fix(ui): remove old scrollbar css
fix(ui): make guidepopover lazy
feat(ui): wip resizable drawer
feat(ui): wip resizable drawer
feat(ui): add scroll-linked shadow
feat(ui): organize files
Align Scrollbar next to content
Move resizable drawer underneath the progress bar
Add InvokeLogo to unpinned & align
Adds Invoke Logo to Unpinned Parameters panel and aligns to make it feel seamless.
# Remove node dependencies on generate.py
This is a draft PR in which I am replacing `generate.py` with a cleaner,
more structured interface to the underlying image generation routines.
The basic code pattern to generate an image using the new API is this:
```
from invokeai.backend import ModelManager, Txt2Img, Img2Img
manager = ModelManager('/data/lstein/invokeai-main/configs/models.yaml')
model = manager.get_model('stable-diffusion-1.5')
txt2img = Txt2Img(model)
outputs = txt2img.generate(prompt='banana sushi', steps=12, scheduler='k_euler_a', iterations=5)
# generate() returns an iterator
for next_output in outputs:
print(next_output.image, next_output.seed)
outputs = Img2Img(model).generate(prompt='strawberry` sushi', init_img='./banana_sushi.png')
output = next(outputs)
output.image.save('strawberries.png')
```
### model management
The `ModelManager` handles model selection and initialization. Its
`get_model()` method will return a `dict` with the following keys:
`model`, `model_name`,`hash`, `width`, and `height`, where `model` is
the actual StableDiffusionGeneratorPIpeline. If `get_model()` is called
without a model name, it will return whatever is defined as the default
in `models.yaml`, or the first entry if no default is designated.
### InvokeAIGenerator
The abstract base class `InvokeAIGenerator` is subclassed into into
`Txt2Img`, `Img2Img`, `Inpaint` and `Embiggen`. The constructor for
these classes takes the model dict returned by
`model_manager.get_model()` and optionally an
`InvokeAIGeneratorBasicParams` object, which encapsulates all the
parameters in common among `Txt2Img`, `Img2Img` etc. If you don't
provide the basic params, a reasonable set of defaults will be chosen.
Any of these parameters can be overridden at `generate()` time.
These classes are defined in `invokeai.backend.generator`, but they are
also exported by `invokeai.backend` as shown in the example below.
```
from invokeai.backend import InvokeAIGeneratorBasicParams, Img2Img
params = InvokeAIGeneratorBasicParams(
perlin = 0.15
steps = 30
scheduler = 'k_lms'
)
img2img = Img2Img(model, params)
outputs = img2img.generate(scheduler='k_heun')
```
Note that we were able to override the basic params in the call to
`generate()`
The `generate()` method will returns an iterator over a series of
`InvokeAIGeneratorOutput` objects. These objects contain the PIL image,
the seed, the model name and hash, and attributes for all the parameters
used to generate the object (you can also get these as a dict). The
`iterations` argument controls how many objects will be returned,
defaulting to 1. Pass `None` to get an infinite iterator.
Given the proposed use of `compel` to generate a templated series of
prompts, I thought the API would benefit from a style that lets you loop
over the output results indefinitely. I did consider returning a single
`InvokeAIGeneratorOutput` object in the event that `iterations=1`, but I
think it's dangerous for a method to return different types of result
under different circumstances.
Changing the model is as easy as this:
```
model = manager.get_model('inkspot-2.0`)
txt2img = Txt2Img(model)
```
### Node and legacy support
With respect to `Nodes`, I have written `model_manager_initializer` and
`restoration_services` modules that return `model_manager` and
`restoration` services respectively. The latter is used by the face
reconstruction and upscaling nodes. There is no longer any reference to
`Generate` in the `app` tree.
I have confirmed that `txt2img` and `img2img` work in the nodes client.
I have not tested `embiggen` or `inpaint` yet. pytests are passing, with
some warnings that I don't think are related to what I did.
The legacy WebUI and CLI are still working off `Generate` (which has not
yet been removed from the source tree) and fully functional.
I've finished all the tasks on my TODO list:
- [x] Update the pytests, which are failing due to dangling references
to `generate`
- [x] Rewrite the `reconstruct.py` and `upscale.py` nodes to call
directly into the postprocessing modules rather than going through
`Generate`
- [x] Update the pytests, which are failing due to dangling references
to `generate`
Prior to the folder restructure, the `paths` for `test-invoke-pip` did
not include the UI's path `invokeai/frontend/`:
```yaml
paths:
- 'pyproject.toml'
- 'ldm/**'
- 'invokeai/backend/**'
- 'invokeai/configs/**'
- 'invokeai/frontend/dist/**'
```
After the restructure, more code was moved into the `invokeai/frontend/`
folder, and `paths` was updated:
```yaml
paths:
- 'pyproject.toml'
- 'invokeai/**'
- 'invokeai/backend/**'
- 'invokeai/configs/**'
- 'invokeai/frontend/web/dist/**'
```
Now, the second path includes the UI. The UI now needs to be excluded,
and must be excluded prior to `invokeai/frontend/web/dist/**` being
included.
On `test-invoke-pip-skip`, we need to do a bit of logic juggling to
invert the folder selection. First, include the web folder, then exclude
everying around it and finally exclude the `dist/` folder
