<h1 id="yaae-or-yet-another-anima-edit">YAAE | Yet Another Anima Edit</h1>As the title implies, this is not the first Anima Edit model and mostly a proof-of-concept test of a diffusion-pipe update to <a target="_blank" rel="ugc" href="https://github.com/tdrussell/diffusion-pipe/commit/928bd6c866035ee7040bc39cf1f358abd1008b20">Support Anima Edit Training</a> as of the current version.Version 0.1Used 984 source-target image pairs subset of the <a target="_blank" rel="ugc" href="https://huggingface.co/datasets/iitolstykh/NHR-Edit">NHR-Edit</a> synthetic dataset. Trained at 512, 768, 1024 resolutions, input images should not exceed 1024 for best results.Can use a resize node to ensure this on input images in ComfyUI as I have in the preview workflows. Target edit tasks, 90 image pairs each:<ul><li>Add Background</li><li>Add Object</li><li>Change Background</li><li>Change Color</li><li>Change Object</li><li>Remove Background</li><li>Remove Object</li></ul>And mixed 354 images of all categories in the "anime" style.The "augmented_instructions" column from the dataset is used for the target captions.The dataset for this proof-of-concept version consists of synthetic Flux outputs, which isn't very compatible with the anime focus of Anima.<h2 id="usage">Usage</h2>As far as I know, generation providers do not support Anima Edit workflows for online generation, so this LoRA is only usable in local generation with ComfyUI or Forge Neo.The basic idea is to take an input image and run img2img generation with a prompt that contains your edit instruction.Ideally the edit instruction should fall under one of the categories that were explicitly trained for this LoRA (see version details), but the model is capable of some level of generalization.ComfyUIThe <a target="_blank" rel="ugc" href="https://github.com/Mirumo0u0/ComfyUI-Cosmos-Reference">ComfyUI-Cosmos-Reference</a> custom node is required to use the workflow.The workflow is included in the preview images, you can download the images and drag them into ComfyUI.Forge Neo<a target="_blank" rel="ugc" href="https://github.com/Haoming02/sd-webui-forge-classic/tree/neo">Forge Neo</a> also supports cosmos reference natively, so you can use this LoRA in the img2img tab. (Make sure to enable it in Settings-&gt;Stable Diffusion)PromptingUse Natural Language for the edit instructions, some examples:"Add a blue background.""Add a glowing white rabbit on the right side.""Switch the background from a snowy pine forest to an icy mountain vista.""Change the blue hair color to white.""Replace the flowing sundress with a black blazer.""Remove the crowd of people."Tags can be included with the Natural Language instruction and help avoid the Flux style influence somewhat, recommend including at least the quality modifier tags: "masterpiece, best quality"<h2 id="citations">Citations</h2><pre><code>@article{Layer2025NoHumansRequired,
 arxivId = {2507.14119},
 author = {Maksim Kuprashevich and Grigorii Alekseenko and Irina Tolstykh and Georgii Fedorov and Bulat Suleimanov and Vladimir Dokholyan and Aleksandr Gordeev},
 title = {{NoHumansRequired: Autonomous High-Quality Image Editing Triplet Mining}},
 year = {2025},
 eprint = {2507.14119},
 archivePrefix = {arXiv},
 primaryClass = {cs.CV},
 url = {https://arxiv.org/abs/2507.14119},
 journal={arXiv preprint arXiv:2507.14119}
}</code></pre>

YAAE | Yet Another Anima Edit

Version 0.1Used 984 source-target image pairs subset of the <a target="_blank" rel="ugc" href="https://huggingface.co/datasets/iitolstykh/NHR-Edit">NHR-Edit</a> synthetic dataset. Target edit tasks, 90 image pairs each:<ul><li>Add Background</li><li>Add Object</li><li>Change Background</li><li>Change Color</li><li>Change Object</li><li>Remove Background</li><li>Remove Object</li></ul>And mixed 354 images of all Categories in the "anime" style.The "augmented_instructions" column from the dataset is used for the target captions.The dataset for this proof-of-concept version consists of synthetic Flux outputs, which isn't very compatible with the anime focus of Anima.

Files with SHA256: 7dba0dbb3bf0d73b24605dd06073598d83caba9455b09df7e1deb6977499407e