Enhance model card with pipeline tag, paper, project, and code links (#1)

- Enhance model card with pipeline tag, paper, project, and code links (5c1476c7250111adf51f685c5f60a665371929ea)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -1,3 +1,87 @@
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-license: cc-by-nc-sa-4.0
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+---
+license: cc-by-nc-sa-4.0
+pipeline_tag: image-to-image
+---
+
+# 🪶 MagicQuill V2: Precise and Interactive Image Editing with Layered Visual Cues
+
+- **Paper:** [MagicQuillV2: Precise and Interactive Image Editing with Layered Visual Cues](https://huggingface.co/papers/2512.03046)
+- **Project Page:** https://magicquill.art/v2/
+- **Code Repository:** https://github.com/zliucz/MagicQuillV2
+- **Hugging Face Spaces Demo:** https://huggingface.co/spaces/AI4Editing/MagicQuillV2
+
+<br>
+
+<div align="center">
+  <video src="https://github.com/user-attachments/assets/58079152-7729-48ed-9bb4-0ddfd1873dd0" width="100%" controls autoplay muted loop></video>
+</div>
+
+<br>
+
+**TLDR:** MagicQuill V2 introduces a layered composition paradigm to generative image editing, disentangling creative intent into controllable visual cues (Content, Spatial, Structural, Color) for precise and intuitive control.
+
+## Hardware Requirements
+
+Our model is based on Flux Kontext, which is large and computationally intensive.
+- **VRAM**: Approximately **40GB** of VRAM is required for inference.
+- **Speed**: It takes about **30 seconds** to generate a single image.
+
+> **Important**: This is a research project focused on pushing the boundaries of interactive image editing. If you do not have sufficient GPU memory, we recommend checking out our [**MagicQuill V1**](https://github.com/ant-research/MagicQuill) or trying the online demo on [**Hugging Face Spaces**](https://huggingface.co/spaces/AI4Editing/MagicQuillV2).
+
+## Setup
+
+1.  **Clone the repository**
+    ```bash
+    git clone https://github.com/magic-quill/MagicQuillV2.git
+    cd MagicQuillV2
+    ```
+
+2.  **Create environment**
+    ```bash
+    conda create -n MagicQuillV2 python=3.10 -y
+    conda activate MagicQuillV2
+    ```
+
+3.  **Install dependencies**
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+4.  **Download models**
+    Download the models from [Hugging Face](https://huggingface.co/LiuZichen/MagicQuillV2-models) and place them in the `models/` directory.
+
+    ```bash
+    huggingface-cli download LiuZichen/MagicQuillV2-models --local-dir models
+    ```
+
+5.  **Run the demo**
+    ```bash
+    python app.py
+    ```
+
+## System Overview
+
+The MagicQuill V2 interactive system is designed to unify our layered composition framework.
+
+<div align="center">
+  <img src="https://github.com/zliucz/MagicQuillV2/raw/main/assets/V2_UI.png" alt="MagicQuill V2 UI" width="100%">
+</div>
+
+### Key Upgrades from V1
+
+1.  **Toolbar (A)**: Features a new **Local Edit Brush** for defining the target editing area, along with tools for sketching edges and applying color.
+2.  **Visual Cue Manager (B)**: Holds all content layer visual cues (**foreground props**) that users can drag onto the canvas to define what to generate.
+3.  **Image Segmentation Panel (C)**: Accessed via the segment icon, this panel allows precise object extraction using SAM (Segment Anything Model) with positive/negative dots or bounding boxes.
+
+## Citation
+
+If you find MagicQuill V2 useful for your research, please cite our paper:
+
+```bibtex
+@article{liu2025magicquillv2,
+  title={MagicQuill V2: Precise and Interactive Image Editing with Layered Visual Cues},
+  author={Zichen Liu, Yue Yu, Hao Ouyang, Qiuyu Wang, Shuailei Ma, Ka Leong Cheng, Wen Wang, Qingyan Bai, Yuxuan Zhang, Yanhong Zeng, Yixuan Li, Xing Zhu, Yujun Shen, Qifeng Chen},
+  journal={arXiv:2512.03046},
+  year={2025}
+}
+```