This is the **next-level face-swap** specialized evolution of the **Dark Beast** lineage, built on the lightning-fast **FLUX.2 Klein 9B** accelerated model from **Black Forest Labs**. Engineered with targeted optimizations for face swapping practices, it integrates **BFS (Best Face Swap)** technology to completely eliminate the rigid, unnatural look that plagued earlier face replacements — delivering seamless, lifelike integrations with preserved identity, expression, and lighting. It also fully fixes the portrait reference issue from the previous **DB BlitZ** versions, ensuring right reference adherence every time.
This repository provides a ControlNet that supports mask-based image inpainting and outpainting for Qwen-Image. ComfyUI offers native support for Qwen-Image-ControlNet-Inpainting. The official workflow can be found here. Make sure your ComfyUI version is >=0.3.59. Liblib AI offers native support for Qwen-Image-ControlNet-Inpainting. Visit for online WebUI or ComfyUI inference.
This repository provides a unified ControlNet that supports 4 common control types (canny, soft edge, depth, pose) for Qwen-Image. - This ControlNet consists of 5 double blocks copied from the pretrained transformer layers. - We train the model from scratch for 50K steps using a dataset of 10M high-quality general and human images. - We train at 1328x1328 resolution in BFloat16, batch size=64, learning rate=4e-5. We set the text drop ratio to 0.10. - This model supports multiple control modes, including canny, soft edge, depth, pose. You can use it just as a normal ControlNet. You can adjust control strength via controlnet_conditioning_scale. - Canny: use cv2.Canny, set controlnet_conditioning_scale in [0.8, 1.0] - Soft Edge: use AnylineDetector, set controlnet_conditioning_scale in [0.8, 1.0] - Depth: use depth-anything, set controlnet_conditioning_scale in [0.8, 1.0] - Pose: use DWPose, set controlnet_conditioning_scale in [0.8, 1.0]
JoyAI-Image-Edit Awakening Spatial Intelligence in Unified Multimodal Understanding and Generation JoyAI-Image-Edit is a multimodal foundation model specialized in instruction-guided image editing. It enables precise and controllable edits by leveraging strong spatial understanding, including scene parsing, relational grounding, and instruction decomposition, allowing complex modifications to be applied accurately to specified regions. Note: JoyImageEditPipeline will be included in the next official diffusers release (>0.38.0). Until then, install from source as shown above.
