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from ..utils import common_annotator_call, create_node_input_types | |
import comfy.model_management as model_management | |
class DSINE_Normal_Map_Preprocessor: | |
def INPUT_TYPES(s): | |
return create_node_input_types( | |
fov=("FLOAT", {"min": 0.0, "max": 365.0, "step": 0.05, "default": 60.0}), | |
iterations=("INT", {"min": 1, "max": 20, "step": 1, "default": 5}) | |
) | |
RETURN_TYPES = ("IMAGE",) | |
FUNCTION = "execute" | |
CATEGORY = "ControlNet Preprocessors/Normal and Depth Estimators" | |
def execute(self, image, fov, iterations, resolution=512, **kwargs): | |
from 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" | |
} |