The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
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#From https://github.com/kornia/kornia
import math
import torch
import torch.nn.functional as F
import comfy.model_management
from kornia.filters import canny
class Canny:
@classmethod
def INPUT_TYPES(s):
return {"required": {"image": ("IMAGE",),
"low_threshold": ("FLOAT", {"default": 0.4, "min": 0.01, "max": 0.99, "step": 0.01}),
"high_threshold": ("FLOAT", {"default": 0.8, "min": 0.01, "max": 0.99, "step": 0.01})
}}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "detect_edge"
CATEGORY = "image/preprocessors"
def detect_edge(self, image, low_threshold, high_threshold):
output = canny(image.to(comfy.model_management.get_torch_device()).movedim(-1, 1), low_threshold, high_threshold)
img_out = output[1].to(comfy.model_management.intermediate_device()).repeat(1, 3, 1, 1).movedim(1, -1)
return (img_out,)
NODE_CLASS_MAPPINGS = {
"Canny": Canny,
}