This was a difficult merge because both PR #1108 and #1243 made
changes to obscure parts of the diffusion code.
- prompt weighting, merging and cross-attention working
- cross-attention does not work with runwayML inpainting
model, but weighting and merging are tested and working
- CLI command parsing code rewritten in order to get embedded
quotes right
- --hires now works with runwayML inpainting
- --embiggen does not work with runwayML and will give an error
- Added an --invert option to invert masks applied to inpainting
- Updated documentation
Now you can activate the Hugging Face `diffusers` library safety check
for NSFW and other potentially disturbing imagery.
To turn on the safety check, pass --safety_checker at the command
line. For developers, the flag is `safety_checker=True` passed to
ldm.generate.Generate(). Once the safety checker is turned on, it
cannot be turned off unless you reinitialize a new Generate object.
When the safety checker is active, suspect images will be blurred and
a warning icon is added. There is also a warning message printed in
the CLI, but it can be a little hard to see because of its positioning
in the output stream.
There is a slight but noticeable delay when the safety checker runs.
Note that invisible watermarking is *not* currently implemented. The
watermark code distributed by the CompViz distribution uses a library
that does not seem to be able to retrieve the watermarks it creates,
and it does not appear that Hugging Face `diffusers` or other SD
distributions are doing any watermarking.
Ironically, the black and white mask file generated by the
`invoke> !mask` command could not be passed as the mask to
`img2img`. This is now fixed and the documentation updated.
- The !mask command takes an image path, a text prompt, and
(optionally) a masking threshold. It creates a mask over the region
indicated by the prompt, and outputs several files that show which
regions will be masked by the chosen prompt and threshold.
- The mask images should not be passed directly to img2img because
they are designed for visualization only. Instead, use the
--text_mask option to pass the selected prompt and threshold.
- See docs/features/INPAINTING.md for details.
On the command line, the new option is --text_mask or -tm.
Example:
```
invoke> a baseball -I /path/to/still_life.png -tm orange
```
This will find the orange fruit in the still life painting and replace
it with an image of a baseball.
- In CLI: the argument is --png_compression <0..9> (-z<0..9>)
- In API, pass `compress_level` to PngWriter.save_image_and_prompt_to_png()
Compression ranges from 0 (no compression) to 9 (maximum compression).
Default value is 6 (as specified by Pillow package).
This addresses an issue first raised in #652.
* “Formally” means that there is a formality such as a rule or declaration, “formerly” refers to a prior state. The latter is almost certainly what is meant here.
<div> around the inline images works great in gh-pages, but breaks plain old markdown in GitHub code display. This removes the <div>s, causing slight degradation in quality of gh-page appearance.
- --inpaint_replace 0.X will cause inpainting to ignore what is under
the masked region with a strength ranging from 0 (don't ignore at all)
to 1.0 (ignore completely)
- sync with upstream development
- update docs
- add a `--inpaint_replace` option that fills masked regions with
latent noise. This allows radical changes to inpainted regions
at the cost of losing context.
- fix up readline, arg processing and metadata writing to accommodate
this change
- fixed bug in storage and retrieval of variations, discovered incidentally
during testing
- update documentation
- !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>
- better readability in dark mode since color change
- better looking changelog
- fix images which where not loading
- also center most of the images
- fix some syntax errors like
- headlines ending with a colon
- codeblocks with wrong fences
- codeblocks without shell
- update conda prompts from ldm to invokeai
- ....
- rename dream.py to invoke.py
- create a compatibility script named dream.py that execs() invoke.py
- redo documentation
- change help message in args
- this does **not** rename the libraries, which are still ldm.dream.util, etc
