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from ..utils import common_annotator_call, define_preprocessor_inputs, INPUT
import comfy.model_management as model_management
class LERES_Depth_Map_Preprocessor:
@classmethod
def INPUT_TYPES(s):
return define_preprocessor_inputs(
rm_nearest=INPUT.FLOAT(max=100.0),
rm_background=INPUT.FLOAT(max=100.0),
boost=INPUT.COMBO(["disable", "enable"]),
resolution=INPUT.RESOLUTION()
)
RETURN_TYPES = ("IMAGE",)
FUNCTION = "execute"
CATEGORY = "ControlNet Preprocessors/Normal and Depth Estimators"
def execute(self, image, rm_nearest=0, rm_background=0, resolution=512, boost="disable", **kwargs):
from custom_controlnet_aux.leres import LeresDetector
model = LeresDetector.from_pretrained().to(model_management.get_torch_device())
out = common_annotator_call(model, image, resolution=resolution, thr_a=rm_nearest, thr_b=rm_background, boost=boost == "enable")
del model
return (out, )
NODE_CLASS_MAPPINGS = {
"LeReS-DepthMapPreprocessor": LERES_Depth_Map_Preprocessor
}
NODE_DISPLAY_NAME_MAPPINGS = {
"LeReS-DepthMapPreprocessor": "LeReS Depth Map (enable boost for leres++)"
} |