Trellis2Conditioning - ComfyUI Built-in Node Documentation - ComfyUI

Trellis2Conditioning converts an input image into conditioning data for the TRELLIS.2 model. It uses a CLIP vision model to encode the image into two sets of features (at 512 and 1024 scales) and packages them as a positive conditioning pair, while also creating a matching zero-filled negative conditioning pair that serves as an empty reference.

Inputs

Parameter	Description	Data Type	Required	Range
`clip_vision_model`	The CLIP vision model used to encode the image into conditioning features.	CLIP_VISION	Yes	Any available CLIP vision model
`image`	Preprocessed image from ImageCropToMask (pad_factor=1.0 for TRELLIS.2).	IMAGE	Yes	Any image

Outputs

Output Name	Description	Data Type
`positive`	Conditioning containing the encoded image features at 512 and 1024 scales, used as the positive conditioning for the TRELLIS.2 model.	CONDITIONING
`negative`	Zero-filled conditioning with the same shape as the positive conditioning, used as an empty negative reference.	CONDITIONING

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