Class LTXAddVideoICLoRAGuide

iclora.py:18–257

@comfy_node(name="LTXAddVideoICLoRAGuide")
class LTXAddVideoICLoRAGuide(io.ComfyNode):
    PATCHIFIER = nodes_lt.SymmetricPatchifier(1, start_end=True)

    @classmethod
    def define_schema(cls):
        return io.Schema(
            node_id="LTXAddVideoICLoRAGuide",
            display_name=NODES_DISPLAY_NAME_PREFIX + " Add Video IC-LoRA Guide",
            category="Lightricks/IC-LoRA",
            description=(
                "Adds one or more conditioning frames starting at the specified frame index. "
                "Supports both single images and multi-frame videos. "
                "The latent_downscale_factor resizes input to a fraction of the target size "
                "(1 = original, 2 = half, 3 = third, etc.) for IC-LoRA on small grids."
            ),
            inputs=[
                io.Conditioning.Input("positive"),
                io.Conditioning.Input("negative"),
                io.Vae.Input("vae"),
                io.Latent.Input(
                    "latent",
                    tooltip="Video-only latent to condition. Must be a 5D video latent (batch, channels, frames, height, width).",
                ),
                io.Image.Input("image"),
                io.Int.Input(
                    "frame_idx",
                    default=0,
                    min=-9999,
                    max=9999,
                    tooltip=(
                        "Frame index to start the conditioning at. "
                        "For single-frame videos, any frame_idx value is acceptable. "
                        "For videos, frame_idx must be 1 modulo 8, otherwise it will be rounded "
                        "down to the nearest 1 modulo 8. Negative values are counted from the end of the video."
                    ),
                ),
                io.Float.Input(
                    "strength",
                    default=1.0,
                    min=0.0,
                    max=1.0,
                    step=0.01,
                ),
                io.Float.Input(
                    "latent_downscale_factor",
                    default=1.0,
                    min=1.0,
                    max=10.0,
                    step=1.0,
                    tooltip="For IC-LoRA on small grid. 1 means original size, 2 means half size, 3 means third, etc.",
                ),
                io.Combo.Input(
                    "crop",
                    options=["disabled", "center"],
                    default="disabled",
                    tooltip="Crop mode when resizing. 'center' crops to fit, 'disabled' stretches to fit.",
                ),
                io.Boolean.Input(