Superside ComfyUI Nodes
df2c9c0beb
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.
206 lines
6.5 KiB
Python
206 lines
6.5 KiB
Python
import logging
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from .base_node import (
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APIClientMixin,
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SupersideFalNode,
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ImageProcessingMixin,
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API_KEY_INPUT_SPEC,
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)
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logger = logging.getLogger(__name__)
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class SupersideTopazUpscaleImageNode(
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SupersideFalNode, ImageProcessingMixin, APIClientMixin
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):
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"""
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Topaz Upscale Image Node: Upscale or enhance images with Topaz models
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via fal.ai API.
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"""
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"image": ("IMAGE",),
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"api_key": API_KEY_INPUT_SPEC,
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},
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"optional": {
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"model": (
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[
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"Low Resolution V2",
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"Standard V2",
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"CGI",
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"High Fidelity V2",
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"Text Refine",
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"Recovery",
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"Redefine",
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"Recovery V2",
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"Standard MAX",
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"Wonder",
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],
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{"default": "Standard V2"},
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),
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"upscale_factor": (
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"FLOAT",
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{
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"default": 2.0,
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"min": 1.0,
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"max": 4.0,
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"step": 0.1,
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"display": "slider",
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},
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),
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"crop_to_fill": ("BOOLEAN", {"default": False}),
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"output_format": (["jpeg", "png"], {"default": "jpeg"}),
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"subject_detection": (
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["All", "Foreground", "Background"],
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{"default": "All"},
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),
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"face_enhancement": ("BOOLEAN", {"default": True}),
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"face_enhancement_creativity": (
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"FLOAT",
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{
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"default": 0.0,
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"min": 0.0,
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"max": 1.0,
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"step": 0.1,
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"display": "slider",
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},
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),
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"face_enhancement_strength": (
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"FLOAT",
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{
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"default": 0.8,
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"min": 0.0,
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"max": 1.0,
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"step": 0.1,
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"display": "slider",
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},
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),
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"sharpen": (
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"FLOAT",
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{
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"default": 0.5,
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"min": 0.0,
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"max": 1.0,
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"step": 0.1,
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"display": "slider",
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},
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),
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"denoise": (
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"FLOAT",
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{
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"default": 0.5,
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"min": 0.0,
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"max": 1.0,
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"step": 0.1,
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"display": "slider",
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},
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),
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"fix_compression": (
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"FLOAT",
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{
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"default": 0.5,
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"min": 0.0,
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"max": 1.0,
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"step": 0.1,
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"display": "slider",
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},
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),
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"strength": (
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"FLOAT",
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{
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"default": 0.5,
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"min": 0.01,
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"max": 1.0,
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"step": 0.99,
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"display": "slider",
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},
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),
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"creativity": ("INT", {"default": 1, "min": 1, "max": 6}),
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"texture": ("INT", {"default": 5, "min": 1, "max": 5}),
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"prompt": (
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"STRING",
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{
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"multiline": True,
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"placeholder": "Optional prompt for Redefine model edits",
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},
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),
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"autoprompt": ("BOOLEAN", {"default": True}),
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"detail": (
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"FLOAT",
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{
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"default": 0.5,
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"min": 0.0,
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"max": 1.0,
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"step": 0.1,
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"display": "slider",
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},
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),
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},
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}
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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "upscale"
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DISPLAY_NAME = "Topaz Upscale Image"
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DESCRIPTION = "Upscale images using Topaz enhancement models"
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def prepare_arguments(self, client, image, **kwargs):
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"""Prepare arguments for the API call."""
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arguments = {
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"image_url": self.upload_image(client, image),
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}
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for key in (
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"model",
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"upscale_factor",
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"crop_to_fill",
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"output_format",
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"subject_detection",
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"face_enhancement",
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"face_enhancement_creativity",
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"face_enhancement_strength",
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"sharpen",
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"denoise",
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"fix_compression",
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"strength",
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"creativity",
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"texture",
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"autoprompt",
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"detail",
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):
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if kwargs.get(key) is not None:
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arguments[key] = kwargs[key]
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if kwargs.get("prompt"):
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arguments["prompt"] = kwargs["prompt"]
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return arguments
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def process_result(self, result):
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"""Process Topaz's single-image response format."""
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if "image" not in result or not result["image"]:
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raise RuntimeError("No image was generated by the API.")
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img_info = result["image"]
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logger.debug(f"Processing Topaz image: {img_info}")
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if not isinstance(img_info, dict) or "url" not in img_info:
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raise RuntimeError("Invalid image format in response")
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return self.process_images({"images": [img_info]})
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def upscale(self, image, api_key, **kwargs):
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"""Main upscaling function."""
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try:
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client = self.get_client(api_key)
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arguments = self.prepare_arguments(client, image, **kwargs)
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logger.info(f"Calling Topaz Upscale API with arguments: {arguments}")
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result = self.call_api(client, "fal-ai/topaz/upscale/image", arguments)
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return self.process_result(result)
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except Exception as e:
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logger.error(f"Topaz upscaling failed: {str(e)}")
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raise
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