InvokeAI：Stable Diffusion最好的WebUI?

Loading Python libraries...

Welcome to InvokeAI. This script will help download the Stable Diffusion weight files
and other large models that are needed for text to image generation. At any point you may interrupt
this program and resume later.

** INITIALIZING INVOKEAI RUNTIME DIRECTORY **
Select a directory in which to install InvokeAI's models and configuration files [/home/ubuntu/invokeai]: /apps/invokeAI
Select the default directory for image outputs [/apps/invokeAI/outputs]: /apps/invokeAI/outputs

InvokeAI models and configuration files will be placed into "/apps/invokeAI" and image outputs will be placed into "/apps/invokeAI/outputs".
Accept these locations? [y] y

You may change the chosen directories at any time by editing the --root and --outdir options in "/home/ubuntu/.invokeai",
You may also change the runtime directory by setting the environment variable INVOKEAI_ROOT.

The NSFW (not safe for work) checker blurs out images that potentially contain sexual imagery.
It can be selectively enabled at run time with --nsfw_checker, and disabled with --no-nsfw_checker.
The following option will set whether the checker is enabled by default. Like other options, you can
change this setting later by editing the file /home/ubuntu/.invokeai.
Enable the NSFW checker by default? [y] n

The next choice selects the sampler to use by default. Samplers have different speed/performance
tradeoffs. If you are not sure what to select, accept the default.
Default sampler to use? (ddim, k_dpm_2_a, k_dpm_2, k_euler_a, k_euler, k_heun, k_lms, plms) [k_heun]:

The number of denoising steps affects both the speed and quality of the images generated.
Higher steps often (but not always) increases the quality of the image, but increases image
generation time. This can be changed at run time. Accept the default if you are unsure.
Default number of steps to use during generation? [20]:
Creating the initialization file at "/home/ubuntu/.invokeai".

Welcome to InvokeAI. This script will help download the Stable Diffusion weight files
and other large models that are needed for text to image generation. At any point you may interrupt
this program and resume later.

** DOWNLOADING DIFFUSION WEIGHTS **
You can download and configure the weights files manually or let this
script do it for you. Manual installation is described at:

https://github.com/invoke-ai/InvokeAI/blob/main/docs/installation/INSTALLING_MODELS.md

You may download the recommended models (about 10GB total), select a customized set, or
completely skip this step.

Download <r>ecommended models, <a>ll models, <c>ustomized list, or <s>kip this step? [r]: 
** LICENSE AGREEMENT FOR WEIGHT FILES **

To download the Stable Diffusion weight files from the official Hugging Face 
repository, you need to read and accept the CreativeML Responsible AI license.

This involves a few easy steps.

1. If you have not already done so, create an account on Hugging Face's web site
   using the "Sign Up" button:

   https://huggingface.co/join

   You will need to verify your email address as part of the HuggingFace
   registration process.

2. Log into your Hugging Face account:

    https://huggingface.co/login

3. Accept the license terms located here:

   https://huggingface.co/runwayml/stable-diffusion-v1-5

   and here:

   https://huggingface.co/runwayml/stable-diffusion-inpainting

    (Yes, you have to accept two slightly different license agreements)

Press <enter> when you are ready to continue:
(Fetching Hugging Face token from cache...not found

4. Thank you! The last step is to enter your HuggingFace access token so that
   this script is authorized to initiate the download. Go to the access tokens
   page of your Hugging Face account and create a token by clicking the 
   "New token" button:

   https://huggingface.co/settings/tokens

   (You can enter anything you like in the token creation field marked "Name". 
   "Role" should be "read").

   Now copy the token to your clipboard and paste it at the prompt. Windows
   users can paste with right-click.
   Token: 
Password: *************************************

** DOWNLOADING WEIGHTS **
* v1-5-pruned-emaonly.ckpt: Downloading...

ubuntu@VM-0-6-ubuntu:/apps/invokeAI$ ./invoke.sh 
Do you want to generate images using the
1. command-line
2. browser-based UI
3. open the developer console
Please enter 1, 2, or 3: 2

Starting the InvokeAI browser-based UI..
* Initializing, be patient...
>> Initialization file /home/ubuntu/.invokeai found. Loading...
>> InvokeAI runtime directory is "/apps/invokeAI"
>> patchmatch.patch_match: INFO - Compiling and loading c extensions from "/apps/invokeAI/src/pypatchmatch/patchmatch".
>> patchmatch.patch_match: WARNING - patchmatch failed to load or compile.
>> patchmatch.patch_match: WARNING - Refer to https://github.com/invoke-ai/InvokeAI/blob/main/docs/installation/INSTALL_PATCHMATCH.md for installation instructions.
>> Patchmatch not loaded (nonfatal)
>> GFPGAN Initialized
>> CodeFormer Initialized
>> ESRGAN Initialized
>> Using device_type cuda
>> Current VRAM usage:  0.00G
>> Scanning Model: stable-diffusion-1.5
>> Model Scanned. OK!!
>> Loading stable-diffusion-1.5 from /apps/invokeAI/models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt
   | LatentDiffusion: Running in eps-prediction mode
   | DiffusionWrapper has 859.52 M params.
   | Making attention of type 'vanilla' with 512 in_channels
   | Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
   | Making attention of type 'vanilla' with 512 in_channels
   | Using faster float16 precision
   | Loading VAE weights from: /apps/invokeAI/models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
>> Model loaded in 61.56s
>> Max VRAM used to load the model: 2.17G 
>> Current VRAM usage:2.17G
>> Current embedding manager terms: *
>> Setting Sampler to k_heun

* --web was specified, starting web server...
>> Initialization file /home/ubuntu/.invokeai found. Loading...
>> Started Invoke AI Web Server!
>> Default host address now 127.0.0.1 (localhost). Use --host 0.0.0.0 to bind any address.
>> Point your browser at http://127.0.0.1:9090