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Feature/qwen eligen support #10473
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Feature/qwen eligen support #10473
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Hey @nolan4 thank you so much for this amazing work! I am trying to test this out but not able to run it, I am using this PR and using the Eligen Lora provided by Diffsynth Studio and using this workflow, please check. |
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hey @nolan4 may you please reply? |
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Hi @krigeta — here’s a screenshot of my workflow, which is based on the Qwen text-to-image template. I’m also using the same EliGen LoRA from Diffsynth Studio that you linked. Hope this helps you get it running! |
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Hey @nolan4 thank you so much for this, what if this branch is not merged then is it possible to create a custom node of this? and yeah i will test this and share the results for sure. |
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hey @nolan4 it is not working in my case, please check. |
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test locally and works, comfy will do a code review to see if anything else needs to be changed! |
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Hey @nolan4, I guess this implementation is missing the colour-coded masks that help the lora to differentiate between the regions when they overlap. Please look into it. |
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btw something similar was implemented in the Inspire Pack called "regional conditioning by color masks" in case you need inspiration or code |
comfy-cli --workspace ./ComfyUI_eligen install --pr "#10473"
comfy-cli --workspace ./ComfyUI_eligen launch |
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Hey @geroldmeisinger , thank you so much for the share, is there any other social media where we can chat? |
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here are the original masks https://www.modelscope.cn/datasets/DiffSynth-Studio/examples_in_diffsynth/files |
These are the ones I got to know about Eligen. In my case, the overlapped masking is not working properly, as I want to create two characters in front of each other, and the view is from the back. Or I would say I use one entity for a character and another for another character, and with ControlNet? Does it work? And if possible, may you share your Discord or other social app? |











Pull Request: Add Entity-Level Image Generation (EliGen) for Qwen Image
Summary
This update implements Entity-Level Image Generation (EliGen) for the Qwen Image model, allowing region-specific prompts through spatial masks. The feature provides fine-grained control over image generation by applying separate attention masks for each entity.
Key Features
• Spatial attention masking with isolated entity prompts
• Automatic mask resizing to match latent dimensions
• RoPE embedding implementation aligned with DiffSynth Studio
• Support for batch_size > 1
• Backward compatible with standard Qwen Image workflows