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How to get Techlatest Stable Diffusion with InvokeAI Web Interface on AWS

This section describes how to launch and connect toTechlatest Stable Diffusion with InvokeAI Web Interface on Amazon Web Services (AWS).

Note: Stable diffusion requires a lot of processing, so a GPU instance is recommended. If you want to use a CPU instance due to the high price of GPU instances, you should use instances with a higher CPU.

GPU’s are not available in some zones and for some instance types.

Below are recommended VM configuration requirements:

  • GPU VM : g4dn.xlarge (4 vcpu 16gb memory) configuration
  • CPU VM : t2.xlarge (4vcpu, 16gb ram)

For CPU, its the minimum spec but more cpu is preferred. Instances with AMD GPU are not recommended.

Note: GPU instance will perform 10 times or more faster when processing request compared to CPU instance . Typical GPU instance will take few seconds to render the images compared to 7-10 minutes by CPU instance, hence GPU instances are preferred.

  1. Open Techlatest Stable Diffusion with InvokeAI Web Interface VM listing on AWS marketplace

/img/aws/invoke-ai/marketplace.png

  1. Click on Continue to subscribe.

Login with your credentials and follow the instruction.

Subscribe to the product and click on Continue to configuration button.

Select a Region where you want to launch the VM(such as US East (N.Virginia))

/img/aws/invoke-ai/region.png Click on Continue to Launch Button

Choose Action: You can launch it through EC2 or from Website.(Let’s choose Launch from website)

/img/aws/stable-diffusion/launch.png

Optionally change the EC2 instance type. (This defaults to t2.xlarge instance type, 4 vCPUs and 16 GB RAM.)

Optionally change the network name and subnetwork names.

/img/aws/stable-diffusion/vpc.png

Select the Security Group. Be sure that whichever Security Group you specify have ports 22 (for SSH), 3389 (for RDP) and 80 (for HTTP) exposed.

Be sure to download the key-pair which is available by default, or you can create the new key-pair and download it. /img/aws/stable-diffusion/SG.png

Click on Launch.
Techlatest Stable Diffusion with InvokeAI Web Interface will begin deploying.

  1. A summary page displays.To see this instance on EC2 Console click on EC2 Console link.

/img/aws/invoke-ai/deployed.png

  1. On the EC2 Console page, instance is up and running. To connect to this instance through putty, copy the IPv4 Public IP Address

/img/aws/invoke-ai/public-ip.png

  1. Open putty, paste the IP address and browse your private key you downloaded while deploying the VM, by going to SSH->Auth, click on Open. Enter ubuntu as userid

/img/aws/desktop-linux/putty-01.png

/img/aws/desktop-linux/putty-02.png

  1. Once connected, change the password for ubuntu user using below command
sudo passwd ubuntu

/img/aws/invoke-ai/ssh-login.png

  1. Now the password for ubuntu user is set, you can connect to the VM’s desktop environment from any local Windows Machine using RDP protocol or Linux Machine using Remmina.

    From your local windows machine, goto “start” menu, in the search box type and select “Remote desktop connection”. In the “Remote Desktop connection” wizard, copy the public IP address and click connect

/img/aws/desktop-linux/rdp.png

  1. This will connect you to the VM’s desktop environment. Provide the username (e.g “ubuntu”) and the password set in the above “Reset password” step to authenticate. Click OK

/img/aws/stable-diffusion/rdp-login.png

  1. Now you are connected to the out of box Techlatest Stable Diffusion with InvokeAI Web Interface environment via Windows Machine.

/img/aws/invoke-ai/rdp-desktop.png

  1. To connect using RDP via Linux machine, first note the external IP of the VM from VM details page,then from your local Linux machine, goto menu, in the search box type and select “Remmina”.

    Note: If you don’t have Remmina installed on your Linux machine, first Install Remmina as per your linux distribution.

/img/gcp/common/remmina-search.png

  1. In the “Remmina Remote Desktop Client” wizard, select the RDP option from dropdown and paste the external ip and click enter.

/img/gcp/common/remmina-external-ip.png

  1. This will connect you to the VM’s desktop environment. Provide “ubuntu” as the userid and the password set in above reset password step to authenticate. Click OK

/img/gcp/common/remmina-rdp-login.png

  1. Now you are connected to out of box Techlatest Stable Diffusion with InvokeAI Web Interface environment via Linux machine.

/img/aws/invoke-ai/rdp-desktop.png

  1. Setting up a huggingface account.

    Create an account on https://huggingface.co/join, complete the registration and verify your email.

    Then goto https://huggingface.co/settings/tokens and click on “Access Tokens” link on left and create a token with “Read” role. Keep the token handy.

/img/gcp/invoke-ai/huggingface-token.png
/img/gcp/invoke-ai/read-role.png

  1. Now open the terminal inside GUI and run below commands
cd /home/ubuntu/invokeai
./invoke.sh

/img/gcp/invoke-ai/execute-invokeai.png

  1. It will prompt you some questions. For the first prompt, select the option 2 as generate images using browser based UI.

/img/gcp/invoke-ai/select-browser-based-ui.png

  1. Next it will ask you to download models, select “r” to download recommended model. You can choose any option other than skip, it is recommended to select “r”. If you select all, make sure you have enough disk space to download all models.

/img/gcp/invoke-ai/download-model.png

  1. After providing all the above option, it will ask for inputting the token at the command prompt, paste the token created in hugging face in step 8 above and click enter.
    Wait till the setup finishes. Once setup is complete, restart the VM.

/img/gcp/invoke-ai/press-enter.png

/img/gcp/invoke-ai/enter-token.png

  1. After VM launch for the first time, GPU instances will take 2-5 minutes and CPU instances will take 5-10 minutes to launch the app in the browser.

    Wait for 2-5 or 5-10 minutes depending on if your VM is GPU or CPU based and then access the InvokeAI GUI via browser by copying the public IP of the VM from the VM’s overview page and paste it in the browser and then hit enter.

    Note: Please use http and not https in the URL when accessing InvokeAI interface in GUI, for eg. http://vm_public_ip.

  2. The Stable Diffusion InvokeAI GUI comes with lots of options and settings. The first window shows text to image page.There are three main sections.

  3. A control panel on the left, which contains various settings for text to image generation.

  4. The current image section in the middle, which shows a large format version of the image you are currently working on. 3. A gallery section on the right that contains a history of the images you have generated.

/img/gcp/invoke-ai/invokeai-web-ui.png

  1. Provide the Prompt and click on Invoke button and wait till it finishes.

/img/gcp/invoke-ai/text-to-image.png

  1. You can see and edit all the images in viewer window. Click on viewer icon as shown below to load the images.

/img/gcp/invoke-ai/viewer.png

/img/gcp/invoke-ai/viewer-window.png

  1. You can also access the web console by clicking web console arrow in the left-bottom

/img/gcp/invoke-ai/open-console.png

/img/gcp/invoke-ai/console.png

  1. For more information on how to use the GUI, Go to InvokeAI Web UI
  2. You can access InvokeAI directory at /home/ubuntu/invokeai.
    The images created from GUI are stored under /home/ubuntu/invokeai/output directory.
    To access this directory, connect to VM’s Desktop environment as explained above, and navigate to home - > ubuntu -> invokeai-> output directory.

/img/gcp/invoke-ai/invokeai-directory.png

/img/gcp/invoke-ai/output-directory.png

  1. You can also access the sourcecode of the InvokeAI. It is available under sourcecode folder on Desktop.

/img/gcp/stable-diffusion/source-code-folder-on-desktop.png

/img/aws/invoke-ai/sourcecode-directory.png

Credits:

https://github.com/CompVis/stable-diffusion.git
https://github.com/AbdBarho/stable-diffusion-webui-docker
https://github.com/AUTOMATIC1111/stable-diffusion-webui
https://github.com/Sygil-Dev/sygil-webui
https://github.com/invoke-ai/InvokeAI
https://invoke-ai.github.io/InvokeAI/other/CONTRIBUTORS/

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