CavinHuang-comfyui-nodes-docs/docs/DWPreprocessor_Provider_for_SEGS __Inspire.md

Documentation

• Class name: DWPreprocessor_Provider_for_SEGS __Inspire
• Category: InspirePack/SEGS/ControlNet
• Output node: False

DWPreprocessor Provider for SEGS是一个专为分割任务设计的图像预处理器。它通过检测手部、身体和面部等各种元素，并调整图像分辨率来增强输入数据，从而获得更好的分割结果。该预处理器利用边界框检测器和姿态估计器来完成这些任务。

Input types

Required

• detect_hand
  • 启用或禁用预处理步骤中的手部检测，影响分割的重点和准确性。
  • Comfy dtype: BOOLEAN
  • Python dtype: bool
• detect_body
  • 启用或禁用身体检测，通过识别身体轮廓来影响分割过程。
  • Comfy dtype: BOOLEAN
  • Python dtype: bool
• detect_face
  • 激活或停用面部检测，通过突出面部特征来影响分割。
  • Comfy dtype: BOOLEAN
  • Python dtype: bool
• resolution_upscale_by
  • 通过指定的放大因子调整输入图像的分辨率，提高分割的细节水平。
  • Comfy dtype: FLOAT
  • Python dtype: float
• bbox_detector
  • 指定要使用的边界框检测器模型，影响元素检测的精确度。
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• pose_estimator
  • 确定要使用的姿态估计器模型，通过准确的姿态信息增强分割效果。
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str

Output types

• segs_preprocessor
  • 提供为分割任务定制的预处理输入，包含检测到的元素和分辨率调整。
  • Comfy dtype: SEGS_PREPROCESSOR
  • Python dtype: object

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class DWPreprocessor_Provider_for_SEGS:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "detect_hand": ("BOOLEAN", {"default": True, "label_on": "enable", "label_off": "disable"}),
                "detect_body": ("BOOLEAN", {"default": True, "label_on": "enable", "label_off": "disable"}),
                "detect_face": ("BOOLEAN", {"default": True, "label_on": "enable", "label_off": "disable"}),
                "resolution_upscale_by": ("FLOAT", {"default": 1.0, "min": 0.5, "max": 100, "step": 0.1}),
                "bbox_detector": (
                    ["yolox_l.torchscript.pt", "yolox_l.onnx", "yolo_nas_l_fp16.onnx", "yolo_nas_m_fp16.onnx", "yolo_nas_s_fp16.onnx"],
                    {"default": "yolox_l.onnx"}
                ),
                "pose_estimator": (["dw-ll_ucoco_384_bs5.torchscript.pt", "dw-ll_ucoco_384.onnx", "dw-ll_ucoco.onnx"], {"default": "dw-ll_ucoco_384_bs5.torchscript.pt"})
            }
        }
    RETURN_TYPES = ("SEGS_PREPROCESSOR",)
    FUNCTION = "doit"

    CATEGORY = "InspirePack/SEGS/ControlNet"

    def doit(self, detect_hand, detect_body, detect_face, resolution_upscale_by, bbox_detector, pose_estimator):
        obj = DWPreprocessor_wrapper(detect_hand, detect_body, detect_face, upscale_factor=resolution_upscale_by, bbox_detector=bbox_detector, pose_estimator=pose_estimator)
        return (obj, )