import node_helpers import comfy.utils import math class TextEncodeQwenImageEdit: @classmethod def INPUT_TYPES(s): return {"required": { "clip": ("CLIP", ), "prompt": ("STRING", {"multiline": True, "dynamicPrompts": True}), }, "optional": {"vae": ("VAE", ), "image": ("IMAGE", ),}} RETURN_TYPES = ("CONDITIONING", "IMAGE", "LATENT") FUNCTION = "encode" CATEGORY = "advanced/conditioning" def encode(self, clip, prompt, vae=None, image=None): ref_latent = None output_image = None if image is None: images = [] else: samples = image.movedim(-1, 1) total = int(1024 * 1024) scale_by = math.sqrt(total / (samples.shape[3] * samples.shape[2])) width = math.floor(samples.shape[3] * scale_by / 8) * 8 height = math.floor(samples.shape[2] * scale_by / 8) * 8 original_width = samples.shape[3] original_height = samples.shape[2] if width < original_width or height < original_height: upscale_method = "area" else: upscale_method = "lanczos" s = comfy.utils.common_upscale(samples, width, height, upscale_method, "disabled") image = s.movedim(1, -1) images = [image[:, :, :, :3]] output_image = image[:, :, :, :3] if vae is not None: ref_latent = vae.encode(image[:, :, :, :3]) tokens = clip.tokenize(prompt, images=images) conditioning = clip.encode_from_tokens_scheduled(tokens) if ref_latent is not None: conditioning = node_helpers.conditioning_set_values(conditioning, {"reference_latents": [ref_latent]}, append=True) latent_output = {"samples": ref_latent} if ref_latent is not None else None return (conditioning, output_image, latent_output) NODE_CLASS_MAPPINGS = { "TextEncodeQwenImageEdit": TextEncodeQwenImageEdit, }