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from ..utils import common_annotator_call, create_node_input_types
import comfy.model_management as model_management
import numpy as np
class MLSD_Preprocessor:
@classmethod
def INPUT_TYPES(s):
return create_node_input_types(
score_threshold = ("FLOAT", {"default": 0.1, "min": 0.01, "max": 2.0, "step": 0.01}),
dist_threshold = ("FLOAT", {"default": 0.1, "min": 0.01, "max": 20.0, "step": 0.01})
)
RETURN_TYPES = ("IMAGE",)
FUNCTION = "execute"
CATEGORY = "ControlNet Preprocessors/Line Extractors"
def execute(self, image, score_threshold, dist_threshold, resolution=512, **kwargs):
from controlnet_aux.mlsd import MLSDdetector
model = MLSDdetector.from_pretrained().to(model_management.get_torch_device())
out = common_annotator_call(model, image, resolution=resolution, thr_v=score_threshold, thr_d=dist_threshold)
return (out, )
NODE_CLASS_MAPPINGS = {
"M-LSDPreprocessor": MLSD_Preprocessor
}
NODE_DISPLAY_NAME_MAPPINGS = {
"M-LSDPreprocessor": "M-LSD Lines"
} |