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ComfyUI/comfy_extras/nodes_sdupscale.py

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from typing_extensions import override
import torch
import comfy.utils
from comfy_api.latest import ComfyExtension, io
class SD_4XUpscale_Conditioning(io.ComfyNode):
@classmethod
def define_schema(cls):
return io.Schema(
node_id="SD_4XUpscale_Conditioning",
category="model/conditioning/stable diffusion upscaler",
inputs=[
io.Image.Input("images"),
io.Conditioning.Input("positive"),
io.Conditioning.Input("negative"),
io.Float.Input("scale_ratio", default=4.0, min=0.0, max=10.0, step=0.01),
feat: mark 429 widgets as advanced for collapsible UI (#12197) * feat: mark 429 widgets as advanced for collapsible UI Mark widgets as advanced across core, comfy_extras, and comfy_api_nodes to support the new collapsible advanced inputs section in the frontend. Changes: - 267 advanced markers in comfy_extras/ - 162 advanced markers in comfy_api_nodes/ - All files pass python3 -m py_compile verification Widgets marked advanced (hidden by default): - Scheduler internals: sigma_max, sigma_min, rho, mu, beta, alpha - Sampler internals: eta, s_noise, order, rtol, atol, h_init, pcoeff, etc. - Memory optimization: tile_size, overlap, temporal_size, temporal_overlap - Pipeline controls: add_noise, start_at_step, end_at_step - Timing controls: start_percent, end_percent - Layer selection: stop_at_clip_layer, layers, block_number - Video encoding: codec, crf, format - Device/dtype: device, noise_device, dtype, weight_dtype Widgets kept basic (always visible): - Core params: strength, steps, cfg, denoise, seed, width, height - Model selectors: ckpt_name, lora_name, vae_name, sampler_name - Common controls: upscale_method, crop, batch_size, fps, opacity Related: frontend PR #11939 Amp-Thread-ID: https://ampcode.com/threads/T-019c1734-6b61-702e-b333-f02c399963fc * fix: remove advanced=True from DynamicCombo.Input (unsupported) Amp-Thread-ID: https://ampcode.com/threads/T-019c1734-6b61-702e-b333-f02c399963fc * fix: address review - un-mark model merge, video, image, and training node widgets as advanced Per comfyanonymous review: - Model merge arguments should not be advanced (all 14 model-specific merge classes) - SaveAnimatedWEBP lossless/quality/method should not be advanced - SaveWEBM/SaveVideo codec/crf/format should not be advanced - TrainLoraNode options should not be advanced (7 inputs) Amp-Thread-ID: https://ampcode.com/threads/T-019c322b-a3a8-71b7-9962-d44573ca6352 * fix: un-mark batch_size and webcam width/height as advanced (should stay basic) Amp-Thread-ID: https://ampcode.com/threads/T-019c3236-1417-74aa-82a3-bcb365fbe9d1 --------- Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>
2026-02-19 19:20:02 -08:00
io.Float.Input("noise_augmentation", default=0.0, min=0.0, max=1.0, step=0.001, advanced=True),
],
outputs=[
io.Conditioning.Output(display_name="positive"),
io.Conditioning.Output(display_name="negative"),
io.Latent.Output(display_name="latent"),
],
)
@classmethod
def execute(cls, images, positive, negative, scale_ratio, noise_augmentation):
width = max(1, round(images.shape[-2] * scale_ratio))
height = max(1, round(images.shape[-3] * scale_ratio))
pixels = comfy.utils.common_upscale((images.movedim(-1,1) * 2.0) - 1.0, width // 4, height // 4, "bilinear", "center")
out_cp = []
out_cn = []
for t in positive:
n = [t[0], t[1].copy()]
n[1]['concat_image'] = pixels
n[1]['noise_augmentation'] = noise_augmentation
out_cp.append(n)
for t in negative:
n = [t[0], t[1].copy()]
n[1]['concat_image'] = pixels
n[1]['noise_augmentation'] = noise_augmentation
out_cn.append(n)
latent = torch.zeros([images.shape[0], 4, height // 4, width // 4])
return io.NodeOutput(out_cp, out_cn, {"samples":latent})
class SdUpscaleExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [
SD_4XUpscale_Conditioning,
]
async def comfy_entrypoint() -> SdUpscaleExtension:
return SdUpscaleExtension()