2.3 KiB
2.3 KiB
Documentation
- Class name: SeargeUpscaleModels
- Category: UI_INPUTS
- Output node: False
- Repo Ref: https://github.com/jobunk/SeargeSDXL.git
该节点负责协调选择和配置图像增强的放大模型,重点是整合各种放大器以实现期望的输出质量。
Input types
Required
- detail_processor
- 细节处理器对于提高图像质量至关重要,在整体放大过程中发挥关键作用。
- Comfy dtype: COMBO[str]
- Python dtype: str
- high_res_upscaler
- 高分辨率放大器对于提高图像分辨率至关重要,对最终视觉效果有显著贡献。
- Comfy dtype: COMBO[str]
- Python dtype: str
- primary_upscaler
- 主要放大器在初始缩放阶段非常关键,为进一步增强设定基础。
- Comfy dtype: COMBO[str]
- Python dtype: str
- secondary_upscaler
- 次要放大器在主要缩放后进一步细化图像,改善细节和清晰度。
- Comfy dtype: COMBO[str]
- Python dtype: str
Output types
- data
- 输出数据封装了放大模型的配置,对于后续处理和最终图像输出至关重要。
- Comfy dtype: Dict[str, Any]
- Python dtype: Dict[str, Any]
Usage tips
- Infra type: CPU
Source code
class SeargeUpscaleModels:
@classmethod
def INPUT_TYPES(cls):
return {'required': {'detail_processor': (UI.UPSCALERS_1x_WITH_NONE(),), 'high_res_upscaler': (UI.UPSCALERS_4x_WITH_NONE(),), 'primary_upscaler': (UI.UPSCALERS_4x_WITH_NONE(),), 'secondary_upscaler': (UI.UPSCALERS_4x_WITH_NONE(),)}, 'optional': {'data': ('SRG_DATA_STREAM',)}}
RETURN_TYPES = ('SRG_DATA_STREAM',)
RETURN_NAMES = ('data',)
FUNCTION = 'get'
CATEGORY = UI.CATEGORY_UI_INPUTS
@staticmethod
def create_dict(detail_processor, high_res_upscaler, primary_upscaler, secondary_upscaler):
return {UI.F_DETAIL_PROCESSOR: detail_processor, UI.F_HIGH_RES_UPSCALER: high_res_upscaler, UI.F_PRIMARY_UPSCALER: primary_upscaler, UI.F_SECONDARY_UPSCALER: secondary_upscaler}
def get(self, detail_processor, high_res_upscaler, primary_upscaler, secondary_upscaler, data=None):
if data is None:
data = {}
data[UI.S_UPSCALE_MODELS] = self.create_dict(detail_processor, high_res_upscaler, primary_upscaler, secondary_upscaler)
return (data,)