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README.md

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-license: cc-by-sa-4.0
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+<div align=center>
+<img src="assets/logo.png" width="150px">
+</div>
+<h2 align="center"> 
+  SmartPhotoCrafter: Unified Reasoning, Generation and Optimization for Automatic Photographic Image Editing
+</h2>
+
+
+<a href="https://arxiv.org/abs/2604.19587"><img src='https://img.shields.io/badge/arXiv-2501.11325-red?style=flat&logo=arXiv&logoColor=red' alt='arxiv'></a>&nbsp;
+<a href="https://vivocameraresearch.github.io/smartphotocrafterweb"><img src='https://img.shields.io/badge/Project-Page-Green' alt='Project'></a>&nbsp;
+<a href="https://huggingface.co/papers/2604.19587"><img src='https://img.shields.io/badge/🤗-HuggingFace-blue' alt='HuggingFace'></a>&nbsp;
+<a href=""><img src='https://img.shields.io/badge/🤖-ModelScope-purple' alt='ModelScope'></a>&nbsp;
+<a href="http://www.apache.org/licenses/LICENSE-2.0"><img src='https://img.shields.io/badge/License-CC BY--NC--SA--4.0-lightgreen?style=flat&logo=Lisence' alt='License'></a>&nbsp;
+
+**SmartPhotoCrafter** is an end-to-end framework for automatic photographic image editing that reformulates traditional editing as a closed-loop reasoning-to-generation process. Unlike prior methods that rely on explicit user instructions, our approach autonomously identifies aesthetic deficiencies, reasons about improvement strategies, and performs targeted edits without human prompts.
+
+
+## ✨ Highlights 
+- **Fully Automatic Editing** – No user instructions or parameters required; the model completes the closed loop of quality assessment → reasoning → editing autonomously.
+- **Dual Capability** – Supports both **image restoration** (denoising, deblurring, low-light enhancement) and **image retouching** (color, tone, contrast enhancement).
+- **Aesthetic Reasoning** – Explicitly generates image quality analysis and editing suggestions, improving interpretability.
+- **High-Fidelity Generation** – Preserves original content structure while delivering photo-realistic outputs with high tonal/color semantic sensitivity.
+- **Reinforcement Learning Optimization** – Jointly optimizes reasoning and generation modules, aligning editing trajectories with human aesthetic preferences.
+
+## 🖼️ Demo
+![teaser](./assets/teaser.png)
+
+## 🖼️ Demo Video
+<a href="https://www.youtube.com/watch?v=2p3t1ju_CxA" target="_blank">
+  <img src="https://github.com/vivoCameraResearch/SmartPhotoCrafter/blob/9d48c1684b424d540d3e3686659d62b2fb4c2a61/assets/thumbnail.jpg" alt="SmartPhotoCrafter" width="760" height="450">
+</a>
+
+
+## 📣 News 
+- **`2026/04/07`**: We open-source the inference scripts.
+- **`2026/04/22`**: Our [Paper on ArXiv](https://arxiv.org/abs/2604.19587) is available!
+
+## ✅ To-Do List for SmartPhotoCrafter Release
+- ✅ Release the inference code of SmartPhotoCrafter
+- [  ]  Release the SmartPhotoCrafter pretrained weights
+
+
+
+
+## Requirements and Installation
+
+### Prepare Environment 
+Create a conda environment & install requirements 
+```shell
+# python==3.10.0 cuda==12.4 torch==2.5
+conda create -n smartphotocrafter python==3.10.0
+conda activate smartphotocrafter
+pip install -r requirements.txt
+```
+
+### 📦 Pretrained Model Weights
+| Models           | Download |   Features |
+|------------------|---------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------|
+| SmartPhotoCrafter      | 🤗 [Huggingface]() 🤖 [ModelScope]()         | 
+Qwen-Image-Edit-2509 | 🤗 [Huggingface](https://huggingface.co/Qwen/Qwen-Image-Edit-2509) 🤖 [ModelScope](https://www.modelscope.cn/models/Qwen/Qwen-Image-Edit-2509) | Base Model |
+ 
+
+## 😉 Demo Inference
+We provide scripts for both automatic and manual editing. Automatic editing only requires inputting one image, while manual editing requires adding a prompt.
+
+Automatically edit reasoning scripts
+```PowerShell
+bash scripts/inference/automatic-edit.sh
+```
+
+Manual edit reasoning scripts
+```PowerShell
+bash scripts/inference/manual-eidt.sh
+```
+
+Script example
+```PowerShell
+CUDA_VISIBLE_DEVICES=0 python infer.py \
+    --model_path "ckpt/Qwen-Image-Edit-2509" \
+    --dit_path "ckpt/DiT.safetensors" \
+    --vlm_path "ckpt/text_encoder" \
+    --image_path "example/841012.png" \
+    --output_folder "example/output/automatic" \
+    --seed 42 \
+```
+
+
+## 🚀 Training
+Coming Soon ...
+
+## ⭐ Acknowledgement
+Our code is modified based on [Edit-R1](https://github.com/PKU-YuanGroup/Edit-R1). We adopt [Qwen-Image-Edit-2509](https://github.com/QwenLM/Qwen-Image) as the base model. 
+
+## 📜 License 
+All the materials, including code, checkpoints, and demos, are made available under the [Creative Commons BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) license. You are free to copy, redistribute, remix, transform, and build upon the project for non-commercial purposes, as long as you give appropriate credit and distribute your contributions under the same license.
+
+
+## 🎓 Citation
+
+```
+@article{zeng2026smartphotocrafter,
+  title={SmartPhotoCrafter: Unified Reasoning, Generation and Optimization for Automatic Photographic Image Editing},
+  author={Zeng, Ying and Luo, Miaosen and Li, Guangyuan and Yang, Yang and Fan, Ruiyang and Shi, Linxiao and Yang, Qirui and Zhang, Jian and Liu, Chengcheng and Zheng, Siming and others},
+  journal={arXiv preprint arXiv:2604.19587},
+  year={2026}
+}
+
+```