Also change import order to ensure CLI args are handled correctly. Had to do this bc importing `InvocationRegistry` before parsing args resulted in the `--root` CLI arg being ignored.
Add `heuristic_resize_fast`, which does the same thing as `heuristic_resize`, except it's about 20x faster.
This is achieved by using opencv for the binary edge handling isntead of python, and checking only 100k pixels to determine what kind of image we are working with.
Besides being much faster, it results in cleaner lines for resized binary canny edge maps, and has results in fewer misidentified segmentation maps.
Tested against normal images, binary canny edge maps, grayscale HED edge maps, segmentation maps, and normal images.
Tested resizing up and down for each.
Besides the new utility function, I needed to swap the `opencv-python` dep for `opencv-contrib-python`, which includes `cv2.ximgproc.thinning`. This function accounts for a good chunk of the perf improvement.
Upstream bug in `transformers` breaks use of `AutoModelForMaskGeneration` class to load SAM models
Simple fix - directly load the model with `SamModel` class instead.
See upstream issue https://github.com/huggingface/transformers/issues/38228
Adds full support for managing model-to-model relationships in the UI and backend.
Introduces RelatedModels subpanel for linking and unlinking models in model management.
- Adds REST API routes for adding, removing, and retrieving model relationships.
- New database migration: creates model_relationships table for bidirectional links.
- New service layer (model_relationships) for relationship management.
- Updated frontend: Related models float to top of LoRA/Main grouped model comboboxes for quick access.
- Added 'Show Only Related' toggle badge to MainModelPicker filter bar
**Amended commit to remove changes to ParamMainModelSelect.tsx and MainModelPicker.tsx to avoid conflict with upstream deletion/ rewrite**
When we do our field type overrides to allow invocations to be instantiated without all required fields, we were not modifying the annotation of the field but did set the default value of the field to `None`.
This results in an error when doing a ser/de round trip. Here's what we end up doing:
```py
from pydantic import BaseModel, Field
class MyModel(BaseModel):
foo: str = Field(default=None)
```
And here is a simple round-trip, which should not error but which does:
```py
MyModel(**MyModel().model_dump())
# ValidationError: 1 validation error for MyModel
# foo
# Input should be a valid string [type=string_type, input_value=None, input_type=NoneType]
# For further information visit https://errors.pydantic.dev/2.11/v/string_type
```
To fix this, we now check every incoming field and update its annotation to match its default value. In other words, when we override the default field value to `None`, we make its type annotation `<original type> | None`.
This prevents the error during deserialization.
This slightly alters the schema for all invocations and outputs - the values of all fields without default values are now typed as `<original type> | None`, reflecting the overrides.
This means the autogenerated types for fields have also changed for fields without defaults:
```ts
// Old
image?: components["schemas"]["ImageField"];
// New
image?: components["schemas"]["ImageField"] | null;
```
This does not break anything on the frontend.
