什么是线稿上色？
这是给线稿上色的任务。
对于已经能自己画线稿的人来说，比起从 0 开始的 text2image，也许“如何让 AI 给自己的线稿上色”往往更重要。
使用 ControlNet 进行线稿上色
如果使用 ControlNet Canny（edge），就可以在保持输入线稿大致原貌的情况下，在那里上色。
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将线稿（或边缘提取结果）传递给 ControlNet，用文本提示词指定服装、颜色和氛围。
基于指令的图像编辑进行的线稿上色
也可以将线稿原样传递给 基于指令的图像编辑 模型让其上色。
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只需将线稿作为输入图像，然后用文本指示“把这个线稿涂成全彩”、“用动画涂法上色”等即可。
基于参考的上色（线稿＋彩色图像）
如果是“想用和这个角色相同的配色涂这个线稿”、“想借用这张画的用色”的情况，可以使用基于参考的上色。
用 ControlNet（lineart / anime 等）固定线稿的形状・构图，用 IP-Adapter 等参考图像适配器传递彩色插图或照片，使其配色、质感、画风接近。
即使是基于指令的图像编辑模型，如果支持多参考，也可以指定“希望参考图像 2 给图像 1 的线稿上色”。
闲话
实际画师的工作流，是“底色 → 阴影 → 完稿”这样，稍微多一些步骤的。
不限于着色，AI 虽然擅长突然制作出成品，但不太擅长像人类一样循序渐进地画画。
我是日本人所以多少有点偏心，从像 Copainter 这样的商业服务到社区的 LoRA，在日本这类研究・实现相当盛行。