Adds SineWave Effect

This commit is contained in:
EllangoK
2023-05-08 20:22:54 -04:00
parent 76be38e595
commit 01e0826bd6
4 changed files with 108 additions and 2 deletions
+56
View File
@@ -0,0 +1,56 @@
import torch
import numpy as np
class SineWave:
def __init__(self):
pass
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"image": ("IMAGE",),
"amplitude": ("FLOAT", {
"default": 50,
"min": 0,
"max": 150,
"step": 5
}),
"frequency": ("FLOAT", {
"default": 5,
"min": 0,
"max": 20,
"step": 1
}),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "apply_sine_wave"
CATEGORY = "postprocessing/Effects"
def apply_sine_wave(self, image: torch.Tensor, amplitude: float, frequency: float):
batch_size, height, width, channels = image.shape
result = torch.zeros_like(image)
for b in range(batch_size):
tensor_image = image[b]
result[b] = self.sine_wave_effect(tensor_image, amplitude, frequency)
return (result,)
def sine_wave_effect(self, image: torch.Tensor, amplitude: float, frequency: float):
height, width, _ = image.shape
shifted_image = torch.zeros_like(image)
for channel in range(3):
for i in range(height):
offset = int(amplitude * np.sin(2 * torch.pi * i * frequency / height))
shifted_image[i, :, channel] = torch.roll(image[i, :, channel], offset)
return shifted_image
NODE_CLASS_MAPPINGS = {
"SineWave": SineWave,
}