Files
Superside ComfyUI Nodes df2c9c0beb Rename all 28 node classes with a Superside prefix
Root cause of nodes not appearing in ComfyUI: this package's node
classes originally reused the exact same class names as the internal
fal-flux-nodes package it was migrated from (e.g. NanoBananaProEditNode,
SeedreamV45EditNode). ComfyUI's NODE_CLASS_MAPPINGS is a flat global
dict - when both packages are installed, whichever loads first wins
and the other's registration for that key is silently dropped, which
is why none of the "Superside "-prefixed nodes were showing up.

Every class is now uniquely prefixed (e.g. SupersideNanoBananaProEditNode),
so this package can never collide with fal-flux-nodes, ComfyUI-fal-API,
or any other node pack regardless of install order. Updated __init__.py,
web/js/show_text.js's TEXT_DISPLAY_NODES list, and README.md to match.
2026-07-09 18:29:46 -04:00

108 lines
3.7 KiB
Python

import logging
from .base_node import (
SupersideFalNode,
ImageProcessingMixin,
APIClientMixin,
API_KEY_INPUT_SPEC,
)
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)
class SupersidePASDUpscalerNode(SupersideFalNode, ImageProcessingMixin, APIClientMixin):
"""
PASD Upscaler Node: Perform high-quality image super-resolution using PASD-SDXL.
The model applies AI-enhanced super-resolution with:
- Pixel-aware stable diffusion
- ControlNet guidance for structure preservation
- Wavelet color correction for natural results
"""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"image": ("IMAGE",),
"api_key": API_KEY_INPUT_SPEC,
},
"optional": {
"scale": ("INT", {"default": 2, "min": 1, "max": 4, "step": 1}),
"steps": ("INT", {"default": 25, "min": 10, "max": 50, "step": 1}),
"guidance_scale": (
"FLOAT",
{"default": 7.0, "min": 1.0, "max": 20.0, "step": 0.1},
),
"conditioning_scale": (
"FLOAT",
{"default": 0.8, "min": 0.1, "max": 1.0, "step": 0.1},
),
"prompt": (
"STRING",
{
"multiline": True,
"default": "",
"placeholder": "Additional prompt to guide "
"super-resolution (optional)",
},
),
"negative_prompt": (
"STRING",
{
"multiline": True,
"default": "blurry, dirty, messy, frames, deformed, dotted, "
"noise, raster lines, unclear, lowres, over-smoothed, "
"painting, ai generated",
"placeholder": "Negative prompt to avoid unwanted artifacts",
},
),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "upscale"
DESCRIPTION = (
"Perform high-quality image super-resolution using PASD-SDXL with "
"pixel-aware stable diffusion and ControlNet guidance"
)
def prepare_arguments(self, client, image, **kwargs):
"""Prepare arguments for the API call."""
# Upload the input image
image_url = self.upload_image(client, image)
arguments = {"image_url": image_url}
# Add optional parameters if provided
if kwargs.get("scale"):
arguments["scale"] = kwargs["scale"]
if kwargs.get("steps"):
arguments["steps"] = kwargs["steps"]
if kwargs.get("guidance_scale"):
arguments["guidance_scale"] = kwargs["guidance_scale"]
if kwargs.get("conditioning_scale"):
arguments["conditioning_scale"] = kwargs["conditioning_scale"]
if kwargs.get("prompt") and kwargs["prompt"].strip():
arguments["prompt"] = kwargs["prompt"].strip()
if kwargs.get("negative_prompt") and kwargs["negative_prompt"].strip():
arguments["negative_prompt"] = kwargs["negative_prompt"].strip()
return arguments
def upscale(self, image, api_key, **kwargs):
"""Main upscaling function."""
try:
client = self.get_client(api_key)
arguments = self.prepare_arguments(client, image, **kwargs)
result = self.call_api(client, "fal-ai/pasd", arguments)
return self.process_images(result)
except Exception as e:
logger.error(f"Upscaling failed: {str(e)}")
raise