File size: 10,015 Bytes
baa8e90 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 |
from torch import Tensor
import torch
from .control import TimestepKeyframe, TimestepKeyframeGroup, ControlWeights, get_properly_arranged_t2i_weights, linear_conversion
from .logger import logger
WEIGHTS_RETURN_NAMES = ("CN_WEIGHTS", "TK_SHORTCUT")
class DefaultWeights:
@classmethod
def INPUT_TYPES(s):
return {
}
RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
RETURN_NAMES = WEIGHTS_RETURN_NAMES
FUNCTION = "load_weights"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights"
def load_weights(self):
weights = ControlWeights.default()
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class ScaledSoftMaskedUniversalWeights:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mask": ("MASK", ),
"min_base_multiplier": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}, ),
"max_base_multiplier": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}, ),
#"lock_min": ("BOOLEAN", {"default": False}, ),
#"lock_max": ("BOOLEAN", {"default": False}, ),
},
}
RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
RETURN_NAMES = WEIGHTS_RETURN_NAMES
FUNCTION = "load_weights"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights"
def load_weights(self, mask: Tensor, min_base_multiplier: float, max_base_multiplier: float, lock_min=False, lock_max=False):
# normalize mask
mask = mask.clone()
x_min = 0.0 if lock_min else mask.min()
x_max = 1.0 if lock_max else mask.max()
if x_min == x_max:
mask = torch.ones_like(mask) * max_base_multiplier
else:
mask = linear_conversion(mask, x_min, x_max, min_base_multiplier, max_base_multiplier)
weights = ControlWeights.universal_mask(weight_mask=mask)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class ScaledSoftUniversalWeights:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"base_multiplier": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 1.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
},
}
RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
RETURN_NAMES = WEIGHTS_RETURN_NAMES
FUNCTION = "load_weights"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights"
def load_weights(self, base_multiplier, flip_weights):
weights = ControlWeights.universal(base_multiplier=base_multiplier, flip_weights=flip_weights)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class SoftControlNetWeights:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 0.09941396206337118, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 0.12050177219802567, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 0.14606275417942507, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 0.17704576264172736, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_04": ("FLOAT", {"default": 0.214600924414215, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_05": ("FLOAT", {"default": 0.26012233262329093, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_06": ("FLOAT", {"default": 0.3152997971191405, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_07": ("FLOAT", {"default": 0.3821815722656249, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_08": ("FLOAT", {"default": 0.4632503906249999, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_09": ("FLOAT", {"default": 0.561515625, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_10": ("FLOAT", {"default": 0.6806249999999999, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_11": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_12": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
},
}
RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
RETURN_NAMES = WEIGHTS_RETURN_NAMES
FUNCTION = "load_weights"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/ControlNet"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11, weight_12, flip_weights):
weights = [weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11, weight_12]
weights = ControlWeights.controlnet(weights, flip_weights=flip_weights)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class CustomControlNetWeights:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_04": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_05": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_06": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_07": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_08": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_09": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_10": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_11": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_12": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
}
}
RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
RETURN_NAMES = WEIGHTS_RETURN_NAMES
FUNCTION = "load_weights"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/ControlNet"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11, weight_12, flip_weights):
weights = [weight_00, weight_01, weight_02, weight_03, weight_04, weight_05, weight_06,
weight_07, weight_08, weight_09, weight_10, weight_11, weight_12]
weights = ControlWeights.controlnet(weights, flip_weights=flip_weights)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class SoftT2IAdapterWeights:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 0.25, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 0.62, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 0.825, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
},
}
RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
RETURN_NAMES = WEIGHTS_RETURN_NAMES
FUNCTION = "load_weights"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/T2IAdapter"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, flip_weights):
weights = [weight_00, weight_01, weight_02, weight_03]
weights = get_properly_arranged_t2i_weights(weights)
weights = ControlWeights.t2iadapter(weights, flip_weights=flip_weights)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
class CustomT2IAdapterWeights:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"weight_00": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_01": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_02": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"weight_03": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}, ),
"flip_weights": ("BOOLEAN", {"default": False}),
},
}
RETURN_TYPES = ("CONTROL_NET_WEIGHTS", "TIMESTEP_KEYFRAME",)
RETURN_NAMES = WEIGHTS_RETURN_NAMES
FUNCTION = "load_weights"
CATEGORY = "Adv-ControlNet 🛂🅐🅒🅝/weights/T2IAdapter"
def load_weights(self, weight_00, weight_01, weight_02, weight_03, flip_weights):
weights = [weight_00, weight_01, weight_02, weight_03]
weights = get_properly_arranged_t2i_weights(weights)
weights = ControlWeights.t2iadapter(weights, flip_weights=flip_weights)
return (weights, TimestepKeyframeGroup.default(TimestepKeyframe(control_weights=weights)))
|