* Move detection category under image category
* Add missing categories
* Move detection nodes to detection category
* Move save nodes to image root catefory
* Rename postprocessors
* Move mask category under image
* Move guiders category to parent level at root of sampling category
* Move custom_sampling category to parent level at the root of sampling category
* Modify description of LoRA loaders
* Fix node id SolidMask
* Move VOID Quadmask under image/mask
* Group compositing nodes under image/compositing
* Move load image as mask to image category for consistency with other load image nodes
* Align display name with Load Checkpoint
* Move dataset category under training category
* Rename Number Convert to Conver Number (verb first)
* Rename Canny node
* Revert wanBlockSwap + description
* Add description to RemoveBackground node
* Revert category update of dataset
The img2vid model is conditioned on clip vision output only which means
there's no CLIP model which is why I added a ImageOnlyCheckpointLoader to
load it. Note that the unClipCheckpointLoader can also load it because it
also has a CLIP_VISION output.
SDV_img2vid_Conditioning is the node used to pass the right conditioning
to the img2vid model.
VideoLinearCFGGuidance applies a linearly decreasing CFG scale to each
video frame from the cfg set in the sampler node to min_cfg.
SDV_img2vid_Conditioning can be found in conditioning->video_models
ImageOnlyCheckpointLoader can be found in loaders->video_models
VideoLinearCFGGuidance can be found in sampling->video_models
