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--- |
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license: apache-2.0 |
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language: |
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- en |
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library_name: diffusers |
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pipeline_tag: text-to-image |
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--- |
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<div align="center"> |
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<h1>StoryMaker: Towards consistent characters in text-to-image generation</h1> |
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<a href='https://arxiv.org/pdf/2409.12576'><img src='https://img.shields.io/badge/Technique-Report-red'></a> |
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[](https://github.com/RedAIGC/StoryMaker) |
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</div> |
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StoryMaker is a personalization solution preserves not only the consistency of faces but also clothing, hairstyles and bodies in the multiple characters scene, enabling the potential to make a story consisting of a series of images. |
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<p align="center"> |
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<img src="assets/day1.png"> |
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Visualization of generated images by StoryMaker. First three rows tell a story about a day in the life of a "office worker" and the last two rows tell a story about a movie of "Before Sunrise". |
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</p> |
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## Demos |
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### Two Portraits Synthesis |
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<p align="center"> |
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<img src="assets/two.png"> |
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</p> |
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### Diverse application |
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<p align="center"> |
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<img src="assets/diverse.png"> |
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</p> |
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## Download |
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You can directly download the model from [Huggingface](https://huggingface.co/RED-AIGC/StoryMaker). |
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If you cannot access to Huggingface, you can use [hf-mirror](https://hf-mirror.com/) to download models. |
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```python |
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export HF_ENDPOINT=https://hf-mirror.com |
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huggingface-cli download --resume-download RED-AIGC/StoryMaker --local-dir checkpoints --local-dir-use-symlinks False |
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``` |
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For face encoder, you need to manually download via this [URL](https://github.com/deepinsight/insightface/issues/1896#issuecomment-1023867304) to `models/buffalo_l` as the default link is invalid. Once you have prepared all models, the folder tree should be like: |
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``` |
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. |
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├── models |
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├── checkpoints/mask.bin |
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├── pipeline_sdxl_storymaker.py |
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└── README.md |
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``` |
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## Usage |
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```python |
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# !pip install opencv-python transformers accelerate insightface |
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import diffusers |
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import cv2 |
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import torch |
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import numpy as np |
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from PIL import Image |
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from insightface.app import FaceAnalysis |
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from pipeline_sdxl_storymaker import StableDiffusionXLStoryMakerPipeline |
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# prepare 'buffalo_l' under ./models |
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app = FaceAnalysis(name='buffalo_l', root='./', providers=['CUDAExecutionProvider', 'CPUExecutionProvider']) |
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app.prepare(ctx_id=0, det_size=(640, 640)) |
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# prepare models under ./checkpoints |
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face_adapter = f'./checkpoints/mask.bin' |
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image_encoder_path = 'laion/CLIP-ViT-H-14-laion2B-s32B-b79K' # from https://huggingface.co/laion/CLIP-ViT-H-14-laion2B-s32B-b79K |
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base_model = 'huaquan/YamerMIX_v11' # from https://huggingface.co/huaquan/YamerMIX_v11 |
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pipe = StableDiffusionXLStoryMakerPipeline.from_pretrained( |
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base_model, |
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torch_dtype=torch.float16 |
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) |
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pipe.cuda() |
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# load adapter |
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pipe.load_storymaker_adapter(image_encoder_path, face_adapter, scale=0.8, lora_scale=0.8) |
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pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config) |
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``` |
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Then, you can customized your own images |
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```python |
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# load an image and mask |
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face_image = Image.open("examples/ldh.png").convert('RGB') |
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mask_image = Image.open("examples/ldh_mask.png").convert('RGB') |
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face_info = app.get(cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)) |
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face_info = sorted(face_info, key=lambda x:(x['bbox'][2]-x['bbox'][0])*(x['bbox'][3]-x['bbox'][1]))[-1] # only use the maximum face |
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prompt = "a person is taking a selfie, the person is wearing a red hat, and a volcano is in the distance" |
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n_prompt = "bad quality, NSFW, low quality, ugly, disfigured, deformed" |
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generator = torch.Generator(device='cuda').manual_seed(666) |
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for i in range(4): |
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output = pipe( |
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image=image, mask_image=mask_image, face_info=face_info, |
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prompt=prompt, |
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negative_prompt=n_prompt, |
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ip_adapter_scale=0.8, lora_scale=0.8, |
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num_inference_steps=25, |
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guidance_scale=7.5, |
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height=1280, width=960, |
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generator=generator, |
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).images[0] |
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output.save(f'examples/results/ldh666_new_{i}.jpg') |
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``` |
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## Acknowledgements |
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- Our work is highly inspired by [IP-Adapter](https://github.com/tencent-ailab/IP-Adapter) and [InstantID](https://github.com/instantX-research/InstantID). Thanks for their great works! |
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- Thanks [Yamer](https://civitai.com/user/Yamer) for developing [YamerMIX](https://civitai.com/models/84040?modelVersionId=309729), we use it as base model in our demo. |
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