gartajackhats1985's picture
Upload 1633 files
681fa96 verified
raw
history blame
2.08 kB
from ..utils import common_annotator_call, define_preprocessor_inputs, INPUT
import comfy.model_management as model_management
import json
class OpenPose_Preprocessor:
@classmethod
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",
}