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from typing import Union
import numpy as np
from collections.abc import Iterable
from .control import LatentKeyframe, LatentKeyframeGroup
from .control import StrengthInterpolation as SI
from .logger import logger
class LatentKeyframeNode:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"batch_index": ("INT", {"default": 0, "min": -1000, "max": 1000, "step": 1}),
"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
},
"optional": {
"prev_latent_kf": ("LATENT_KEYFRAME", ),
}
}
RETURN_NAMES = ("LATENT_KF", )
RETURN_TYPES = ("LATENT_KEYFRAME", )
FUNCTION = "load_keyframe"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/keyframes"
def load_keyframe(self,
batch_index: int,
strength: float,
prev_latent_kf: LatentKeyframeGroup=None,
prev_latent_keyframe: LatentKeyframeGroup=None, # old name
):
prev_latent_keyframe = prev_latent_keyframe if prev_latent_keyframe else prev_latent_kf
if not prev_latent_keyframe:
prev_latent_keyframe = LatentKeyframeGroup()
else:
prev_latent_keyframe = prev_latent_keyframe.clone()
keyframe = LatentKeyframe(batch_index, strength)
prev_latent_keyframe.add(keyframe)
return (prev_latent_keyframe,)
class LatentKeyframeGroupNode:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"index_strengths": ("STRING", {"multiline": True, "default": ""}),
},
"optional": {
"prev_latent_kf": ("LATENT_KEYFRAME", ),
"latent_optional": ("LATENT", ),
"print_keyframes": ("BOOLEAN", {"default": False})
}
}
RETURN_NAMES = ("LATENT_KF", )
RETURN_TYPES = ("LATENT_KEYFRAME", )
FUNCTION = "load_keyframes"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/keyframes"
def validate_index(self, index: int, latent_count: int = 0, is_range: bool = False, allow_negative = False) -> int:
# if part of range, do nothing
if is_range:
return index
# otherwise, validate index
# validate not out of range - only when latent_count is passed in
if latent_count > 0 and index > latent_count-1:
raise IndexError(f"Index '{index}' out of range for the total {latent_count} latents.")
# if negative, validate not out of range
if index < 0:
if not allow_negative:
raise IndexError(f"Negative indeces not allowed, but was {index}.")
conv_index = latent_count+index
if conv_index < 0:
raise IndexError(f"Index '{index}', converted to '{conv_index}' out of range for the total {latent_count} latents.")
index = conv_index
return index
def convert_to_index_int(self, raw_index: str, latent_count: int = 0, is_range: bool = False, allow_negative = False) -> int:
try:
return self.validate_index(int(raw_index), latent_count=latent_count, is_range=is_range, allow_negative=allow_negative)
except ValueError as e:
raise ValueError(f"index '{raw_index}' must be an integer.", e)
def convert_to_latent_keyframes(self, latent_indeces: str, latent_count: int) -> set[LatentKeyframe]:
if not latent_indeces:
return set()
int_latent_indeces = [i for i in range(0, latent_count)]
allow_negative = latent_count > 0
chosen_indeces = set()
# parse string - allow positive ints, negative ints, and ranges separated by ':'
groups = latent_indeces.split(",")
groups = [g.strip() for g in groups]
for g in groups:
# parse strengths - default to 1.0 if no strength given
strength = 1.0
if '=' in g:
g, strength_str = g.split("=", 1)
g = g.strip()
try:
strength = float(strength_str.strip())
except ValueError as e:
raise ValueError(f"strength '{strength_str}' must be a float.", e)
if strength < 0:
raise ValueError(f"Strength '{strength}' cannot be negative.")
# parse range of indeces (e.g. 2:16)
if ':' in g:
index_range = g.split(":", 1)
index_range = [r.strip() for r in index_range]
start_index = self.convert_to_index_int(index_range[0], latent_count=latent_count, is_range=True, allow_negative=allow_negative)
end_index = self.convert_to_index_int(index_range[1], latent_count=latent_count, is_range=True, allow_negative=allow_negative)
# if latents were passed in, base indeces on known latent count
if len(int_latent_indeces) > 0:
for i in int_latent_indeces[start_index:end_index]:
chosen_indeces.add(LatentKeyframe(i, strength))
# otherwise, assume indeces are valid
else:
for i in range(start_index, end_index):
chosen_indeces.add(LatentKeyframe(i, strength))
# parse individual indeces
else:
chosen_indeces.add(LatentKeyframe(self.convert_to_index_int(g, latent_count=latent_count, allow_negative=allow_negative), strength))
return chosen_indeces
def load_keyframes(self,
index_strengths: str,
prev_latent_kf: LatentKeyframeGroup=None,
prev_latent_keyframe: LatentKeyframeGroup=None, # old name
latent_image_opt=None,
print_keyframes=False):
prev_latent_keyframe = prev_latent_keyframe if prev_latent_keyframe else prev_latent_kf
if not prev_latent_keyframe:
prev_latent_keyframe = LatentKeyframeGroup()
else:
prev_latent_keyframe = prev_latent_keyframe.clone()
curr_latent_keyframe = LatentKeyframeGroup()
latent_count = -1
if latent_image_opt:
latent_count = latent_image_opt['samples'].size()[0]
latent_keyframes = self.convert_to_latent_keyframes(index_strengths, latent_count=latent_count)
for latent_keyframe in latent_keyframes:
curr_latent_keyframe.add(latent_keyframe)
if print_keyframes:
for keyframe in curr_latent_keyframe.keyframes:
logger.info(f"keyframe {keyframe.batch_index}:{keyframe.strength}")
# replace values with prev_latent_keyframes
for latent_keyframe in prev_latent_keyframe.keyframes:
curr_latent_keyframe.add(latent_keyframe)
return (curr_latent_keyframe,)
class LatentKeyframeInterpolationNode:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"batch_index_from": ("INT", {"default": 0, "min": -10000, "max": 10000, "step": 1}),
"batch_index_to_excl": ("INT", {"default": 0, "min": -10000, "max": 10000, "step": 1}),
"strength_from": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"strength_to": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"interpolation": ([SI.LINEAR, SI.EASE_IN, SI.EASE_OUT, SI.EASE_IN_OUT], ),
},
"optional": {
"prev_latent_kf": ("LATENT_KEYFRAME", ),
"print_keyframes": ("BOOLEAN", {"default": False})
}
}
RETURN_NAMES = ("LATENT_KF", )
RETURN_TYPES = ("LATENT_KEYFRAME", )
FUNCTION = "load_keyframe"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/keyframes"
def load_keyframe(self,
batch_index_from: int,
strength_from: float,
batch_index_to_excl: int,
strength_to: float,
interpolation: str,
prev_latent_kf: LatentKeyframeGroup=None,
prev_latent_keyframe: LatentKeyframeGroup=None, # old name
print_keyframes=False):
if (batch_index_from > batch_index_to_excl):
raise ValueError("batch_index_from must be less than or equal to batch_index_to.")
if (batch_index_from < 0 and batch_index_to_excl >= 0):
raise ValueError("batch_index_from and batch_index_to must be either both positive or both negative.")
prev_latent_keyframe = prev_latent_keyframe if prev_latent_keyframe else prev_latent_kf
if not prev_latent_keyframe:
prev_latent_keyframe = LatentKeyframeGroup()
else:
prev_latent_keyframe = prev_latent_keyframe.clone()
curr_latent_keyframe = LatentKeyframeGroup()
steps = batch_index_to_excl - batch_index_from
diff = strength_to - strength_from
if interpolation == SI.LINEAR:
weights = np.linspace(strength_from, strength_to, steps)
elif interpolation == SI.EASE_IN:
index = np.linspace(0, 1, steps)
weights = diff * np.power(index, 2) + strength_from
elif interpolation == SI.EASE_OUT:
index = np.linspace(0, 1, steps)
weights = diff * (1 - np.power(1 - index, 2)) + strength_from
elif interpolation == SI.EASE_IN_OUT:
index = np.linspace(0, 1, steps)
weights = diff * ((1 - np.cos(index * np.pi)) / 2) + strength_from
for i in range(steps):
keyframe = LatentKeyframe(batch_index_from + i, float(weights[i]))
curr_latent_keyframe.add(keyframe)
if print_keyframes:
for keyframe in curr_latent_keyframe.keyframes:
logger.info(f"keyframe {keyframe.batch_index}:{keyframe.strength}")
# replace values with prev_latent_keyframes
for latent_keyframe in prev_latent_keyframe.keyframes:
curr_latent_keyframe.add(latent_keyframe)
return (curr_latent_keyframe,)
class LatentKeyframeBatchedGroupNode:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"float_strengths": ("FLOAT", {"default": -1, "min": -1, "step": 0.001, "forceInput": True}),
},
"optional": {
"prev_latent_kf": ("LATENT_KEYFRAME", ),
"print_keyframes": ("BOOLEAN", {"default": False})
}
}
RETURN_NAMES = ("LATENT_KF", )
RETURN_TYPES = ("LATENT_KEYFRAME", )
FUNCTION = "load_keyframe"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/keyframes"
def load_keyframe(self, float_strengths: Union[float, list[float]],
prev_latent_kf: LatentKeyframeGroup=None,
prev_latent_keyframe: LatentKeyframeGroup=None, # old name
print_keyframes=False):
prev_latent_keyframe = prev_latent_keyframe if prev_latent_keyframe else prev_latent_kf
if not prev_latent_keyframe:
prev_latent_keyframe = LatentKeyframeGroup()
else:
prev_latent_keyframe = prev_latent_keyframe.clone()
curr_latent_keyframe = LatentKeyframeGroup()
# if received a normal float input, do nothing
if type(float_strengths) in (float, int):
logger.info("No batched float_strengths passed into Latent Keyframe Batch Group node; will not create any new keyframes.")
# if iterable, attempt to create LatentKeyframes with chosen strengths
elif isinstance(float_strengths, Iterable):
for idx, strength in enumerate(float_strengths):
keyframe = LatentKeyframe(idx, strength)
curr_latent_keyframe.add(keyframe)
else:
raise ValueError(f"Expected strengths to be an iterable input, but was {type(float_strengths).__repr__}.")
if print_keyframes:
for keyframe in curr_latent_keyframe.keyframes:
logger.info(f"keyframe {keyframe.batch_index}:{keyframe.strength}")
# replace values with prev_latent_keyframes
for latent_keyframe in prev_latent_keyframe.keyframes:
curr_latent_keyframe.add(latent_keyframe)
return (curr_latent_keyframe,)
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