
Jupyter Server 1.13.0 is running at: http://localhost:8888/lab?token={token}
Copy the token to clipboard.
-
Open your browser on Windows, and browse http://localhost:8888/.
You will be asked to input the token. Please use the token you copied at previous step.