Improve model card

README.md

@@ -1,3 +1,66 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+pipeline_tag: image-to-image
+---
+
+# VeraRetouch: A Lightweight Fully Differentiable Framework for Multi-Task Reasoning Photo Retouching
+
+VeraRetouch is a lightweight and fully differentiable framework for multi-task photo retouching. It employs a 0.5B Vision-Language Model (VLM) as the central intelligence to formulate retouching plans based on instructions and scene semantics, combined with a fully differentiable Retouch Renderer for direct end-to-end pixel-level training.
+
+[**Paper**](https://huggingface.co/papers/2604.27375) | [**Project Page**](https://apollo-yi.github.io/VeraRetouch/) | [**GitHub**](https://github.com/OpenVeraTeam/VeraRetouch)
+
+## 🚀 Quick Start
+
+### ⚙️ Environment Setup
+```bash
+# Clone the repository
+git clone https://github.com/OpenVeraTeam/VeraRetouch.git
+cd VeraRetouch
+
+# Create and activate conda environment
+conda create -n vera-retouch python=3.10
+conda activate vera-retouch
+pip install -r requirements.txt
+```
+
+### 🎨 Inference Modes
+VeraRetouch supports three primary inference modes via `inference.py`. Ensure you have downloaded the weights and placed them in the `./checkpoints` directory.
+
+#### Auto Retouch
+Automatically enhances an image based on scene analysis.
+```bash
+python inference.py --mode auto \
+                    --model-path ./checkpoints/VeraRetouch \
+                    --img_paths ./data_samples/input/sample_flower.jpg \
+                    --save_dir ./data_samples/output/
+```
+
+#### Style Retouch
+Retouches an image based on a specific user prompt.
+```bash
+python inference.py --mode style \
+                    --prompt "I want a dreamy bright pink style." \
+                    --model-path ./checkpoints/VeraRetouch \
+                    --img_paths ./data_samples/input/sample_flower.jpg \
+                    --save_dir ./data_samples/output/
+```
+
+#### Param Retouch
+Applies retouching based on specific operator parameters.
+```bash
+python inference.py --mode style \
+                    --instruction_path ./data_samples/param.json \
+                    --model-path ./checkpoints/VeraRetouch \
+                    --img_paths ./data_samples/input/sample_flower.jpg \
+                    --save_dir ./data_samples/output/
+```
+
+## Citation
+```bibtex
+@article{guo2026veraretouch,
+  title={VeraRetouch: A Lightweight Fully Differentiable Framework for Multi-Task Reasoning Photo Retouching},
+  author={Guo, Yihong and Lyu, Youwei and Tang, Jiajun and Zhou, Yizhuo and Wang, Hongliang and Chen, Jinwei and Zou, Changqing and Fan, Qingnan},
+  journal={arXiv preprint arXiv:2604.27375},
+  year={2026}
+}
+```