Improve model card for Lego-Edit: Add metadata, links, abstract, and usage

README.md

@@ -1,3 +1,235 @@
----
-license: apache-2.0
----
+---
+license: cc-by-nc-4.0
+pipeline_tag: image-to-image
+library_name: transformers
+tags:
+- vision-language
+- image-editing
+- multimodal
+- qwen2_5
+---
+
+<p align="center">
+  <img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/lego_pic.png" alt="Lego-Edit" width="240"/>
+</p>
+
+<p align="center">
+  <a href="https://xiaomi-research.github.io/lego-edit/">
+    <img
+      src="https://img.shields.io/static/v1?label=Project%20Page&message=Web&color=green"
+      alt="Lego-Edit Website"
+    />
+  </a>
+  <a href="https://huggingface.co/papers/2509.12883">
+    <img
+      src="https://img.shields.io/static/v1?label=Paper&message=HuggingFace&color=red"
+      alt="Lego-Edit Paper on arXiv"
+    />
+  </a>
+  <a href="https://github.com/xiaomi-research/lego-edit">
+    <img 
+        src="https://img.shields.io/static/v1?label=Code&message=GitHub&color=blue" 
+        alt="Lego-Edit Github"
+    />
+  </a>
+  <a href="https://editdemo.ai.xiaomi.net/">
+    <img
+      src="https://img.shields.io/badge/Demo-Live-orange"
+      alt="Lego-Edit Demo"
+    />
+  </a>
+</p>
+
+# Lego-Edit: A General Image Editing Framework with Model-Level Bricks and MLLM Builder
+
+Instruction-based image editing has garnered significant attention due to its direct interaction with users. However, real-world user instructions are immensely diverse, and existing methods often fail to generalize effectively to instructions outside their training domain, limiting their practical application. To address this, we propose Lego-Edit, which leverages the generalization capability of Multi-modal Large Language Model (MLLM) to organize a suite of model-level editing tools to tackle this challenge. Lego-Edit incorporates two key designs: (1) a model-level toolkit comprising diverse models efficiently trained on limited data and several image manipulation functions, enabling fine-grained composition of editing actions by the MLLM; and (2) a three-stage progressive reinforcement learning approach that uses feedback on unannotated, open-domain instructions to train the MLLM, equipping it with generalized reasoning capabilities for handling real-world instructions. Experiments demonstrate that Lego-Edit achieves state-of-the-art performance on GEdit-Bench and ImgBench. It exhibits robust reasoning capabilities for open-domain instructions and can utilize newly introduced editing tools without additional fine-tuning. The figure below showcases Lego-Edit's qualitative performance.
+
+<p align="center"><img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/case_pic.png" width="95%"></p>
+
+## ✨ Features
+
+Lego-Edit supports local editing, global editing, and multi-step editing as demonstrated in our tests, with corresponding results shown above. We discuss its feedback responsiveness and tool-extension capabilities in our paper.
+
+Additionally, Lego-Edit accepts mask inputs for precise editing region control. Example applications are provided here:
+
+<p align="center"><img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/maskcase1.png" width="95%"></p>
+
+<p align="center"><img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/maskcase2.png" width="95%"></p>
+
+You can try it and find more usages of this framework.
+
+## 📢 News
+
+- **Sep 17, 2025:** We released the [demo](https://editdemo.ai.xiaomi.net/), [model](https://huggingface.co/xiaomi-research/lego-edit), and [report](https://arxiv.org/abs/2509.12883) for Lego-Edit.
+
+## 🔥 Quick Start
+
+1️⃣  Set up environment
+```bash
+conda create -n legoedit python==3.11
+conda activate legoedit
+pip install -r ./requirements.txt
+Install flash-attention (you can install the corresponding version of flash-attention at https://github.com/Dao-AILab/flash-attention/releases)
+Modify ~/yourconda/envs/lego-edit/lib/python3.11/site-packages/transformers/modeling_utils.py, line 5105, map_location="meta" to map_location="cpu"
+```
+
+2️⃣  Download pretrained checkpoint and custom nodes
+
+Custom Nodes:
+```bash
+cd custom_nodes
+git clone https://github.com/chflame163/ComfyUI_LayerStyle.git
+git clone https://github.com/Fannovel16/comfyui_controlnet_aux.git
+```
+
+Base Model: 
+
+1. Download the [FLUX.1-Fill-dev](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev/blob/main/flux1-fill-dev.safetensors) and [FLUX.1-Canny-dev](https://huggingface.co/black-forest-labs/FLUX.1-Canny-dev/blob/main/flux1-canny-dev.safetensors) and copy them to './models/unet/'.
+
+2. Download the [vae](https://huggingface.co/black-forest-labs/FLUX.1-Fill-dev/blob/main/ae.safetensors) and copy it to './models/vae/'.
+
+3. Download the [clip_l](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/clip_l.safetensors) and [t5xxl](https://huggingface.co/comfyanonymous/flux_text_encoders/blob/main/t5xxl_fp8_e4m3fn.safetensors) and copy them to './models/clip/'.
+
+4. Download the [lama](https://drive.google.com/file/d/11RbsVSav3O-fReBsPHBE1nn8kcFIMnKp/view?usp=drive_link), unzip and copy it to './lama'.
+
+
+Our Model:
+
+1. Download all the models (Builder, mimo_lora, CVSOS, CVRES, loras) from [lego-edit](https://huggingface.co/xiaomi-research/lego-edit/).
+
+
+Your model structure should match the following:
+```bash
+├── README.md               
+├── requirements.txt                      
+├── legodemo.py                
+├── Builder/                
+├── mimo_lora/
+├── models/                     
+│   ├── unet/
+│   ├── vae/              
+│   ├── clip/         
+│   └── loras/              
+├── CVSOS/
+├── CVRES/
+├── lama/                     
+│   ├── big-lama/  
+```
+
+
+3️⃣ Use Gradio WebUI to start playing with Lego-Edit!
+```bash
+python legodemo.py
+```
+
+## 💼 New Tools Integration
+
+Our Lego-Edit supports the integration of new tools. You can follow the steps below to add custom tools, and The Builder will be able to use them during image editing.
+
+1️⃣  Add the custom tools in system_prompt.txt
+
+In system_prompt.txt, you can see many tools such as FASTINPAINT, FLUX-FILL, and more. You can add new tools to perform your desired editing tasks. For example, after the FLUX-POSE tool, you could define a new FLUX-SR tool to handle image super-resolution. In system_prompt.txt, you only need to add the model's description, inputs, outputs and constraints, as shown below:
+```bash
+...
+10.FLUX-POSE (Change the object's posture, expression, etc.)
+Input: {Image[image], Str[prompt]}
+Output: {Image[image]}
+Constraint: The input prompt must provide a detailed description of the external characteristics of the modification target, such as gender, clothing, accessories, etc and don't use any PREDICT model in advance.
+11.FLUX-BRIGHT (Input image and ratio, adjust image brightness according to ratio)
+Input: {Image[image], Float[ratio]}
+Output: {Image[image]}
+Constraint: The range of input ratio is > 0, where 0 represents the darkest, 0.5 represents it remains unchanged and > 0.5 represents the brighter.
+**Actual example1:**
+...
+```
+
+
+2️⃣  Add the tool function in legodemo.py
+
+In the initialize_model_mapping function within legodemo.py, add the function name of your new tool.
+```python
+    def initialize_model_mapping(self) -> Dict[str, Any]:
+        return {
+            "CMI-PRED": self.dummy_captionmask_pred,
+            "RES": self.dummy_res,
+            "MASK-SEG": self.dummy_mask_seg,
+            "FASTINPAINT": self.dummy_fastinpaint,
+            "FLUX-FILL": self.dummy_flux_fill,
+            "FLUX-INPAINT": self.dummy_flux_inpaint,
+            "INVERSE": self.dummy_inverse,
+            "COMPOSE": self.dummy_compose,
+            "RESIZE": self.dummy_resize,
+            "BBOX": self.dummy_bbox,
+            "SOS": self.dummy_sos,
+            "FLUX-CBG": self.dummy_flux_cbg,
+            "ADD-PRED": self.dummy_add_pred,
+            "FLUX-STYLE": self.dummy_flux_style,
+            "FLUX-RCM": self.dummy_flux_rcm,
+            "FLUX-ENV": self.dummy_flux_env,
+            "FLUX-POSE": self.dummy_flux_pose,
+            "FLUX-BRIGHT": self.dummy_flux_bright
+        }
+```
+
+Complete your function (dummy_flux_sr) in legodemo.py.
+```python
+    def dummy_flux_bright(self, inputs: Dict[str, DataObject]) -> Dict[str, DataObject]:
+        image_ori = inputs['image'].copy()
+        ratio = inputs['ratio']
+        input_value = max(0.0, min(1.0, ratio))
+        ratio = 2 * input_value
+        image_pil = Image.fromarray(image_ori[:,:,::-1])  
+        enhancer = ImageEnhance.Brightness(image_pil)
+        image_new = enhancer.enhance(ratio)
+        image_new = np.array(image_new)[:,:,::-1]
+        return {
+            "image": image_new
+        }
+```
+
+3️⃣ Restart Gradio WebUI
+
+<p align="center"><img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/bright.png" width="95%"></p>
+
+
+## 📍 More Usages
+
+Some editing models are trained at a resolution of 768 via the ICEdit method, prioritizing higher output quality over the standard 512 resolution. We provide the corresponding trained [Single-Task-LoRA](https://huggingface.co/xiaomi-research/lego-edit/tree/main/loras). Based on our testing, these models deliver superior performance within their specific functional domains.
+
+<p align="center"><img src="https://github.com/xiaomi-research/lego-edit/raw/main/resources/lora_effect.png" width="95%"></p>
+
+You can refer to the usage instructions at [ICEdit](https://github.com/River-Zhang/ICEdit) to use these LoRAs independently.
+
+
+## 📄 Disclaimer
+
+We open-source this project for academic research. The vast majority of images 
+used in this project are either generated or licensed. If you have any concerns, 
+please contact us, and we will promptly remove any inappropriate content. 
+Our code is released under the Apache 2.0 License, while our models are under 
+the CC BY-NC 4.0 License. Any models related to <a href="https://huggingface.co/black-forest-labs/FLUX.1-dev" target="_blank">FLUX.1-dev</a> 
+base model must adhere to the original licensing terms.
+<br><br>This research aims to advance the field of generative AI. Users are free to 
+create images using this tool, provided they comply with local laws and exercise 
+responsible usage. The developers are not liable for any misuse of the tool by users.
+
+## ✍️ Citation
+
+If this repo is helpful, please help to ⭐ it.
+
+If you find this project useful for your research, please consider citing our paper:
+
+```bibtex
+@article{jia2025legoedit,
+  title   = {Lego-Edit: A General Image Editing Framework with Model-Level Bricks and MLLM Builder},
+  author  = {Qifei Jia and Yu Liu and Yajie Chai and Xintong Yao and Qiming Lu and Yasen Zhang and Runyu Shi and Ying Huang and Guoquan Zhang},
+  journal = {arXiv preprint arXiv:2509.12883},
+  year    = {2025},
+  url     = {https://arxiv.org/abs/2509.12883}
+}
+```
+
+
+## 🙏 Acknowledgments
+
+- Built on the [MiMo-VL](https://github.com/XiaomiMiMo/MiMo-VL), [ComfyUI](https://github.com/comfyanonymous/ComfyUI), [FLUX](https://github.com/black-forest-labs/flux), [ICEdit](https://github.com/River-Zhang/ICEdit), [EVF-SAM](https://github.com/hustvl/EVF-SAM) and [LaMa](https://github.com/advimman/lama)