Add Docker setup for InsTaG training framework

[jmanhype]

This PR adds Docker support for containerized training

[jmanhype]

Docker Setup for InsTaG Training Framework

English

This pull request provides a complete Docker-based environment for the InsTaG training framework. It addresses several setup challenges documented in the issues by providing a consistent, containerized environment.

Key Features:

1. Dual Container Architecture:

   • Main container (CUDA 11.7, Python 3.9) for training and inference
   • Separate Sapiens container (CUDA 12.1, Python 3.10) for geometry priors

2. Helper Scripts:

   • docker-run.sh - Simplifies common operations
   • setup-docker.sh - Automates initial setup and dependency installation

3. Comprehensive Documentation:

   • Complete workflow examples
   • Detailed troubleshooting guidance
   • Support for different audio feature extractors (DeepSpeech, Wav2Vec, AVE, HuBERT)

4. Automated Setup:

   • OpenFace integration for facial AU extraction
   • EasyPortrait model download
   • Sapiens model download

5. Workflow Improvements:

   • No manual environment conflicts
   • Simplified audio feature extraction
   • Streamlined teeth mask generation
   • Container-based geometry prior generation

The documentation includes examples for both short-video adaptation (with geometry priors) and long-video training, making it easier to use the framework in various scenarios.

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中文

此 Pull Request 为 InsTaG 训练框架提供了完整的基于 Docker 的环境。它通过提供一致的容器化环境解决了 issues 中记录的几个设置挑战。

主要特点：

1. 双容器架构：

   • 主容器（CUDA 11.7，Python 3.9）用于训练和推理
   • 单独的 Sapiens 容器（CUDA 12.1，Python 3.10）用于几何先验生成

2. 辅助脚本：

   • docker-run.sh - 简化常见操作
   • setup-docker.sh - 自动化初始设置和依赖安装

3. 全面的文档：

   • 完整的工作流示例
   • 详细的故障排除指南
   • 支持不同的音频特征提取器（DeepSpeech、Wav2Vec、AVE、HuBERT）

4. 自动化设置：

   • OpenFace 集成用于面部 AU 提取
   • EasyPortrait 模型下载
   • Sapiens 模型下载

5. 工作流改进：

   • 没有手动环境冲突
   • 简化的音频特征提取
   • 简化的牙齿遮罩生成
   • 基于容器的几何先验生成

文档包括短视频适应（带几何先验）和长视频训练的示例，使框架在各种场景中更易于使用。