Improve model card: Add paper, project page, code, pipeline tag, and usage examples

This PR significantly improves the model card for **ShadowDraw: From Any Object to Shadow–Drawing Compositional Art** by:

* Adding the `pipeline_tag: text-to-image` to enhance discoverability on the Hugging Face Hub for generative image tasks.
* Including a direct link to the paper: [ShadowDraw: From Any Object to Shadow-Drawing Compositional Art](https://huggingface.co/papers/2512.05110).
* Adding links to the official project page: https://red-fairy.github.io/ShadowDraw/.
* Providing a link to the GitHub repository: https://github.com/Red-Fairy/ShadowDraw.
* Incorporating detailed "Installation" and "Generate Your Own Shadow-Drawing Art" sections directly from the GitHub README, including code snippets for easy replication.
* Retaining the existing `license: cc-by-2.0`.

This update makes the model card comprehensive and immediately useful for users interested in the ShadowDraw framework.

README.md

@@ -1,3 +1,77 @@
----
-license: cc-by-2.0
----
+---
+license: cc-by-2.0
+pipeline_tag: text-to-image
+---
+
+# ShadowDraw: From Any Object to Shadow–Drawing Compositional Art
+
+This repository contains the models and code for **ShadowDraw**, a framework that transforms ordinary 3D objects into shadow-drawing compositional art. Given a 3D object, the system predicts scene parameters, including object pose and lighting, together with a partial line drawing, such that the cast shadow completes the drawing into a recognizable image.
+
+-   **Paper**: [ShadowDraw: From Any Object to Shadow-Drawing Compositional Art](https://huggingface.co/papers/2512.05110)
+-   **Project Page**: https://red-fairy.github.io/ShadowDraw/
+-   **Code**: https://github.com/Red-Fairy/ShadowDraw
+
+<div align="center">
+  <img src="https://github.com/Red-Fairy/ShadowDraw/raw/main/assets/teaser.gif" alt="ShadowDraw Teaser" width="600"/>
+</div>
+
+## 🔧 Installation
+
+First, create a conda environment and install the dependencies:
+
+```bash
+git clone https://github.com/red-fairy/ShadowDraw.git
+cd ShadowDraw
+conda env create -f environment.yml
+```
+
+Then, install Blender 4.3.2 following the instructions [here](https://download.blender.org/release/Blender4.3/), unzip it, and specify the path to the Blender executable in the `blender_path` argument of the `main.py` script.
+
+## 🎨 Generate Your Own Shadow-Drawing Art
+
+### Shadow-Drawing Art from a Single Object
+
+First, download the LoRA weights for the line drawing generation model from HuggingFace:
+```bash
+huggingface-cli download RedFairy/Flux-ShadowDraw-LoRA --local-dir ./checkpoints
+```
+
+Then, prepare your 3D object file in `.obj`, `.glb`, or `.ply` format, and run the following command:
+
+```bash
+python scripts/launch.py --object_filepaths PATH_TO_OBJECT_FILE \
+    --save_name SAVE_NAME \
+    --output_root OUTPUT_ROOT \
+    --optimize_object_params
+```
+
+To accelerate the generation process, you can remove `--optimize_object_params` and instead add `--sample_distribution`. This will fix the azimuths and fit a distribution of object internal rotations with respect to fractal dimension and sample internal rotations accordingly. 
+
+To add gravity to the object, add `--use_gravity`. If specified, the object will be first animated by gravity to find a stable pose and then rendered. 
+
+### Shadow-Drawing Art from Multiple Objects
+
+For multi-object compositions, you can use the following command:
+
+```bash
+python scripts/launch.py --object_filepaths PATH_TO_OBJECT_FILES \
+    --save_name SAVE_NAME \
+    --output_root OUTPUT_ROOT \
+    --sample_distribution
+```
+
+Here, `PATH_TO_OBJECT_FILES` should be a space-separated list of `.obj`, `.glb`, or `.ply` files.
+
+For user-specified subject, add `--user_character CHARACTER_NAME` and `--system_prompt_path system_prompts/prompt_proposal_user.txt`.
+
+## 📊 Citation
+If you find this work useful, please consider citing:
+
+```bibtex
+@article{luo2025shadowdraw,
+  title={ShadowDraw: From Any Object to Shadow–Drawing Compositional Art},
+  author={Luo, Rundong and Snavely, Noah and Ma, Wei-Chiu},
+  journal={arXiv preprint arXiv:2512.05110},
+  year={2025}   
+}
+```