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from ..utils import common_annotator_call, define_preprocessor_inputs, INPUT
import comfy.model_management as model_management
class DSINE_Normal_Map_Preprocessor:
@classmethod
def INPUT_TYPES(s):
return define_preprocessor_inputs(
fov=INPUT.FLOAT(max=365.0, default=60.0),
iterations=INPUT.INT(min=1, max=20, default=5),
resolution=INPUT.RESOLUTION()
)
RETURN_TYPES = ("IMAGE",)
FUNCTION = "execute"
CATEGORY = "ControlNet Preprocessors/Normal and Depth Estimators"
def execute(self, image, fov=60.0, iterations=5, resolution=512, **kwargs):
from custom_controlnet_aux.dsine import DsineDetector
model = DsineDetector.from_pretrained().to(model_management.get_torch_device())
out = common_annotator_call(model, image, fov=fov, iterations=iterations, resolution=resolution)
del model
return (out,)
NODE_CLASS_MAPPINGS = {
"DSINE-NormalMapPreprocessor": DSINE_Normal_Map_Preprocessor
}
NODE_DISPLAY_NAME_MAPPINGS = {
"DSINE-NormalMapPreprocessor": "DSINE Normal Map"
}