Add project page link

README.md

@@ -1,10 +1,134 @@
 ---
-license: apache-2.0
-language:
-- en
 base_model:
 - black-forest-labs/FLUX.1-dev
-pipeline_tag: text-to-image
+language:
+- en
 library_name: diffusers
+license: apache-2.0
+pipeline_tag: text-to-image
+project_page: https://aigcdesigngroup.github.io/AnyStory/
+---
+
+This model repo is for [AnyStory](https://github.com/junjiehe96/AnyStory).
+
+<div align="center">
+<h1>AnyStory: Towards Unified Single and Multiple Subject Personalization in Text-to-Image Generation</h1>
+
+<a href='https://aigcdesigngroup.github.io/AnyStory/'><img src='https://img.shields.io/badge/Project-Page-green'></a>
+<a href='https://arxiv.org/pdf/2501.09503'><img src='https://img.shields.io/badge/arXiv-2501.09503-red'></a>
+<a href='https://huggingface.co/spaces/modelscope/AnyStory'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-yellow'></a>
+<a href='https://modelscope.cn/studios/iic/AnyStory'><img src='https://img.shields.io/badge/ModelScope-Spaces-blue'></a>
+
+</div>
+
+<img src='assets/examples-sdxl.jpg'>
+
+AnyStory is a unified approach for personalized subject generation. It not only achieves high-fidelity personalization for single subjects, but also for multiple subjects, without sacrificing subject fidelity.
+
 ---
-This model repo is for [AnyStory](https://github.com/junjiehe96/AnyStory).
+
+## News
+
+- [2025/05/01] 🚀 We release the code and demo for the `FLUX.1-dev` version of AnyStory.
+
+## Usage
+
+```python
+import torch
+from PIL import Image
+
+from huggingface_hub import hf_hub_download
+from anystory.generate import AnyStoryFluxPipeline
+
+anystory_path = hf_hub_download(repo_id="Junjie96/AnyStory", filename="anystory_flux.bin")
+story_pipe = AnyStoryFluxPipeline(
+    hf_flux_pipeline_path="black-forest-labs/FLUX.1-dev",
+    hf_flux_redux_path="black-forest-labs/FLUX.1-Redux-dev",
+    anystory_path=anystory_path,
+    device="cuda",
+    torch_dtype=torch.bfloat16
+)
+# you can add lora here
+# story_pipe.flux_pipeline.load_lora_weights(lora_path, adapter_name="...")
+
+# single-subject
+subject_image = Image.open("assets/examples/1.webp").convert("RGB")
+subject_mask = Image.open("assets/examples/1_mask.webp").convert("L")
+prompt = "Cartoon style. A sheep is riding a skateboard and gliding through the city," \
+         " holding a wooden sign that says \"hello\"."
+image = story_pipe.generate(prompt=prompt, images=[subject_image], masks=[subject_mask], seed=2025,
+                            num_inference_steps=25, height=512, width=512,
+                            guidance_scale=3.5)
+image.save("output_1.png")
+
+# multi-subject
+subject_image_1 = Image.open("assets/examples/6_1.webp").convert("RGB")
+subject_mask_1 = Image.open("assets/examples/6_1_mask.webp").convert("L")
+subject_image_2 = Image.open("assets/examples/6_2.webp").convert("RGB")
+subject_mask_2 = Image.open("assets/examples/6_2_mask.webp").convert("L")
+prompt = "Two men are sitting by a wooden table, which is laden with delicious food and a pot of wine. " \
+         "One of the men holds a wine glass, drinking heartily with a bold expression; " \
+         "the other smiles as he pours wine for his companion, both of them engaged in cheerful conversation. " \
+         "In the background is an ancient pavilion surrounded by emerald bamboo groves, with sunlight filtering " \
+         "through the leaves to cast dappled shadows."
+
+image = story_pipe.generate(prompt=prompt,
+                            images=[subject_image_1, subject_image_2],
+                            masks=[subject_mask_1, subject_mask_2],
+                            seed=2025,
+                            enable_router=True, ref_start_at=0.09,
+                            num_inference_steps=25, height=512, width=512,
+                            guidance_scale=3.5)
+image.save("output_2.png")
+```
+
+### Storyboard generation
+
+```python
+import json
+from storyboard import StoryboardPipeline
+
+storyboard_pipe = StoryboardPipeline()
+
+script_dict = json.load(open("assets/scripts/013420.json"))
+print(script_dict)
+results = storyboard_pipe(script_dict, style_name="Comic book")
+for key, result in results.items():
+    result.save(f"output_1_{key}.png")
+
+# 狮子王辛巴成长
+script_dict = json.load(open("assets/scripts/014933.json"))
+print(script_dict)
+results = storyboard_pipe(script_dict, style_name="Japanese Anime")
+for key, result in results.items():
+    result.save(f"output_2_{key}.png")
+```
+
+Example output:
+
+<img src='assets/scripts/013420_result.jpg'>
+<img src='assets/scripts/014933_result.jpg'>
+
+## Applications
+
+Intelligent creation of AI story pictures with [Qwen](https://github.com/QwenLM/Qwen3) Agent (please refer to `storyboard.py`)
+
+<img src='assets/storyboard_en.png'>
+
+AI Animation Video Production with [Wan](https://github.com/Wan-Video/Wan2.1) Image-to-Video
+
+## **Acknowledgements**
+
+This code is built on [diffusers](https://github.com/huggingface/diffusers)
+and [OminiControl](https://github.com/Yuanshi9815/OminiControl). Highly appreciate their great work!
+
+## Cite
+
+```bibtex
+@article{he2025anystory,
+  title={AnyStory: Towards Unified Single and Multiple Subject Personalization in Text-to-Image Generation},
+  author={He, Junjie and Tuo, Yuxiang and Chen, Binghui and Zhong, Chongyang and Geng, Yifeng and Bo, Liefeng},
+  journal={arXiv preprint arXiv:2501.09503},
+  year={2025}
+}
+```