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Update app.py

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@@ -18,54 +18,10 @@ default_steps = 30
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  GUIDANCE = """
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-
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  ### [πŸ’₯ New] πŸ‘‹πŸ‘‹πŸ‘‹ We release the <a href="https://github.com/lzyhha/diffusers/tree/main/src/diffusers/pipelines/visualcloze" target="_blank"><span style="color:rgb(253, 60, 94);"><em><strong>diffusers</strong></em></span></a> implementation that makes it easier to use the model through pipelines. See <a href="https://huggingface.co/VisualCloze/VisualClozePipeline-384" target="_blank">Model Card</a> for details.
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-
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- ## πŸ“‹ Quick Start Guide:
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- 1. Adjust **Number of In-context Examples**, 0 disables in-context learning.
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- 2. Set **Task Columns**, the number of images involved in a task.
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- 3. Upload Images. For in-context examples, upload all images. For the current query, upload images exclude the target.
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- 4. Click **Generate** to create the images.
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- 5. Parameters can be fine-tuned under **Advanced Options**.
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-
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- ## πŸ”₯ Task Examples:
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- Click the task button in the right bottom to acquire **examples** of various tasks.
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- Each click on a task may result in different examples.
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- **Make sure all images and prompts are loaded before clicking the generate button.**
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-
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-
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- ## πŸ’» Runtime on the Zero GPU:
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- The runtime on the Zero GPU runtime depends on the size of the image grid.
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- When generating an image with the resoluation of 1024,
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- the runtime is approximately **[45s for a 2x2 grid], [55s for a 2x3 grid], [70s for a 3x3 grid], [90s for a 3x4 grid]**.
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- **Deploying locally with an 80G A100 can reduce the runtime by more than half.**
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- Disabling SDEdit upsampling by setting the upsampling noise to 1 or reducing the upsampling steps
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- can also save computation time, but it may lead to a decrease in generation quality.
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-
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- ### Note: For better quality, you can deploy the demo locally using the [model](https://huggingface.co/VisualCloze/VisualCloze/blob/main/visualcloze-512-lora.pth), which supports a higher resolution than this online demo, by following the instructions in the [GitHub repository](https://github.com/lzyhha/VisualCloze/tree/main?tab=readme-ov-file#2-web-demo-gradio).
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- """
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-
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- CITATION = r"""
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- If you find VisualCloze is helpful, please consider to star ⭐ the <a href='https://github.com/lzyhha/VisualCloze' target='_blank'>Github Repo</a>. Thanks!
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- ---
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- πŸ“ **Citation**
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- <br>
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- If our work is useful for your research, please consider citing:
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- ```bibtex
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- @article{li2025visualcloze,
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- title={VisualCloze: A Universal Image Generation Framework via Visual In-Context Learning},
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- author={Li, Zhong-Yu and Du, ruoyi and Yan, Juncheng and Zhuo, Le and Li, Zhen and Gao, Peng and Ma, Zhanyu and Cheng, Ming-Ming},
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- journal={arXiv preprint arXiv:2504.07960},
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- year={2025}
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- }
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- ```
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  πŸ“‹ **License**
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  <br>
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  This project is licensed under apache-2.0.
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-
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- πŸ“§ **Contact**
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- <br>
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- Need help or have questions? Contact us at: lizhongyu [AT] mail.nankai.edu.cn.
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  """
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  NOTE = r"""
 
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  GUIDANCE = """
 
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  ### [πŸ’₯ New] πŸ‘‹πŸ‘‹πŸ‘‹ We release the <a href="https://github.com/lzyhha/diffusers/tree/main/src/diffusers/pipelines/visualcloze" target="_blank"><span style="color:rgb(253, 60, 94);"><em><strong>diffusers</strong></em></span></a> implementation that makes it easier to use the model through pipelines. See <a href="https://huggingface.co/VisualCloze/VisualClozePipeline-384" target="_blank">Model Card</a> for details.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  πŸ“‹ **License**
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  <br>
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  This project is licensed under apache-2.0.
 
 
 
 
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  """
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  NOTE = r"""