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from ..utils import common_annotator_call, define_preprocessor_inputs, INPUT | |
import comfy.model_management as model_management | |
import json | |
class OpenPose_Preprocessor: | |
def INPUT_TYPES(s): | |
return define_preprocessor_inputs( | |
detect_hand=INPUT.COMBO(["enable", "disable"]), | |
detect_body=INPUT.COMBO(["enable", "disable"]), | |
detect_face=INPUT.COMBO(["enable", "disable"]), | |
resolution=INPUT.RESOLUTION(), | |
scale_stick_for_xinsr_cn=INPUT.COMBO(["disable", "enable"]) | |
) | |
RETURN_TYPES = ("IMAGE", "POSE_KEYPOINT") | |
FUNCTION = "estimate_pose" | |
CATEGORY = "ControlNet Preprocessors/Faces and Poses Estimators" | |
def estimate_pose(self, image, detect_hand="enable", detect_body="enable", detect_face="enable", scale_stick_for_xinsr_cn="disable", resolution=512, **kwargs): | |
from custom_controlnet_aux.open_pose import OpenposeDetector | |
detect_hand = detect_hand == "enable" | |
detect_body = detect_body == "enable" | |
detect_face = detect_face == "enable" | |
scale_stick_for_xinsr_cn = scale_stick_for_xinsr_cn == "enable" | |
model = OpenposeDetector.from_pretrained().to(model_management.get_torch_device()) | |
self.openpose_dicts = [] | |
def func(image, **kwargs): | |
pose_img, openpose_dict = model(image, **kwargs) | |
self.openpose_dicts.append(openpose_dict) | |
return pose_img | |
out = common_annotator_call(func, image, include_hand=detect_hand, include_face=detect_face, include_body=detect_body, image_and_json=True, xinsr_stick_scaling=scale_stick_for_xinsr_cn, resolution=resolution) | |
del model | |
return { | |
'ui': { "openpose_json": [json.dumps(self.openpose_dicts, indent=4)] }, | |
"result": (out, self.openpose_dicts) | |
} | |
NODE_CLASS_MAPPINGS = { | |
"OpenposePreprocessor": OpenPose_Preprocessor, | |
} | |
NODE_DISPLAY_NAME_MAPPINGS = { | |
"OpenposePreprocessor": "OpenPose Pose", | |
} |