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+Revision:master,CreatedAt:1754971377

README.md

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----
-license: apache-2.0
-datasets:
-- acvlab/FantasyPortrait-Multi-Expr
-language:
-- en
----
-# FantasyPortrait: Enhancing Multi-Character Portrait Animation with Expression-Augmented Diffusion Transformers
+---
+frameworks:
+- Pytorch
+license: Apache License 2.0
+tasks:
+- text-to-video-synthesis
+
+
+# FantasyPortrait：基于表情增强扩散变换器的多角色肖像动画生成
 
 [![Home Page](https://img.shields.io/badge/Project-FantasyPortrait-blue.svg)](https://fantasy-amap.github.io/fantasy-portrait/)
 [![arXiv](https://img.shields.io/badge/Arxiv-2507.12956-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2507.12956)
-[![hf_dataset](https://img.shields.io/badge/🤗%20Dataset-FantasyPortrait-yellow.svg)](https://huggingface.co/datasets/acvlab/FantasyPortrait-Multi-Expr)
+[![hf_dataset](https://img.shields.io/badge/🤗%20Dataset-FantasyPortrait-yellow.svg)](https://huggingface.co/datasets/acvlab/FantasyPortrait)
 [![hf_paper](https://img.shields.io/badge/🤗-FantasyPortrait-red.svg)](https://huggingface.co/papers/2507.12956)
 
-## 🔥 Latest News!!
-* August 10, 2025: We released the inference code, model weights and datasets.
+## 🔥 最新动态！！
+* 2025年8月10日：我们已发布推理代码、模型权重和数据集。
 
-## Demo
-For more interesting results, please visit our [website](https://fantasy-amap.github.io/fantasy-portrait/).
+## 演示
+更多有趣的结果，请访问我们的[网站](https://fantasy-amap.github.io/fantasy-portrait/)。
 
 | ![单人示例](./danren_1.gif) | ![对比](./duibi.gif) |
 | :---: | :---: |
 | ![动物](./dongwu.gif) | ![双人1](./shuangren_1.gif) |
 | ![双人2](./shuangren_2.gif) | ![三人](./sanren.gif) |
 
+## 快速开始
+### 🛠️ 安装
 
-## Quickstart
-### 🛠️Installation
-
-Clone the repo:
+克隆仓库：
 
 ```
 git clone https://github.com/Fantasy-AMAP/fantasy-portrait.git
 cd fantasy-portrait
 ```
 
-Install dependencies:
+安装依赖：
 ```
 apt-get install ffmpeg
-# Ensure torch >= 2.0.0
+# 确保 torch >= 2.0.0
 pip install -r requirements.txt
-# Note: flash attention must be installed
+# 注意：必须安装 flash attention
 pip install flash_attn
 ```
 
-### 📦Multi-Expr Dataset
-We make public the first multi-portrait facial expression video dataset **Multi-Expr Dataset**, Please download it via the this [link](https://huggingface.co/datasets/acvlab/FantasyPortrait-Multi-Expr).
+### 📦 Multi-Expr 数据集
+我们公开了首个多人肖像面部表情视频数据集 **Multi-Expr Dataset**，请通过以下链接下载：
 
-### 🧱Model Download
-| Models        |                       Download Link                                           |    Notes                      |
+
+### 🧱 模型下载
+| 模型        |                       下载链接                                           |    说明                      |
 | --------------|-------------------------------------------------------------------------------|-------------------------------|
-| Wan2.1-I2V-14B-720P  |      🤗 [Huggingface](https://huggingface.co/Wan-AI/Wan2.1-I2V-14B-720P)    🤖 [ModelScope](https://www.modelscope.cn/models/Wan-AI/Wan2.1-I2V-14B-720P)     | Base model
-| FantasyPortrait      |      🤗 [Huggingface](https://huggingface.co/acvlab/FantasyPortrait/)     🤖 [ModelScope](https://www.modelscope.cn/models/amap_cvlab/FantasyPortrait/)         | Our emo condition weights
+| Wan2.1-I2V-14B-720P  |      🤗 [Huggingface](https://huggingface.co/Wan-AI/Wan2.1-I2V-14B-720P)    🤖 [ModelScope](https://www.modelscope.cn/models/Wan-AI/Wan2.1-I2V-14B-720P)     | 基础模型
+| FantasyPortrait      |      🤗 [Huggingface](https://huggingface.co/acvlab/FantasyPortrait/)     🤖 [ModelScope](https://www.modelscope.cn/models/amap_cvlab/FantasyPortrait/)         | 我们的表情条件权重
 
-Download models using huggingface-cli:
+使用 huggingface-cli 下载模型：
 ``` sh
 pip install "huggingface_hub[cli]"
 huggingface-cli download Wan-AI/Wan2.1-I2V-14B-720P --local-dir ./models/Wan2.1-I2V-14B-720P
 huggingface-cli download acvlab/FantasyPortrait --local-dir ./models
 ```
 
-Download models using modelscope-cli:
+使用 modelscope-cli 下载模型：
 ``` sh
 pip install modelscope
 modelscope download Wan-AI/Wan2.1-I2V-14B-720P --local_dir ./models/Wan2.1-I2V-14B-720P
 modelscope download amap_cvlab/FantasyPortrait  --local_dir ./models
 ```
 
-### 🔑 Single-Portrait Inference
+### 🔑 单人肖像推理
 ``` sh
 bash infer_single.sh
 ```
 
-### 🔑 Multi-Portrait Inference
-If you use input image and drive videos with multiple people, you can run as follows:
+### 🔑 多人肖像推理
 ``` sh
 bash infer_multi.sh
 ```
-If you use input image with multiple people and different multiple single-human driven videos, you can run as follows:
-```sh
-bash infer_multi_diff.sh
-```
 
-### 📦Speed and VRAM Usage
-We present a detailed table here. The model is tested on a single A100.
 
-|`torch_dtype`|`num_persistent_param_in_dit`|Speed|Required VRAM|
+### 📦 速度与显存占用
+我们在��提供详细表格。模型在单张A100上进行测试。
+
+|`torch_dtype`|`num_persistent_param_in_dit`|速度|所需显存|
 |-|-|-|-|
-|torch.bfloat16|None (unlimited)|15.5s/it|40G|
-|torch.bfloat16|7*10**9 (7B)|32.8s/it|20G|
-|torch.bfloat16|0|42.6s/it|5G|
+|torch.bfloat16|None (无限制)|15.5秒/迭代|40G|
+|torch.bfloat16|7*10**9 (7B)|32.8秒/迭代|20G|
+|torch.bfloat16|0|42.6秒/迭代|5G|
 
 
 
-## 🧩 Community Works
-We ❤️ contributions from the open-source community! If your work has improved FantasyPortrait, please inform us.
-Or you can directly e-mail [[email protected]](mailto://[email protected]). We are happy to reference your project for everyone's convenience.
+## 🧩 社区贡献
+我们 ❤️ 来自开源社区的贡献！如果您的工作改进了 FantasyPortrait，请告知我们。
+您也可以直接发送邮件至 [[email protected]](mailto://[email protected])。我们很乐意引用您的项目，方便大家使用。
 
-## 🔗Citation
-If you find this repository useful, please consider giving a star ⭐ and citation
+## 🔗 引用
+如果本仓库对您有帮助，请考虑给我们一个 star ⭐ 并引用以下论文：
 ```
 @article{wang2025fantasyportrait,
   title={FantasyPortrait: Enhancing Multi-Character Portrait Animation with Expression-Augmented Diffusion Transformers},
@@ -107,5 +104,5 @@ If you find this repository useful, please consider giving a star ⭐ and citati
 }
 ```
 
-## Acknowledgments
-Thanks to [Wan2.1](https://github.com/Wan-Video/Wan2.1), [PD-FGC](https://github.com/Dorniwang/PD-FGC-inference) and [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) for open-sourcing their models and code, which provided valuable references and support for this project. Their contributions to the open-source community are truly appreciated.
+## 致谢
+感谢 [Wan2.1](https://github.com/Wan-Video/Wan2.1)、[PD-FGC](https://github.com/Dorniwang/PD-FGC-inference) 和 [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) 开源他们的模型和代码，为本项目提供了宝贵的参考和支持。我们非常感谢他们对开源社区的贡献。

configuration.json

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+{"framework":"Pytorch","task":"text-to-video-synthesis"}

face_det.onnx

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+size 370619

face_landmark.onnx

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+size 2865751

fantasyportrait_model.ckpt

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+oid sha256:95e1b17849ba13766ea21bd9a9a160b115e80f5dc9adf810da600a9b606c81df
+size 4013364090

pd_fpg.pth

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+oid sha256:b34f69d8e6070d1f1e9986a31bc954a8998d45ae74436aa7de128825b3606007
+size 39542043

upload.py

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+from huggingface_hub import HfApi
+
+api = HfApi()
+local_dir = "/Users/zuojing/wangqiang/FantasyPortrait"
+repo_id = "acvlab/FantasyPortrait"
+
+# 上传文件夹
+api.upload_folder(
+    folder_path=local_dir,
+    repo_id=repo_id,
+    repo_type="model"
+)