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from ..utils import common_annotator_call, define_preprocessor_inputs, INPUT
import comfy.model_management as model_management
class Depth_Anything_Preprocessor:
@classmethod
def INPUT_TYPES(s):
return define_preprocessor_inputs(
ckpt_name=INPUT.COMBO(
["depth_anything_vitl14.pth", "depth_anything_vitb14.pth", "depth_anything_vits14.pth"]
),
resolution=INPUT.RESOLUTION()
)
RETURN_TYPES = ("IMAGE",)
FUNCTION = "execute"
CATEGORY = "ControlNet Preprocessors/Normal and Depth Estimators"
def execute(self, image, ckpt_name="depth_anything_vitl14.pth", resolution=512, **kwargs):
from custom_controlnet_aux.depth_anything import DepthAnythingDetector
model = DepthAnythingDetector.from_pretrained(filename=ckpt_name).to(model_management.get_torch_device())
out = common_annotator_call(model, image, resolution=resolution)
del model
return (out, )
class Zoe_Depth_Anything_Preprocessor:
@classmethod
def INPUT_TYPES(s):
return define_preprocessor_inputs(
environment=INPUT.COMBO(["indoor", "outdoor"]),
resolution=INPUT.RESOLUTION()
)
RETURN_TYPES = ("IMAGE",)
FUNCTION = "execute"
CATEGORY = "ControlNet Preprocessors/Normal and Depth Estimators"
def execute(self, image, environment="indoor", resolution=512, **kwargs):
from custom_controlnet_aux.zoe import ZoeDepthAnythingDetector
ckpt_name = "depth_anything_metric_depth_indoor.pt" if environment == "indoor" else "depth_anything_metric_depth_outdoor.pt"
model = ZoeDepthAnythingDetector.from_pretrained(filename=ckpt_name).to(model_management.get_torch_device())
out = common_annotator_call(model, image, resolution=resolution)
del model
return (out, )
NODE_CLASS_MAPPINGS = {
"DepthAnythingPreprocessor": Depth_Anything_Preprocessor,
"Zoe_DepthAnythingPreprocessor": Zoe_Depth_Anything_Preprocessor
}
NODE_DISPLAY_NAME_MAPPINGS = {
"DepthAnythingPreprocessor": "Depth Anything",
"Zoe_DepthAnythingPreprocessor": "Zoe Depth Anything"
} |