…odels
- If CLI asked to convert the currently loaded model, the model would
crash on the first rendering. CLI will now refuse to convert a model
loaded in memory (probably a good idea in any case).
- CLI will offer the `v1-inpainting-inference.yaml` as the configuration
file when importing an inpainting a .ckpt or .safetensors file that has
"inpainting" in the name. Otherwise it offers `v1-inference.yaml` as the
default.
rather than bypassing any path with diffusers in it, im specifically bypassing model.safetensors and diffusion_pytorch_model.safetensors both of which should be diffusers files in most cases.
- If CLI asked to convert the currently loaded model, the model would crash
on the first rendering. CLI will now refuse to convert a model loaded
in memory (probably a good idea in any case).
- CLI will offer the `v1-inpainting-inference.yaml` as the configuration
file when importing an inpainting a .ckpt or .safetensors file that
has "inpainting" in the name. Otherwise it offers `v1-inference.yaml`
as the default.
Found a couple of places where the formatting was messed up. I also
added a "Quick Start Guide" to the README for people who encounter
InvokeAI through PyPi. It features the PyPi install!
pulling in denoising support from upstream (its already there, invoke
just isn't using it). I've enabled this as a command line argument as
construction of the ESRGAN handler happens once. Ideally this would be a
UI option that could be adjusted for each upscaling task. Unfortunately
that is beyond my current level of InvokeAI-foo.
Upstream reference is here, starting on line 99 "use dni to control the
denoise strength"
https://github.com/xinntao/Real-ESRGAN/blob/master/inference_realesrgan.py
