There are only a couple SDXL inpainting models, and my tests indicate they are not as good as SD1.5 inpainting, but at least we support them now.
- Add the config file. This matches what is used in A1111. The only difference from the non-inpainting SDXL config is the number of in-channels.
- Update the legacy config maps to use this config file.
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.
This is the first phase of a big shifting of files and directories
in the source tree.
You will need to run `pip install -e .` before the code will work again!
Here's what's in the current commit:
1) Remove a lot of dead code that dealt with checkpoint and safetensor loading.
2) Entire ckpt_generator hierarchy is now gone!
3) ldm.invoke.generator.* => invokeai.generator.*
4) ldm.model.* => invokeai.model.*
5) ldm.invoke.model_manager => invokeai.model.model_manager
6) In addition, a number of frequently-accessed classes can be imported
from the invokeai.model and invokeai.generator modules:
from invokeai.generator import ( Generator, PipelineIntermediateState,
StableDiffusionGeneratorPipeline, infill_methods)
from invokeai.models import ( ModelManager, SDLegacyType
InvokeAIDiffuserComponent, AttentionMapSaver,
DDIMSampler, KSampler, PLMSSampler,
PostprocessingSettings )
1) Downgrade numpy to avoid dependency conflict with numba
2) Move all non ldm/invoke files into `invokeai`. This includes assets, backend, frontend, and configs.
3) Fix up way that the backend finds the frontend and the generator finds the NSFW caution.png icon.
