Load CLIP Vision

Documentation

Class name: CLIPVisionLoader
Category: loaders
Output node: False

The CLIPVisionLoader node is designed for loading CLIP Vision models from specified paths. It abstracts the complexities of locating and initializing CLIP Vision models, making them readily available for further processing or inference tasks.

Input types

Required

clip_name
- Specifies the name of the CLIP Vision model to be loaded. This name is used to locate the model file within a predefined directory structure.
- Comfy dtype: COMBO[STRING]
- Python dtype: str

Output types

clip_vision
- Comfy dtype: CLIP_VISION
- The loaded CLIP Vision model, ready for use in encoding images or performing other vision-related tasks.
- Python dtype: torch.nn.Module

Usage tips

Infra type: CPU
Common nodes:
- IPAdapterApply
- IPAdapterApplyFaceID
- IPAdapter
- IPAdapterEncoder
- CLIPVisionEncode
- ToIPAdapterPipe //Inspire
- Reroute
- AV_IPAdapter

Source code

class CLIPVisionLoader:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": { "clip_name": (folder_paths.get_filename_list("clip_vision"), ),
                             }}
    RETURN_TYPES = ("CLIP_VISION",)
    FUNCTION = "load_clip"

    CATEGORY = "loaders"

    def load_clip(self, clip_name):
        clip_path = folder_paths.get_full_path("clip_vision", clip_name)
        clip_vision = comfy.clip_vision.load(clip_path)
        return (clip_vision,)

1.8 KiB Raw Permalink Blame History