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Qwen-Image-2512-Fun-Controlnet-Union
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Mirrored
Qwen-Image-2512-Fun-Controlnet-Union-2602.safetensors Compared to the previous version of the model, we added Gray control to the model. The model was trained for a longer time than before.
Compared to the previous version of the model, we added Gray control to the model. The model was trained for a longer time than before.
Qwen-Image-2512-Fun-Controlnet-Union.safetensors
ControlNet weights for Qwen-Image-2512. The model supports multiple control conditions such as Canny, HED, Depth, Pose, MLSD and Scribble.
Model Features
This ControlNet is added on 5 layer blocks. It supports multiple control conditions—including Canny, HED, Depth, Pose, MLSD, Scribble and Gray. It can be used like a standard ControlNet.
Inpainting mode is also supported.
When obtaining control images, acquiring them in a multi-resolution manner results in better generalization.
You can adjust control_context_scale for stronger control and better detail preservation. For better stability, we highly recommend using a detailed prompt. The optimal range for control_context_scale is from 0.70 to 0.95.
Results
Pose + Inpaint
Output
Pose
Output
Pose
Output
Scribble
Output
Canny
Output
HED
Output
Depth
Output
Gray
Output
Inference
Go to the VideoX-Fun repository for more details.
Please clone the VideoX-Fun repository and create the required directories:
# Clone the code
git clone https://github.com/aigc-apps/VideoX-Fun.git
# Enter VideoX-Fun's directory
cd VideoX-Fun
# Create model directories
mkdir -p models/Diffusion_Transformer
mkdir -p models/Personalized_Model
Then download the weights into models/Diffusion_Transformer and models/Personalized_Model.