anime2real2511-paulhe-v2.0

Yes! I trained another LoRA again. Although the previous LoRA already restored expressions quite well, this one has even better expression fidelity than the last LoRA. As for consistency, I think it ranks very highly among all real-life conversion LoRAs.

Feel free to test it out. I tested it on multiple ahegao images as well as some subtle micro-expressions. In most cases, the expressions can be restored very well with the LoRA alone. For a small number of images, you can try optimizing the prompt to achieve a better restoration.

Here, I used LLaMA to reverse-engineer the prompts and fed them into Qwen 2511. I simply added a prompt reverse-engineering module to the official example template. I am only providing the LoRA model here. If you need the workflow, you can also ask me. I may release the workflow later as well.

If you want better skin quality, you can connect it with Z-Image Turbo for image refinement. I should upload the related workflow to RunningHub, so you can try it there.

This LoRA was also trained on an RTX 5090, using 69 images for 7,500 training steps. Enjoy the power of the 5090!

trigger words:

transform into a real-life version. Strictly preserve the facial expression and pupil color, and strictly keep the hairstyle unchanged. with facial features like those of a real person. Make the skin more realistic, with fine peach fuzz. Keep the character’s proportions in the image unchanged. Strictly preserve the character’s expression and subtle detailed movements.

If you feel that the result generated with the official workflow alone is not accurate enough, you can try optimizing the prompt after my original prompt using the same sentence structure. However, it is best not to delete my original prompt. This is especially useful for images with subtle micro-expressions.

If you think the result is good, please follow and give it a like!

是的！我又练了一炉lora，虽然上一次lora表情已经比较还原，但是这次的表情还原性比上一个lora还要好一点，一致性我认为在所有的转真人lora里面也算是排很前的了。你们不妨测试一下，我测试了多个阿黑颜照片，还有一些微表情，绝大部分单靠lora就能很好还原，有一小部分可以尝试优化提示词来还原。这里我使用的是用llama反推提示词喂给qwen2511。而我只是在官方的示例模板里面加入了一组反推模块而已。这里我只提供lora模型，如果你们需要工作流，也可以向我询问，我可能后续也会发布工作流。

如果想要皮肤质量更好的话可以接zimageturbo进行洗图，相关工作流我应该会上传到runninghub上面，你们可以试试。

这次同样是使用rtx5090进行训练，使用69张图片进行7500步的训练，尽情享受5090的威力吧！

提示词：transform into a real-life version. Strictly preserve the facial expression and pupil color, and strictly keep the hairstyle unchanged. with facial features like those of a real person. Make the skin more realistic, with fine peach fuzz. Keep the character’s proportions in the image unchanged. Strictly preserve the character’s expression and subtle detailed movements.

如果觉得单纯用官方工作流生成的有一点点不还原，你可以尝试在我这个原来提示词后面用同样的句式优化提示词。但是注意最好不要把我原来的提示词删掉。这在一些微表情的图中尤其管用。

如果觉得效果不错就点一下关注和点赞吧！