Improve model card

README.md

@@ -1,3 +1,69 @@
----
-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 reasoning photo retouching. It utilizes a 0.5B Vision-Language Model (VLM) to analyze image defects and formulate plans, which are then executed by a custom differentiable Retouch Renderer.
+
+[[Paper](https://huggingface.co/papers/2604.27375)] [[Project Page](https://apollo-yi.github.io/VeraRetouch/)] [[GitHub](https://github.com/OpenVeraTeam/VeraRetouch)]
+
+## Overview
+Existing photo retouching approaches often rely on non-differentiable external software, creating optimization barriers. VeraRetouch overcomes this with a fully differentiable Retouch Renderer, enabling direct end-to-end pixel-level training. It supports several modes:
+- **Auto Mode:** Analyzes image defects and enhances them automatically.
+- **Style Mode:** Retouches images based on user-provided text prompts.
+- **Param Mode:** Executes retouching based on specific operator parameters.
+
+## Usage
+
+### Installation
+```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 Examples
+The model supports three inference modes. First, download the weights and place them in the `./checkpoints` directory.
+
+**Auto Retouch Mode:**
+```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 Mode:**
+```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 Mode:**
+```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}
+}
+```