<h1 id="object-removal-lora-of-flux-fill-dev-v2-lxevhn4gf">Object Removal LoRA of Flux Fill Dev v2</h1>Update 20250517Released Remove Anything v1.0 on runninghub.<a target="_blank" rel="ugc" href="https://www.runninghub.ai/ai-detail/1923389726278283265">https://www.runninghub.ai/ai-detail/1923389726278283265</a>I could say much better than Object Removal LoRA v2and it is stronger than many closed source platform on object removal.<img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/3a48b6a4-9ef3-4010-baf7-0ec5d7c8427b/width=525/3a48b6a4-9ef3-4010-baf7-0ec5d7c8427b.jpeg" />bmm 4300 is Remove Anything v1.0Update 20250503Released v2 for object removalUsing new training method, select training objective by timestep, 700Trained on subset of RORD datasetDataset around 500epoch 3repeat 1rank 16lr 1e-4The last image in demo example is experimental and it introduces artifacts. So, the 700 reg 0.5 is deprecated.Update 20240320Released v1 for object removalAbout this versionTrained with larger dataset.Merged with additional inpaint training to improve details texture.Known Issue:Due to the training dataset mostly is to remove human, when removing part of human,the model would tends to remove the human part from the image.It is better to use original fill to accomplish this type of removal.Update 20250316Upload a more trained file.It seems longer training improve the generalization.Update 20250314 Adding random selection training for beta. It ranfom selects noised factual or noised ground true to train. It is able to prevent the model degradation due to mis-aligned training objective.Trainer:<a target="_blank" rel="ugc" href="https://github.com/lrzjason/T2ITrainer">https://github.com/lrzjason/T2ITrainer</a>Dataset:<a target="_blank" rel="ugc" href="https://huggingface.co/datasets/lrzjason/ObjectRemovalAlpha">lrzjason/ObjectRemovalFluxFill</a>You could download the lora from huggingface without waiting. This EA is only to support me for further more open source development<a target="_blank" rel="ugc" href="https://huggingface.co/lrzjason/ObjectRemovalFluxFill">https://huggingface.co/lrzjason/ObjectRemovalFluxFill</a><h2 id="model-description-luuksqz81">Model Description</h2>This is an Object Removal LoRA fine-tuned from Flux Fill Dev model.The lora is designed to remove objects from specified masked areas, making it useful for image editing tasks where unwanted objects need to be erased seamlessly.This lora is inspired by <a target="_blank" rel="ugc" href="https://objectdrop.github.io/">Object Drop</a>. Object Drop achieved amazing result on removing objects and I want to try it with Flux fill model.Due to the computing power limitation, this alpha version only trained on very small dataset.If anyone interested in and want to sponsor the computing power, please contact me.<h3 id="intended-use-vy6o1b0b9">Intended Use</h3>This model is intended for non-commercial use only, as per the FLUX.1 [dev] Non-Commercial License.<h3 id="limitations-8hg8qmtel">Limitations</h3>Non-Commercial Use Only: This model is restricted to non-commercial applications. Any commercial use is prohibited under the FLUX.1 [dev] Non-Commercial License.Large Masked Area: The model may struggle with large masked area.<h3 id="how-to-use-36p1m0ljx">How to Use</h3>To use this model, you need to provide an image and a corresponding mask indicating the area where the object should be removed. The model will then generate an edited image with the object removed.Using Flux Fill as base model and load the lora.<h2 id="training-data-bymfr5idr">Training Data</h2>The model was fine-tuned on a small dataset of images with corresponding masks, focusing on object removal tasks. The dataset includes various objects and scenes to ensure robust performance.<h3 id="license-5edo0cnpd">License</h3>This model is licensed under the [FLUX.1 [dev] Non-Commercial License](<a target="_blank" rel="ugc" href="https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md">https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md</a>). You are free to use, modify, and distribute the model for non-commercial purposes. Commercial use is strictly prohibited.<h3 id="citation-7okmbu5eg">Citation</h3>If you use this model in your research or projects, please cite it as follows:```bibtex@misc{object-removal-lora,author = {lrzjason},title = {Object Removal LoRA of Flux Fill Dev},year = {2025}}```<h3 id="contact-140g3skjc">Contact</h3>Twitter: [@Lrzjason](<a target="_blank" rel="ugc" href="https://twitter.com/Lrzjason">https://twitter.com/Lrzjason</a>)Email: <a target="_blank" rel="ugc" href="mailto:lrzjason@gmail.com">lrzjason@gmail.com</a>QQ Group: 866612947Civitai: [xiaozhijason](<a target="_blank" rel="ugc" href="https://civarchive.com/user/xiaozhijason">https://civarchive.com/user/xiaozhijason</a>)Wechat: fkdeai<h3 id="sponsors-me-for-more-open-source-projects:-uszm0v6r0">Sponsors me for more open source projects:</h3>Buymeacoffee:<img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/377f3970-d214-462c-8ba3-a2c8f03830f5/width=525/377f3970-d214-462c-8ba3-a2c8f03830f5.jpeg" />Wechat:<img src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/aaea97bf-c7ae-4f3a-b70b-f7fee6a81564/width=525/aaea97bf-c7ae-4f3a-b70b-f7fee6a81564.jpeg" />Disclaimer: This model is provided "as-is" without any warranties. The authors are not responsible for any misuse or damages arising from its use.

Object Removal Flux Fill v2

Trained with new method.Use timestep to select training objective.<a target="_blank" rel="ugc" href="https://github.com/lrzjason/T2ITrainer">https://github.com/lrzjason/T2ITrainer</a>

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