ComfyUI Extension: ComfyUI_EchoMimic

Authored by smthemex

Created 6 months ago

Updated 18 days ago

479 stars

You can using a/EchoMimic in comfyui,whitch Lifelike Audio-Driven Portrait Animations through Editable Landmark Conditioning

Custom Nodes (0)

README

ComfyUI_EchoMimic

You can use EchoMimic & EchoMimic V2 in comfyui

Echomimic：Lifelike Audio-Driven Portrait Animations through Editable Landmark Conditioning
Echomimic_v2: Towards Striking, Simplified, and Semi-Body Human Animation

New Updates 2025-01-04:

Hallo2的放大功能并不是必须项目，已移植其他分支，主分支已删除掉Hallo2的内容
The amplification function of Hallo2 is not a mandatory item, it has been ported to other branches, and the content of Hallo2 has been deleted from the main branch
支持新版的ACC模型，在infer_mode里选择pose_acc开启，如果外网通畅会自动下载，你也可以从这里预下载（denoising_unet_acc.pth和motion_module_acc.pth），并放在ComfyUI\models\echo_mimic\v2里，推荐的步数为6步,cfg为1，尺寸为768*768。ACC模型较大，小显存耗时可能会比较长；
Support the new version of ACC model, select 'pose_acc' to enable in 'infer_mode', and if the network is smooth, it will automatically download. You can also pre download from here and put it in A. The recommended 'steps' are '6' ,'cfg' is '1' and the size is 768 * 768. The ACC model is relatively large, and low video memory consumption may be longer

Previous updates：

新增输入图片跟基准图片对齐功能（选择pose_normal_sapiens时自动开启，3种驱动方式都能使用，见下面的示例图），修复之前的蒙版对齐错误。
Added the function of aligning the input image with the reference image (automatically turned on when selecting pose_normal_sapiens, all three driving methods can be used，See the example diagram below), fixed the previous mask alignment error.
V2版现在跟V1一样，有三种pose驱动方式，第一种，infer_mode选择audio_drive,pose_dir 选择列表里的几个默认pose，则使用默认的npy pose文件，第二种，infer_mode选择audio_drive,pose_dir 选择已有的npy文件夹（位于...ComfyUI/input/tensorrt_lite目录下），第三种，infer_mode选择pose_normal_dwpose 或pose_normal_sapiens,video_images连接视频入口，确认...ComfyUI/models/echo_mimic 下有yolov8m.pt 和sapiens_1b_goliath_best_goliath_AP_639_torchscript.pt2 模型（见图示和example里的工作流,下载地址见后附）；
因为调用了sapiens的pose方法，所以需要安装yolo的库ultralytics ，安装方法： pip install ultralytics
The V2 version now has three different pose driving methods, just like the V1 version. The first method is to select audio_drive for infer_mode and default poses from the list for pose_dir, using the default npy pose file. The second method is to select audio-drive for infer_mode and an existing npy folder (located in the... ComfyUI/input/tensorrt_lite directory) for pose_dir. The third method is to select 'pose_normal_dwpose' or 'pose_normal_sapiens' for infer_mode, connect to the video portal with video_images, and confirm Under ComfyUI/models/echo_mimic, there are 'YOLOV8m.pt' and 'sapiens_1b_goliath_best_goliath_AP_639_torchscript.pt2' models (see the workflow in the diagram and example,Please see the download link below)
Because the pose method of ‘Sapiens’ was called, it is necessary to install YOLO's library ultralytics. Installation method： pip install ultralytics

1. Installation

In the ./ComfyUI /custom_node directory, run the following:

git clone https://github.com/smthemex/ComfyUI_EchoMimic.git

2. Requirements

pip install -r requirements.txt

Notice

If use v1 version 如果要使用V1版本：

pip install --no-deps facenet-pytorch

因为V1版本才需求facenet-pytorch，所以不使用V1版是不需要安装facenet-pytorch的，如果安装facenet-pytorch后comfyUI崩了，可以先卸载torch，然后再重新安装，以下版本只是示例：
if comfyUI broken after pip install facenet-pytorch ,try this below:

pip uninstall torchaudio torchvision torch xformers
pip install torch torchvision torchaudio --index-url  https://download.pytorch.org/whl/cu124
pip install xformers

如果使用的是便携包版本在python_embeded目录下打开CMD ;
If it is a portable package comfyUI： open CMD in python_embeded dir

python -m pip uninstall torchaudio torchvision torch xformers
python -m pip install torch torchvision torchaudio --index-url  https://download.pytorch.org/whl/cu124
python -m pip install xformers

如果ffmpeg 报错，if ffmpeg error：

pip uninstall ffmpeg   
pip install ffmpeg-python

其他库缺啥装啥。。。
If the module is missing, , pip install missing module.

Troubleshooting errors with stable-audio-tools / other audio issues

If using conda & python >3.12

Uninstall all & downgrade python

pip uninstall torchaudio torchvision torch xformers ffmpeg

conda uninstall python
conda install python=3.11.9

pip install --upgrade pip wheel
conda install pytorch==2.2.0 torchvision==0.17.0 torchaudio==2.2.0 pytorch-cuda=11.8 -c pytorch -c nvidia
or install torch 2.4 
conda install pytorch torchvision torchaudio pytorch-cuda=12.4 -c pytorch -c nvidia

Should have most of these packages if you install the custom nodes from git urls

pip install flash-attn spandrel opencv-python diffusers jwt diffusers bitsandbytes omegaconf decord carvekit insightface easydict open_clip ffmpeg-python taming onnxruntime

3. Models Required

3.1 V1 & V2 Shared model v1 和 v2 共用的模型:
如果能直连抱脸,点击就会自动下载所需模型,不需要手动下载.

unet link
V1 & V2 audio link
vae(stabilityai/sd-vae-ft-mse) link

├── ComfyUI/models/ echo_mimic
|         ├── unet
|             ├── diffusion_pytorch_model.bin
|             ├── config.json
|         ├── audio_processor
|             ├── whisper_tiny.pt
|         ├── vae
|             ├── diffusion_pytorch_model.safetensors
|             ├── config.json

3.2 V1 models V1使用以下模型:

V1 address link
Audio-Drived Algo Inference 音频驱动

├── ComfyUI/models/echo_mimic
|         ├── denoising_unet.pth
|         ├── face_locator.pth
|         ├── motion_module.pth
|         ├── reference_unet.pth
Audio-Drived Algo Inference  acc  音频驱动加速版
|         ├── denoising_unet_acc.pth
|         ├── motion_module_acc.pth

Using Pose-Drived Algo Inference 姿态驱动

├── ComfyUI/models/echo_mimic
|         ├── denoising_unet_pose.pth
|         ├── face_locator_pose.pth
|         ├── motion_module_pose.pth
|         ├── reference_unet_pose.pth
Using Pose-Drived Algo Inference  ACC   姿态驱动加速版
|         ├── denoising_unet_pose_acc.pth
|         ├── motion_module_pose_acc.pth

3.2 v2 version
use model below V2, Automatic download, you can manually add it 使用以下模型,使用及自动下载,你可以手动添加:
模型地址address:huggingface

├── ComfyUI/models/echo_mimic/v2
|         ├── denoising_unet.pth
|         ├── motion_module.pth
|         ├── pose_encoder.pth
|         ├── reference_unet.pth
if use acc 姿态驱动加速版   
|         ├── denoising_unet_acc.pth
|         ├── motion_module_acc.pth

YOLOm8 download link
sapiens pose download link
sapiens的pose 模型可以量化为fp16的，详细见我的sapiens插件地址

├── ComfyUI/models/echo_mimic
|         ├── yolov8m.pt
|         ├── sapiens_1b_goliath_best_goliath_AP_639_torchscript.pt2  or/或者 sapiens_1b_goliath_best_goliath_AP_639_torchscript_fp16.pt2

4 Example

自动对齐输入图片Automatically align input images；
V2加载自定义视频驱动视频，V2 loads custom video driver videos
V2选择自定义pose驱动视频，V2 Choose Custom Pose Driver Video
Echomimic_v2 use default pose new version 使用官方默认的pose文件
motion_sync Extract facial features directly from the video (with the option of voice synchronization), while generating a PKL model for the reference video ，The old version 直接从从视频中提取面部特征(可以选择声音同步),同时生成参考视频的pkl模型旧版
mormal Audio-Drived Algo Inference The old version workflow 音频驱动视频常规示例旧版
pose from pkl，The old version, 基于预生成的pkl模型生成视频. 旧版
示例的 VH node ComfyUI-VideoHelperSuite node: ComfyUI-VideoHelperSuite

5 Function Description

infer_mode：音频驱动视频生成，“audio_drived” 和"audio_drived_acc"；
infer_mode：参考pkl模型文件视频pose生成 "pose_normal", "pose_acc"；
----motion_sync：如果打开且video_file有视频文件时，生成pkl文件，并生成参考视频的视频；pkl文件在input\tensorrt_lite 目录下，再次使用需要重启comfyUI。
----motion_sync：如果关闭且pose_mode不为none的时候，读取选定的pose_mode目录名的pkl文件，生成pose视频；如果pose_mode为空的时候，生成基于默认assets\test_pose_demo_pose的视频

特别的选项：

save_video：如果不想使用VH节点时，可以开启，默认关闭；
draw_mouse：你可以试试；
length：帧数，时长等于length/fps；
acc模型，6步就可以，但是质量略有下降；
lowvram :低显存用户可以开启 lowvram users can enable it
内置内置图片等比例裁切。
特别注意的地方：
cfg数值设置为1，仅在turbo模式有效，其他会报错。

Infir_mode: Audio driven video generation, "audio-d rived" and "audio-d rived_acc";
Infer_rode: Refer to the PKL model file to generate "pose_normal" and "pose_acc" for the video pose;
Motion_Sync: If opened and there is a video file in videoFILE, generate a pkl file and generate a reference video for the video; The pkl file is located in the input \ sensorrt_lite directory. To use it again, you need to restart ComfyUI.
Motion_Sync: If turned off and pose_mode is not 'none', read the pkl file of the selected pose_mode directory name and generate a pose video; If pose_mode is empty, generate a video based on the default assets \ test_pose_demo_pose

Special options:
--Save_video: If you do not want to use VH nodes, it can be turned on and turned off by default;
--Draw_mause: You can try it out;
--Length: frame rate, duration equal to length/fps;
--The ACC model only requires 6 steps, but the quality has slightly decreased;
--Built in image proportional cropping.
Special attention should be paid to:
--The cfg value is set to 1, which is only valid in turbo mode, otherwise an error will be reported.

既往更新：

增加detection_Resnet50_Final.pth 和RealESRGAN_x2plus.pth自动下载的代码，首次使用，保持realesrgan和face_detection_model菜单为‘none’（无）时就会自动下载，如果菜单里已有模型，请选择模型。
当你用torch 2.2.0+cuda 成功安装最新的facenet-pytorch库后，可以卸载掉基于 2.2.0版本的torch torchvision torchaudio xformers 然后重新安装更高版本的torch torchvision torchaudio xformers，以下是卸载和安装的示例（假设安装torch2.4）：
facecrop_ratio的放大系数为1/facecrop_ratio，如果设置为0.5，面部会得到2倍的放大，建议只在参考图片或者驱动视频中的人脸占比很小的时候，才将facecrop_ratio调整为较小的值.为1 或者0 时不裁切
添加lowvram模式，方便6G或者8G显存用户使用，注意，开启之后会很慢，而且占用内存较大，请谨慎尝试。

Previous updates：

The magnification factor of 'facecrop-ratio' is '1/facecrop-ratio'. If set to 0.5, the face will be magnified twice. It is recommended to adjust facecrop-ratio to a smaller value only when the proportion of faces in the reference image or driving video is very small,Do not cut when it is 1 or 0;
After successfully installing the latest ‘facenet-pytorch’ library using torch 2.2.0+CUDA, you can uninstall torch torch vision torch audio xformers based on version 2.2.0 and then reinstall a higher version of torch、 torch vision、 torch audio xformers. Here is an example of uninstallation and installation (installing torch 2.4):
Add lowvram mode for convenient use by 6G or 8G video memory users. Please note that it will be slow and consume a large amount of memory when turned on. Please try carefully

6 Citation

EchoMimici

@misc{chen2024echomimic,
  title={EchoMimic: Lifelike Audio-Driven Portrait Animations through Editable Landmark Conditioning},
  author={Zhiyuan Chen, Jiajiong Cao, Zhiquan Chen, Yuming Li, Chenguang Ma},
  year={2024},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}

EchoMimici-V2

@misc{meng2024echomimic,
  title={EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation},
  author={Rang Meng, Xingyu Zhang, Yuming Li, Chenguang Ma},
  year={2024},
  eprint={2411.10061},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}

sapiens

@article{khirodkar2024sapiens,
  title={Sapiens: Foundation for Human Vision Models},
  author={Khirodkar, Rawal and Bagautdinov, Timur and Martinez, Julieta and Zhaoen, Su and James, Austin and Selednik, Peter and Anderson, Stuart and Saito, Shunsuke},
  journal={arXiv preprint arXiv:2408.12569},
  year={2024}
}