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# 已配置环境与已下载模型清单
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> 最后更新：2026-03-25
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> 机器：WSL2, RTX 5090, CUDA 12.9
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---
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## 一、Conda 环境总览
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```
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conda env list
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```
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| 环境名 | 路径 | 用途 | 磁盘占用 |
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|--------|------|------|---------|
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| `LivePortrait` | `/home/xsl/miniconda3/envs/LivePortrait` | 头部动作驱动 | 8.6GB |
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| `MuseTalk` | `/home/xsl/miniconda3/envs/MuseTalk` | 唇形同步（主力） | 11GB |
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| `latentsync` | `/home/xsl/miniconda3/envs/latentsync` | 唇形同步（备用） | 9.2GB |
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| `condiff-train-hair` | `/home/xsl/miniconda3/envs/condiff-train-hair` | 其他项目（未动） | — |
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| `onediff` | `/home/xsl/miniconda3/envs/onediff` | 其他项目（未动） | — |
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| `vllm-qwen3` | `/home/xsl/miniconda3/envs/vllm-qwen3` | 其他项目（未动） | — |
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| `py310` | `/home/xsl/miniconda3/envs/py310` | 通用 Python 3.10 | — |
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---
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## 二、LivePortrait 环境
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**激活**：`conda activate LivePortrait`
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### 关键包版本
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| 包 | 版本 |
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|----|------|
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| torch | `2.12.0.dev20260324+cu128`（nightly） |
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| CUDA | 12.8 |
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### 已下载权重
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位置：`/home/xsl/work/LivePortrait/pretrained_weights/`（总计 **1.2GB**）
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```
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pretrained_weights/
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├── insightface/
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│ └── models/buffalo_l/
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│ ├── 2d106det.onnx (4.8MB) 人脸关键点检测
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│ └── det_10g.onnx (17MB) 人脸检测
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├── liveportrait/
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│ ├── base_models/
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│ │ ├── appearance_feature_extractor.pth (3.3MB)
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│ │ ├── motion_extractor.pth (108MB)
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│ │ ├── spade_generator.pth (212MB)
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│ │ └── warping_module.pth (174MB)
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│ ├── retargeting_models/
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│ │ └── stitching_retargeting_module.pth (2.3MB)
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│ └── landmark.onnx (110MB)
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└── liveportrait_animals/
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├── base_models/ (同上，动物版)
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└── base_models_v1.1/
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└── appearance_feature_extractor.pth (3.3MB)
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```
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**来源**：`hf download KlingTeam/LivePortrait --local-dir pretrained_weights`
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---
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## 三、MuseTalk 环境
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**激活**：`conda activate MuseTalk`
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### 关键包版本
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| 包 | 版本 | 备注 |
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|----|------|------|
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| torch | `2.12.0.dev20260324+cu128` | nightly，sm_120 必须 |
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| mmcv | `2.1.0` | 从源码编译，需要 nvcc |
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| mmdet | `3.3.0` | ≥3.3.0 才兼容 mmcv 2.1.0 |
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| mmpose | `1.3.2` | ≥1.3.0 才兼容 mmcv 2.1.0 |
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| transformers | `5.3.0` | ≥4.45.0 才兼容 huggingface_hub 1.x |
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| huggingface_hub | `1.7.2` | CLI 命令名为 `hf` |
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| diffusers | `0.32.2` | |
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### 已下载权重
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位置：`/home/xsl/work/MuseTalk/models/`（总计 **5.5GB**）
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```
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models/
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├── musetalkV15/
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│ ├── unet.pth (3.2GB) 主模型
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│ └── musetalk.json 模型配置
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├── sd-vae/
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│ ├── diffusion_pytorch_model.bin (320MB) VAE 解码器
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│ └── config.json
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├── dwpose/
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│ └── dw-ll_ucoco_384.pth (389MB) 姿态估计（DWPose）
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├── whisper/
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│ ├── pytorch_model.bin (145MB) 音频特征提取
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│ ├── config.json
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│ └── preprocessor_config.json
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├── syncnet/
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│ └── latentsync_syncnet.pt (1.4GB) 唇形同步评估
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└── face-parse-bisent/
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├── 79999_iter.pth (51MB) 人脸解析
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└── resnet18-5c106cde.pth (45MB) backbone
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```
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**来源**：
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- `musetalkV15` → `hf download TMElyralab/MuseTalk`
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- `sd-vae` → `hf download stabilityai/sd-vae-ft-mse`
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- `dwpose` → `hf download yzd-v/DWPose`
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- `whisper` → `hf download openai/whisper-tiny`
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- `syncnet` → `hf download ByteDance/LatentSync`
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- `face-parse-bisent` → gdown (Google Drive) + pytorch.org
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---
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## 四、LatentSync 环境
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**激活**：`conda activate latentsync`
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### 关键包版本
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| 包 | 版本 |
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|----|------|
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| torch | `2.12.0.dev20260324+cu128`（nightly） |
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| diffusers | `0.32.2` |
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### 已下载权重
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位置：`/home/xsl/work/LatentSync/checkpoints/`（总计 **5.4GB**）
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```
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checkpoints/
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├── latentsync_unet.pt (4.8GB) 主扩散模型
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├── whisper/
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│ └── tiny.pt (73MB) Whisper 音频编码器
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└── auxiliary/
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└── models/buffalo_l/ (约330MB) insightface 人脸模型
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├── 1k3d68.onnx (137MB)
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├── 2d106det.onnx (4.8MB)
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├── det_10g.onnx (17MB)
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├── genderage.onnx (1.3MB)
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└── w600k_r50.onnx (167MB)
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```
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**来源**：
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- `latentsync_unet.pt` → `hf download ByteDance/LatentSync-1.6`
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- `whisper/tiny.pt` → `hf download ByteDance/LatentSync-1.6`
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- `buffalo_l` → 运行时自动下载（insightface）
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---
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## 五、磁盘占用汇总
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| 类别 | 路径 | 大小 |
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|------|------|------|
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| LivePortrait 权重 | `work/LivePortrait/pretrained_weights` | 1.2GB |
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| LatentSync 权重 | `work/LatentSync/checkpoints` | 5.4GB |
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| MuseTalk 权重 | `work/MuseTalk/models` | 5.5GB |
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| **模型合计** | | **~12GB** |
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| LivePortrait conda 环境 | `envs/LivePortrait` | 8.6GB |
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| MuseTalk conda 环境 | `envs/MuseTalk` | 11GB |
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| latentsync conda 环境 | `envs/latentsync` | 9.2GB |
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| **环境合计** | | **~29GB** |
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---
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## 六、产品新环境建议
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如果要为产品重建一套干净环境，**最小必要集合**是：
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```bash
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# 一个统一环境（避免两套 conda env 切换）
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conda create -n digital-human python=3.10
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conda activate digital-human
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conda install -y -c conda-forge ffmpeg
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# PyTorch nightly（RTX 5090 必须）
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pip install --pre torch torchvision torchaudio \
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--index-url https://download.pytorch.org/whl/nightly/cu128
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# LivePortrait 依赖
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pip install -r /home/xsl/work/LivePortrait/requirements.txt
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# MuseTalk 依赖（含 MMLab 完整链）
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pip install -r /home/xsl/work/MuseTalk/requirements.txt
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pip install --no-build-isolation chumpy
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pip install mmengine
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MMCV_WITH_OPS=1 pip install mmcv==2.1.0 --no-build-isolation
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pip install "mmdet>=3.3.0" "mmpose>=1.3.0"
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pip install xtcocotools json-tricks munkres
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pip install "transformers>=4.45.0"
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```
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**可复用的模型权重**（无需重新下载）：
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- LivePortrait：`/home/xsl/work/LivePortrait/pretrained_weights/` — 直接用
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- MuseTalk：`/home/xsl/work/MuseTalk/models/` — 直接用
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- LatentSync（如需）：`/home/xsl/work/LatentSync/checkpoints/` — 直接用
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