* Fix img2img and inpainting code so a strength of 1 behaves the same as txt2img.
* Make generated images identical to their txt2img counterparts when strength is 1.
Updates the CLI to define CLI commands as Pydantic objects, similar to
how Invocations (nodes) work. For example:
```py
class HelpCommand(BaseCommand):
"""Shows help"""
type: Literal['help'] = 'help'
def run(self, context: CliContext) -> None:
context.parser.print_help()
```
*looks like this #2814 was reverted accidentally. instead of trying to
revert the revert, this PR can simply be re-accepted and will fix the
ui.*
- Migrate UI from SCSS to Chakra's CSS-in-JS system
- better dx
- more capable theming
- full RTL language support (we now have Arabic and Hebrew)
- general cleanup of the whole UI's styling
- Tidy npm packages and update scripts, necessitates update to github
actions
To test this PR in dev mode, you will need to do a `yarn install` as a
lot has changed.
thanks to @blessedcoolant for helping out on this, it was a big effort.
There are actually two Stable Diffusion v2 legacy checkpoint
configurations:
1. "epsilon" prediction type for Stable Diffusion v2 Base
2. "v-prediction" type for Stable Diffusion v2-768
This commit adds the configuration file needed for epsilon prediction
type models as well as the UI that prompts the user to select the
appropriate configuration file when the code can't do so automatically.
To avoid `git blame` recording all the autoformatting changes under the
name 'lstein', this PR adds a `.git-blame-ignore-revs` that will ignore
any provenance changes that occurred during the recent refactor merge.
This fixes the crash that was occurring when trying to load a legacy
checkpoint file.
Note that this PR includes commits from #2867 to avoid diffusers files
from re-downloading at startup time.
There are actually two Stable Diffusion v2 legacy checkpoint
configurations:
1) "epsilon" prediction type for Stable Diffusion v2 Base
2) "v-prediction" type for Stable Diffusion v2-768
This commit adds the configuration file needed for epsilon prediction
type models as well as the UI that prompts the user to select the
appropriate configuration file when the code can't do so
automatically.
