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Qwen-Image-2512-Fun-Controlnet-Union.safetensors

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README.md

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 ---
 license: apache-2.0
 ---
+# Qwen-Image-2512-Fun-Controlnet-Union
+
+[![Github](https://img.shields.io/badge/🎬%20Code-VideoX_Fun-blue)](https://github.com/aigc-apps/VideoX-Fun)
+
+## Model Features
+- This ControlNet is added on 5 layer blocks. It supports multiple control conditions—including Canny, HED, Depth, Pose, MLSD and Scribble. 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 0.65 to 1.00. 
+
+## Results
+<table border="0" style="width: 100%; text-align: left; margin-top: 20px;">
+  <tr>
+    <td>Pose + Inpaint</td>
+    <td>Output</td>
+  </tr>
+  <tr>
+    <td><img src="asset/inpaint.jpg" width="100%" /><img src="asset/mask.jpg" width="100%" /><img src="asset/pose.jpg" width="100%" /></td>
+    <td><img src="results/pose_inpaint.png" width="100%" /></td>
+  </tr>
+</table>
+
+<table border="0" style="width: 100%; text-align: left; margin-top: 20px;">
+  <tr>
+    <td>Pose</td>
+    <td>Output</td>
+  </tr>
+  <tr>
+    <td><img src="asset/pose2.jpg" width="100%" /></td>
+    <td><img src="results/pose2.png" width="100%" /></td>
+  </tr>
+</table>
+
+<table border="0" style="width: 100%; text-align: left; margin-top: 20px;">
+  <tr>
+    <td>Pose</td>
+    <td>Output</td>
+  </tr>
+  <tr>
+    <td><img src="asset/pose.jpg" width="100%" /></td>
+    <td><img src="results/pose.png" width="100%" /></td>
+  </tr>
+</table>
+
+<table border="0" style="width: 100%; text-align: left; margin-top: 20px;">
+  <tr>
+    <td>Scribble</td>
+    <td>Output</td>
+  </tr>
+  <tr>
+    <td><img src="asset/scribble.jpg" width="100%" /></td>
+    <td><img src="results/scribble.png" width="100%" /></td>
+  </tr>
+</table>
+
+<table border="0" style="width: 100%; text-align: left; margin-top: 20px;">
+  <tr>
+    <td>Canny</td>
+    <td>Output</td>
+  </tr>
+  <tr>
+    <td><img src="asset/canny.jpg" width="100%" /></td>
+    <td><img src="results/canny.png" width="100%" /></td>
+  </tr>
+</table>
+
+<table border="0" style="width: 100%; text-align: left; margin-top: 20px;">
+  <tr>
+    <td>HED</td>
+    <td>Output</td>
+  </tr>
+  <tr>
+    <td><img src="asset/hed.jpg" width="100%" /></td>
+    <td><img src="results/hed.png" width="100%" /></td>
+  </tr>
+</table>
+
+<table border="0" style="width: 100%; text-align: left; margin-top: 20px;">
+  <tr>
+    <td>Depth</td>
+    <td>Output</td>
+  </tr>
+  <tr>
+    <td><img src="asset/depth.jpg" width="100%" /></td>
+    <td><img src="results/depth.png" width="100%" /></td>
+  </tr>
+</table>
+
+## Inference
+Go to the VideoX-Fun repository for more details.
+
+Please clone the VideoX-Fun repository and create the required directories:
+
+```sh
+# 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.
+
+```
+📦 models/
+├── 📂 Diffusion_Transformer/
+│   └── 📂 Qwen-Image-2512/
+├── 📂 Personalized_Model/
+│   └── 📦 Qwen-Image-2512-Fun-Controlnet-Union.safetensors
+```
+
+Then run the file `examples/qwenimage_fun/predict_t2i_control.py` and `examples/qwenimage_fun/predict_i2i_inpaint.py`.