Update 2602

Qwen-Image-2512-Fun-Controlnet-Union-2602.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0d1ac366efaa27dec070b3a8ebe9a41b5ebc567913dee71ed992e7032f66dc37
+size 3512432536

README.md

@@ -7,8 +7,15 @@ library_name: videox_fun
 
 [![Github](https://img.shields.io/badge/🎬%20Code-VideoX_Fun-blue)](https://github.com/aigc-apps/VideoX-Fun)
 
+## Model Card
+
+| Name | Description |
+|--|--|
+| 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. |
+| 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 and Scribble. It can be used like a standard ControlNet. 
+- 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. 
@@ -91,6 +98,17 @@ library_name: videox_fun
   </tr>
 </table>
 
+<table border="0" style="width: 100%; text-align: left; margin-top: 20px;">
+  <tr>
+    <td>Gray</td>
+    <td>Output</td>
+  </tr>
+  <tr>
+    <td><img src="asset/gray.jpg" width="100%" /></td>
+    <td><img src="results/gray.png" width="100%" /></td>
+  </tr>
+</table>
+
 ## Inference
 Go to the VideoX-Fun repository for more details.
 
@@ -118,4 +136,4 @@ Then download the weights into models/Diffusion_Transformer and models/Personali
 │   └── 📦 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`.
+Then run the file `examples/qwenimage_fun/predict_t2i_control.py` and `examples/qwenimage_fun/predict_i2i_inpaint.py`.