110 lines
3.6 KiB
Python
110 lines
3.6 KiB
Python
import folder_paths
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from nodes import VAEEncode
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from .utils import TimestepKeyframeGroup
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from .control_sparsectrl import SparseMethod, SparseIndexMethod, SparseSettings, SparseSpreadMethod
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from .control import load_sparsectrl
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# node for SparseCtrl loading
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class SparseCtrlLoaderAdvanced:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"control_net_name": (folder_paths.get_filename_list("controlnet"), ),
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"use_motion": ("BOOLEAN", {"default": True}, ),
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"motion_strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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"motion_scale": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
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},
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"optional": {
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"sparse_method": ("SPARSE_METHOD", ),
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"tk_optional": ("TIMESTEP_KEYFRAME", ),
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}
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}
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RETURN_TYPES = ("CONTROL_NET", )
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FUNCTION = "load_controlnet"
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CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/SparseCtrl"
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def load_controlnet(self, control_net_name: str, use_motion: bool, motion_strength: float, motion_scale: float, sparse_method: SparseMethod=SparseSpreadMethod(), tk_optional: TimestepKeyframeGroup=None):
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controlnet_path = folder_paths.get_full_path("controlnet", control_net_name)
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sparse_settings = SparseSettings(sparse_method=sparse_method, use_motion=use_motion, motion_strength=motion_strength, motion_scale=motion_scale)
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controlnet = load_sparsectrl(controlnet_path, timestep_keyframe=tk_optional, sparse_settings=sparse_settings)
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return (controlnet,)
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class SparseIndexMethodNode:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"indexes": ("STRING", {"default": "0"}),
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}
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}
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RETURN_TYPES = ("SPARSE_METHOD",)
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FUNCTION = "get_method"
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CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/SparseCtrl"
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def get_method(self, indexes: str):
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idxs = []
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unique_idxs = set()
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# get indeces from string
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str_idxs = [x.strip() for x in indexes.strip().split(",")]
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for str_idx in str_idxs:
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try:
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idx = int(str_idx)
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if idx in unique_idxs:
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raise ValueError(f"'{idx}' is duplicated; indexes must be unique.")
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idxs.append(idx)
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unique_idxs.add(idx)
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except ValueError:
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raise ValueError(f"'{str_idx}' is not a valid integer index.")
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if len(idxs) == 0:
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raise ValueError(f"No indexes were listed in Sparse Index Method.")
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return (SparseIndexMethod(idxs),)
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class SparseSpreadMethodNode:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"spread": (SparseSpreadMethod.LIST,),
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}
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}
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RETURN_TYPES = ("SPARSE_METHOD",)
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FUNCTION = "get_method"
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CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/SparseCtrl"
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def get_method(self, spread: str):
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return (SparseSpreadMethod(spread=spread),)
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class VAEEncodePreprocessor:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"image": ("IMAGE", ),
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"vae": ("VAE", )
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}
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("latent_IMAGE",)
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FUNCTION = "preprocess_images"
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CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/SparseCtrl/preprocess"
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def preprocess_images(self, vae, image):
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image = VAEEncode.vae_encode_crop_pixels(image)
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encoded = vae.encode(image[:,:,:,:3])
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encoded = encoded.movedim(1,-1)
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return (encoded,)
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