add ability to import and edit alternative models online

- !import_model <path/to/model/weights> will import a new model,
  prompt the user for its name and description, write it to the
  models.yaml file, and load it.

- !edit_model <model_name> will bring up a previously-defined model
  and prompt the user to edit its descriptive fields.

Example of !import_model

<pre>
invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b>
>> Model import in process. Please enter the values needed to configure this model:

Name for this model: <b>waifu-diffusion</b>
Description of this model: <b>Waifu Diffusion v1.3</b>
Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b>
Default image width: <b>512</b>
Default image height: <b>512</b>
>> New configuration:
waifu-diffusion:
  config: configs/stable-diffusion/v1-inference.yaml
  description: Waifu Diffusion v1.3
  height: 512
  weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt
  width: 512
OK to import [n]? <b>y</b>
>> Caching model stable-diffusion-1.4 in system RAM
>> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.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
</pre>

Example of !edit_model

<pre>
invoke> <b>!edit_model waifu-diffusion</b>
>> Editing model waifu-diffusion from configuration file ./configs/models.yaml
description: <b>Waifu diffusion v1.4beta</b>
weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b>
config: configs/stable-diffusion/v1-inference.yaml
width: 512
height: 512

>> New configuration:
waifu-diffusion:
  config: configs/stable-diffusion/v1-inference.yaml
  description: Waifu diffusion v1.4beta
  weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt
  height: 512
  width: 512

OK to import [n]? y
>> Caching model stable-diffusion-1.4 in system RAM
>> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt
...
</pre>
This commit is contained in:
Lincoln Stein
2022-10-13 23:48:07 -04:00
parent 916f5bfbb2
commit 6afc0f9b38
7 changed files with 380 additions and 75 deletions

View File

@ -157,7 +157,8 @@ Here are the invoke> command that apply to txt2img:
| --gfpgan_strength <float> | -G <float> | -G0 | Fix faces using the GFPGAN algorithm; argument indicates how hard the algorithm should try (0.0-1.0) |
| --save_original | -save_orig| False | When upscaling or fixing faces, this will cause the original image to be saved rather than replaced. |
| --variation <float> |-v<float>| 0.0 | Add a bit of noise (0.0=none, 1.0=high) to the image in order to generate a series of variations. Usually used in combination with -S<seed> and -n<int> to generate a series a riffs on a starting image. See [Variations](./VARIATIONS.md). |
| --with_variations <pattern> | -V<pattern>| None | Combine two or more variations. See [Variations](./VARIATIONS.md) for now to use this. |
| --with_variations <pattern> | | None | Combine two or more variations. See [Variations](./VARIATIONS.md) for now to use this. |
| --save_intermediates <n> | | None | Save the image from every nth step into an "intermediates" folder inside the output directory |
Note that the width and height of the image must be multiples of
64. You can provide different values, but they will be rounded down to
@ -206,10 +207,10 @@ well as the --mask (-M) argument:
| --init_mask <path> | -M<path> | None |Path to an image the same size as the initial_image, with areas for inpainting made transparent.|
# Convenience commands
# Postprocessing
In addition to the standard image generation arguments, there are a
series of convenience commands that begin with !:
To postprocess a file using face restoration or upscaling, use the
`!fix` command.
## !fix
@ -243,21 +244,156 @@ Outputs:
[2] outputs/img-samples/000018.2273800735.embiggen-00.png: !fix "outputs/img-samples/000017.243781548.gfpgan-00.png" -s 50 -S 2273800735 -W 512 -H 512 -C 7.5 -A k_lms --embiggen 3.0 0.75 0.25
~~~
## !fetch
# Model selection and importation
This command retrieves the generation parameters from a previously
generated image and either loads them into the command line. You may
provide either the name of a file in the current output directory, or
a full file path.
The CLI allows you to add new models on the fly, as well as to switch
among them rapidly without leaving the script.
~~~
invoke> !fetch 0000015.8929913.png
# the script returns the next line, ready for editing and running:
invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
~~~
## !models
Note that this command may behave unexpectedly if given a PNG file that
was not generated by InvokeAI.
This prints out a list of the models defined in `config/models.yaml'.
The active model is bold-faced
Example:
<pre>
laion400m not loaded <no description>
<b>stable-diffusion-1.4 active Stable Diffusion v1.4</b>
waifu-diffusion not loaded Waifu Diffusion v1.3
</pre>
## !switch <model>
This quickly switches from one model to another without leaving the
CLI script. `invoke.py` uses a memory caching system; once a model
has been loaded, switching back and forth is quick. The following
example shows this in action. Note how the second column of the
`!models` table changes to `cached` after a model is first loaded,
and that the long initialization step is not needed when loading
a cached model.
<pre>
invoke> !models
laion400m not loaded <no description>
<b>stable-diffusion-1.4 cached Stable Diffusion v1.4</b>
waifu-diffusion active Waifu Diffusion v1.3
invoke> !switch waifu-diffusion
>> Caching model stable-diffusion-1.4 in system RAM
>> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.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
>> Model loaded in 18.24s
>> Max VRAM used to load the model: 2.17G
>> Current VRAM usage:2.17G
>> Setting Sampler to k_lms
invoke> !models
laion400m not loaded <no description>
stable-diffusion-1.4 cached Stable Diffusion v1.4
<b>waifu-diffusion active Waifu Diffusion v1.3</b>
invoke> !switch stable-diffusion-1.4
>> Caching model waifu-diffusion in system RAM
>> Retrieving model stable-diffusion-1.4 from system RAM cache
>> Setting Sampler to k_lms
invoke> !models
laion400m not loaded <no description>
<b>stable-diffusion-1.4 active Stable Diffusion v1.4</b>
waifu-diffusion cached Waifu Diffusion v1.3
</pre>
## !import_model <path/to/model/weights>
This command imports a new model weights file into InvokeAI, makes it
available for image generation within the script, and writes out the
configuration for the model into `config/models.yaml` for use in
subsequent sessions.
Provide `!import_model` with the path to a weights file ending in
`.ckpt`. If you type a partial path and press tab, the CLI will
autocomplete. Although it will also autocomplete to `.vae` files,
these are not currenty supported (but will be soon).
When you hit return, the CLI will prompt you to fill in additional
information about the model, including the short name you wish to use
for it with the `!switch` command, a brief description of the model,
the default image width and height to use with this model, and the
model's configuration file. The latter three fields are automatically
filled with reasonable defaults. In the example below, the bold-faced
text shows what the user typed in with the exception of the width,
height and configuration file paths, which were filled in
automatically.
Example:
<pre>
invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b>
>> Model import in process. Please enter the values needed to configure this model:
Name for this model: <b>waifu-diffusion</b>
Description of this model: <b>Waifu Diffusion v1.3</b>
Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b>
Default image width: <b>512</b>
Default image height: <b>512</b>
>> New configuration:
waifu-diffusion:
config: configs/stable-diffusion/v1-inference.yaml
description: Really horrible Hentai pictures
height: 512
weights: models/ldm/stable-diffusion-v1/RD1412.ckpt
width: 512
OK to import [n]? <b>y</b>
>> Caching model stable-diffusion-1.4 in system RAM
>> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.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
invoke>
</pre>
##!edit_model <name_of_model>
The `!edit_model` command can be used to modify a model that is
already defined in `config/models.yaml`. Call it with the short
name of the model you wish to modify, and it will allow you to
modify the model's `description`, `weights` and other fields.
Example:
<pre>
invoke> <b>!edit_model waifu-diffusion</b>
>> Editing model waifu-diffusion from configuration file ./configs/models.yaml
description: <b>Waifu diffusion v1.4beta</b>
weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b>
config: configs/stable-diffusion/v1-inference.yaml
width: 512
height: 512
>> New configuration:
waifu-diffusion:
config: configs/stable-diffusion/v1-inference.yaml
description: Waifu diffusion v1.4beta
weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt
height: 512
width: 512
OK to import [n]? y
>> Caching model stable-diffusion-1.4 in system RAM
>> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt
...
</pre>
# History processing
The CLI provides a series of convenient commands for reviewing previous
actions, retrieving them, modifying them, and re-running them.
## !history
@ -284,6 +420,22 @@ invoke> !20
invoke> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
~~~
## !fetch
This command retrieves the generation parameters from a previously
generated image and either loads them into the command line. You may
provide either the name of a file in the current output directory, or
a full file path.
~~~
invoke> !fetch 0000015.8929913.png
# the script returns the next line, ready for editing and running:
invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
~~~
Note that this command may behave unexpectedly if given a PNG file that
was not generated by InvokeAI.
## !search <search string>
This is similar to !history but it only returns lines that contain