CavinHuang-comfyui-nodes-docs/docs/SeargeParameterProcessor.md

Documentation

• Class name: SeargeParameterProcessor
• Category: Searge/deprecated/UI
• Output node: False
• Repo Ref: https://github.com/jobunk/SeargeSDXL.git

该节点旨在处理和优化图像生成任务的输入参数，确保参数正确配置以实现期望的输出质量和风格。

Input types

Required

• inputs
  • 输入参数至关重要，因为它提供了节点将处理和优化的初始参数集。它直接影响节点的操作和最终输出。
  • Comfy dtype: Dict[str, Any]
  • Python dtype: Dict[str, Any]

Output types

• parameters
  • 输出参数代表了处理过并优化的参数集，现在可以准备在图像生成过程的后续阶段使用。
  • Comfy dtype: Dict[str, Any]
  • Python dtype: Dict[str, Any]

Usage tips

• Infra type: CPU

Source code

class SeargeParameterProcessor:
    REFINER_INTENSITY = ['hard', 'soft']
    HRF_SEED_OFFSET = ['same', 'distinct']
    STATES = ['disabled', 'enabled']
    OPERATION_MODE = ['text to image', 'image to image', 'inpainting']
    PROMPT_STYLE = ['simple', '3 prompts G+L-N', 'subject focus', 'style focus', 'weighted', 'overlay', 'subject - style', 'style - subject', 'style only', 'weighted - overlay', 'overlay - weighted']
    STYLE_TEMPLATE = ['none', 'from preprocessor', 'test']
    SAVE_TO = ['output folder', 'input folder']

    @classmethod
    def INPUT_TYPES(s):
        return {'required': {'inputs': ('PARAMETER_INPUTS',)}}
    RETURN_TYPES = ('PARAMETERS',)
    RETURN_NAMES = ('parameters',)
    FUNCTION = 'process'
    CATEGORY = 'Searge/_deprecated_/UI'

    def process(self, inputs):
        if inputs is None:
            parameters = {}
        else:
            parameters = inputs
        if parameters['denoise'] is None:
            parameters['denoise'] = 1.0
        saturation = parameters['refiner_intensity']
        if saturation is not None:
            if saturation == SeargeParameterProcessor.REFINER_INTENSITY[1]:
                parameters['noise_offset'] = 1
            else:
                parameters['noise_offset'] = 0
        hires_fix = parameters['hires_fix']
        if hires_fix is not None and hires_fix == SeargeParameterProcessor.STATES[0]:
            parameters['hrf_steps'] = 0
        hrf_saturation = parameters['hrf_intensity']
        if hrf_saturation is not None:
            if hrf_saturation == SeargeParameterProcessor.REFINER_INTENSITY[1]:
                parameters['hrf_noise_offset'] = 1
            else:
                parameters['hrf_noise_offset'] = 0
        seed_offset = parameters['hrf_seed_offset']
        if seed_offset is not None:
            seed = parameters['seed'] if parameters['seed'] is not None else 0
            if seed_offset == SeargeParameterProcessor.HRF_SEED_OFFSET[1]:
                parameters['hrf_seed'] = seed + 3
            else:
                parameters['hrf_seed'] = seed
        style_template = parameters['style_template']
        if style_template is not None:
            if style_template == SeargeParameterProcessor.STYLE_TEMPLATE[1]:
                pass
            if style_template == SeargeParameterProcessor.STYLE_TEMPLATE[2]:
                if parameters['noise_offset'] is not None:
                    parameters['noise_offset'] = 1 - parameters['hrf_noise_offset']
                if parameters['hrf_noise_offset'] is not None:
                    parameters['hrf_noise_offset'] = 1 - parameters['hrf_noise_offset']
            else:
                pass
        operation_mode = parameters['operation_mode']
        if operation_mode is not None:
            if operation_mode == SeargeParameterProcessor.OPERATION_MODE[1]:
                parameters['operation_selector'] = 1
            elif operation_mode == SeargeParameterProcessor.OPERATION_MODE[2]:
                parameters['operation_selector'] = 2
            else:
                parameters['operation_selector'] = 0
                parameters['denoise'] = 1.0
        prompt_style = parameters['prompt_style']
        if prompt_style is not None:
            if prompt_style == SeargeParameterProcessor.PROMPT_STYLE[0]:
                parameters['prompt_style_selector'] = 0
                parameters['prompt_style_group'] = 0
                main_prompt = parameters['main_prompt']
                parameters['secondary_prompt'] = main_prompt
                parameters['style_prompt'] = ''
                parameters['negative_style'] = ''
            elif prompt_style == SeargeParameterProcessor.PROMPT_STYLE[2]:
                parameters['prompt_style_selector'] = 1
                parameters['prompt_style_group'] = 0
            elif prompt_style == SeargeParameterProcessor.PROMPT_STYLE[3]:
                parameters['prompt_style_selector'] = 2
                parameters['prompt_style_group'] = 0
            elif prompt_style == SeargeParameterProcessor.PROMPT_STYLE[4]:
                parameters['prompt_style_selector'] = 3
                parameters['prompt_style_group'] = 0
            elif prompt_style == SeargeParameterProcessor.PROMPT_STYLE[5]:
                parameters['prompt_style_selector'] = 4
                parameters['prompt_style_group'] = 0
            elif prompt_style == SeargeParameterProcessor.PROMPT_STYLE[6]:
                parameters['prompt_style_selector'] = 0
                parameters['prompt_style_group'] = 1
            elif prompt_style == SeargeParameterProcessor.PROMPT_STYLE[7]:
                parameters['prompt_style_selector'] = 1
                parameters['prompt_style_group'] = 1
            elif prompt_style == SeargeParameterProcessor.PROMPT_STYLE[8]:
                parameters['prompt_style_selector'] = 2
                parameters['prompt_style_group'] = 1
            elif prompt_style == SeargeParameterProcessor.PROMPT_STYLE[9]:
                parameters['prompt_style_selector'] = 3
                parameters['prompt_style_group'] = 1
            elif prompt_style == SeargeParameterProcessor.PROMPT_STYLE[10]:
                parameters['prompt_style_selector'] = 4
                parameters['prompt_style_group'] = 1
            else:
                parameters['prompt_style_selector'] = 0
                parameters['prompt_style_group'] = 0
                parameters['style_prompt'] = ''
                parameters['negative_style'] = ''
        save_image = parameters['save_image']
        if save_image is not None:
            if save_image == SeargeParameterProcessor.STATES[0]:
                parameters['save_upscaled_image'] = SeargeParameterProcessor.STATES[0]
                parameters['hires_fix'] = SeargeParameterProcessor.STATES[0]
            elif parameters['save_directory'] == SeargeParameterProcessor.SAVE_TO[1]:
                parameters['hires_fix'] = SeargeParameterProcessor.STATES[1]
        return (parameters,)