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Add value remap option to WeightScheduleConvert

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Kijai 2024-05-03 15:06:13 +03:00
parent 8436ac8166
commit 3e84ca7d96
1 changed files with 20 additions and 1 deletions
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21
nodes/curve_nodes.py
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@ -287,6 +287,9 @@ class WeightScheduleConvert:
"optional": {
"remap_to_frames": ("INT", {"default": 0}),
"interpolation_curve": ("FLOAT", {"forceInput": True}),
"remap_values": ("BOOLEAN", {"default": False}),
"remap_min": ("FLOAT", {"default": 0.0, "min": -100000, "max": 100000.0, "step": 0.01}),
"remap_max": ("FLOAT", {"default": 1.0, "min": -100000, "max": 100000.0, "step": 0.01}),
},
}
@ -308,7 +311,7 @@ Converts different value lists/series to another type.
else:
raise ValueError("Unsupported input type")
def execute(self, input_values, output_type, invert, repeat, remap_to_frames=0, interpolation_curve=None):
def execute(self, input_values, output_type, invert, repeat, remap_to_frames=0, interpolation_curve=None, remap_min=0.0, remap_max=1.0, remap_values=False):
import pandas as pd
input_type = self.detect_input_type(input_values)
@ -345,6 +348,8 @@ Converts different value lists/series to another type.
float_values = np.interp(np.linspace(0, 1, remap_to_frames), np.linspace(0, 1, len(normalized_values)), normalized_values).tolist()
float_values = float_values * repeat
if remap_values:
float_values = self.remap_values(float_values, remap_min, remap_max)
if output_type == 'list':
out = float_values,
@ -358,6 +363,20 @@ Converts different value lists/series to another type.
elif output_type == 'match_input':
out = float_values,
return (out, [str(value) for value in float_values], [int(value) for value in float_values])
def remap_values(self, values, target_min, target_max):
# Determine the current range
current_min = min(values)
current_max = max(values)
current_range = current_max - current_min
# Determine the target range
target_range = target_max - target_min
# Perform the linear interpolation for each value
remapped_values = [(value - current_min) / current_range * target_range + target_min for value in values]
return remapped_values
class FloatToMask: