mirror of
https://github.com/comfyanonymous/ComfyUI.git
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cc1c5da4f6
- Implement automatic algorithm selection: area for downscaling, lanczos for upscaling - Improve image quality by choosing optimal scaling method based on target size - Add Chinese comments for better code documentation - Ensure 8-pixel alignment for better compatibility with diffusion models
69 lines
2.4 KiB
Python
69 lines
2.4 KiB
Python
import node_helpers
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import comfy.utils
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import math
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class TextEncodeQwenImageEdit:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {
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"clip": ("CLIP", ),
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"prompt": ("STRING", {"multiline": True, "dynamicPrompts": True}),
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},
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"optional": {"vae": ("VAE", ),
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"image": ("IMAGE", ),}}
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RETURN_TYPES = ("CONDITIONING", "IMAGE", "LATENT")
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FUNCTION = "encode"
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CATEGORY = "advanced/conditioning"
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def encode(self, clip, prompt, vae=None, image=None):
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ref_latent = None
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output_image = None
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if image is None:
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images = []
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else:
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samples = image.movedim(-1, 1)
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total = int(1024 * 1024)
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scale_by = math.sqrt(total / (samples.shape[3] * samples.shape[2]))
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# 修改缩放规则：乘数为8，向下取整
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width = math.floor(samples.shape[3] * scale_by / 8) * 8
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height = math.floor(samples.shape[2] * scale_by / 8) * 8
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# 根据缩放比例选择算法：缩小用area，放大用lanczos
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original_width = samples.shape[3]
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original_height = samples.shape[2]
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if width < original_width or height < original_height:
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# 缩小图像，使用area算法保持细节
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upscale_method = "area"
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else:
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# 放大图像，使用lanczos算法获得更好质量
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upscale_method = "lanczos"
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s = comfy.utils.common_upscale(samples, width, height, upscale_method, "disabled")
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image = s.movedim(1, -1)
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images = [image[:, :, :, :3]]
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output_image = image[:, :, :, :3]
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if vae is not None:
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ref_latent = vae.encode(image[:, :, :, :3])
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tokens = clip.tokenize(prompt, images=images)
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conditioning = clip.encode_from_tokens_scheduled(tokens)
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if ref_latent is not None:
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conditioning = node_helpers.conditioning_set_values(conditioning, {"reference_latents": [ref_latent]}, append=True)
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# 将ref_latent包装成ComfyUI LATENT类型要求的格式
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latent_output = {"samples": ref_latent} if ref_latent is not None else None
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return (conditioning, output_image, latent_output)
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NODE_CLASS_MAPPINGS = {
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"TextEncodeQwenImageEdit": TextEncodeQwenImageEdit,
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}
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