| 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", |
| } |
