ComfyUI/comfy_extras/nodes_zimage.py
2026-01-19 23:17:38 -05:00

89 lines
3.5 KiB
Python

import node_helpers
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io
import math
import comfy.utils
class TextEncodeZImageOmni(io.ComfyNode):
@classmethod
def define_schema(cls):
return io.Schema(
node_id="TextEncodeZImageOmni",
category="advanced/conditioning",
is_experimental=True,
inputs=[
io.Clip.Input("clip"),
io.ClipVision.Input("image_encoder", optional=True),
io.String.Input("prompt", multiline=True, dynamic_prompts=True),
io.Boolean.Input("auto_resize_images", default=True),
io.Vae.Input("vae", optional=True),
io.Image.Input("image1", optional=True),
io.Image.Input("image2", optional=True),
io.Image.Input("image3", optional=True),
],
outputs=[
io.Conditioning.Output(),
],
)
@classmethod
def execute(cls, clip, prompt, image_encoder=None, auto_resize_images=True, vae=None, image1=None, image2=None, image3=None) -> io.NodeOutput:
ref_latents = []
images = list(filter(lambda a: a is not None, [image1, image2, image3]))
prompt_list = []
template = None
if len(images) > 0:
prompt_list = ["<|im_start|>user\n<|vision_start|>"]
prompt_list += ["<|vision_end|><|vision_start|>"] * (len(images) - 1)
prompt_list += ["<|vision_end|><|im_end|>"]
template = "<|vision_end|>{}<|im_end|>\n<|im_start|>assistant\n<|vision_start|>"
encoded_images = []
for i, image in enumerate(images):
if image_encoder is not None:
encoded_images.append(image_encoder.encode_image(image))
if vae is not None:
if auto_resize_images:
samples = image.movedim(-1, 1)
total = int(1024 * 1024)
scale_by = math.sqrt(total / (samples.shape[3] * samples.shape[2]))
width = round(samples.shape[3] * scale_by / 8.0) * 8
height = round(samples.shape[2] * scale_by / 8.0) * 8
image = comfy.utils.common_upscale(samples, width, height, "area", "disabled").movedim(1, -1)
ref_latents.append(vae.encode(image))
tokens = clip.tokenize(prompt, llama_template=template)
conditioning = clip.encode_from_tokens_scheduled(tokens)
extra_text_embeds = []
for p in prompt_list:
tokens = clip.tokenize(p, llama_template="{}")
text_embeds = clip.encode_from_tokens_scheduled(tokens)
extra_text_embeds.append(text_embeds[0][0])
if len(ref_latents) > 0:
conditioning = node_helpers.conditioning_set_values(conditioning, {"reference_latents": ref_latents}, append=True)
if len(encoded_images) > 0:
conditioning = node_helpers.conditioning_set_values(conditioning, {"clip_vision_outputs": encoded_images}, append=True)
if len(extra_text_embeds) > 0:
conditioning = node_helpers.conditioning_set_values(conditioning, {"reference_latents_text_embeds": extra_text_embeds}, append=True)
return io.NodeOutput(conditioning)
class ZImageExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [
TextEncodeZImageOmni,
]
async def comfy_entrypoint() -> ZImageExtension:
return ZImageExtension()