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In the field of AI art generation, diffusion models are transitioning from U-Net based architectures to Transformer-based architectures (DiT). However, the DiT ecosystem faces challenges in plugin support, efficiency, and multi-conditional control. Recently, a team led by Xiaojiu-z introduced EasyControl, an innovative framework designed to provide efficient and flexible conditional control capabilities for DiT models, effectively giving DiT models the power of ControlNet.

FLUX-Controlnet-Inpainting, an image repair tool based on ControlNet and FLUX.1-dev, is redefining our understanding of image restoration. This tool not only inherits the high-quality image generation capabilities of the FLUX.1-dev model but also cleverly integrates the strengths of ControlNet. It can accurately repair images based on information from edges, sketches, depth maps, etc., generating content that harmonizes with the surrounding environment in specified areas.

ComfyUI version 0.2.0 introduces Flux ControlNets technology, including Canny and Union control nets, significantly enhancing image processing capabilities. The optimized queue management features, new 'Go-to Node' for quick navigation, 'Contain' image display, and task output folder view, greatly improve work efficiency. Enhanced node library functionalities such as bookmarks, recursive expand/collapse, and search filters make resource management easier. The user interface and experience have been completely revamped.

"The 'Online FLUX' by fal.ai offers a revolutionary experience for drawing enthusiasts, introducing ControlNet and LoRA features that are ready to use out of the box without complex configurations. ControlNet simplifies modifying characters' expressions or controlling scene objects; the LoRA model supports online training, allowing users to customize and share models, promoting creative diffusion. This platform integrates with third-party functionalities, making drawing more flexible and personalized, supporting various styles from cyberpunk to Chinese aesthetics. The usability of the Online FLUX is profound."

Tencent's Hunyuan DiT model has recently partnered with the community to release three new controllable plugins for ControlNet: tile (high-definition image enlargement), inpainting (image restoration and expansion), and lineart (line art generation), further expanding its ControlNet matrix. The addition of these plugins enables the Hunyuan DiT model to cover a wider range of application scenarios.

Recently, Xinsir has released a brand new open-source model called Controlnet++, which can control over a dozen conditions through a single network. Specifically, Controlnet++ supports inputs such as Openpose and Canny, thus avoiding the hassle of frequently switching models.Based on the ControlNet architecture, Controlnet++ supports over ten different control types through additional modules, designed for text-to-image generation and editing. This model can generate high-resolution images with

Tencent's MetaGen Image Generation Large Model (Hunyuan DiT) has recently been upgraded to a 6GB VRAM version, making it easy for personal computer users to run. This version is compatible with plugins such as LoRA and ControlNet and has added support for the Kohya graphical user interface, lowering the threshold for developers to train personalized LoRA models. The Hunyuan DiT model has been upgraded to version 1.2, with improvements in image texture and composition.At the same time, Tencent ha

Tencent's Hunyuan DiT model has announced the full open-sourcing of its training code, including LoRA and ControlNet plugins. LoRA is a technique for fine-tuning large language models that allows training models with specific characteristics using a small amount of data, without modifying the original model or increasing its size.

Recently, the independent research organization InstantX, focused on AI content generation, released multiple SD3 ControlNet models, including Canny, Pose, Inpaint, and others.

{title:The Popular 'Video Version of ControlNet' is Open Source! Precisely Change Art Styles with Prompt Words, Created by a Fully Chinese Team list: The latest video processing algorithm CoDeF, developed by a fully Chinese team, has rapidly gone viral online after its release. CoDeF can precisely control the art style of videos based on prompt words while maintaining lip sync. CoDeF achieves video style transfer tasks through content deformation fields and possesses good cross-frame consistency}