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Browse files- .gitattributes +35 -35
- .gitignore +21 -0
- LICENSE +21 -0
- README.md +142 -13
- inference.py +49 -0
- requirements.txt +22 -0
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.gitignore
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# Byte-compiled / optimized / DLL files
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__pycache__/
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# Model weights
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**/*.pth
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**/*.onnx
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pretrained_weights/*.md
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pretrained_weights/docs
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# Ipython notebook
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*.ipynb
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# Temporary files or benchmark resources
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animations/*
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tmp/*
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LICENSE
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MIT License
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Copyright (c) 2024 Kuaishou Visual Generation and Interaction Center
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
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<h1 align="center">This is the modification of LivePortrait: Efficient Portrait Animation with Stitching and Retargeting Control for allowing video as a source </h1>
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<br>
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<div align="center">
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<!-- <a href='LICENSE'><img src='https://img.shields.io/badge/license-MIT-yellow'></a> -->
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<a href='https://arxiv.org/pdf/2407.03168'><img src='https://img.shields.io/badge/arXiv-LivePortrait-red'></a>
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<a href='https://liveportrait.github.io'><img src='https://img.shields.io/badge/Project-LivePortrait-green'></a>
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<a href ='https://github.com/KwaiVGI/LivePortrait'>Official Liveportrait</a>
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</div>
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<br>
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<p align="center">
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<img src="./assets/docs/showcase2.gif" alt="showcase">
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<br>
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π₯ For more results, visit LivePortrait <a href="https://liveportrait.github.io/"><strong>homepage</strong></a> π₯
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</p>
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## π₯ Getting Started
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### 1. Clone the code and prepare the environment
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```bash
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git clone https://github.com/KwaiVGI/LivePortrait
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cd LivePortrait
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# create env using conda
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conda create -n LivePortrait python==3.9.18
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conda activate LivePortrait
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# install dependencies with pip
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pip install -r requirements.txt
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```
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### 2. Download pretrained weights
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Download the pretrained weights from HuggingFace:
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```bash
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# you may need to run `git lfs install` first
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git clone https://huggingface.co/KwaiVGI/liveportrait pretrained_weights
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```
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Or, download all pretrained weights from [Google Drive](https://drive.google.com/drive/folders/1UtKgzKjFAOmZkhNK-OYT0caJ_w2XAnib) or [Baidu Yun](https://pan.baidu.com/s/1MGctWmNla_vZxDbEp2Dtzw?pwd=z5cn). We have packed all weights in one directory π. Unzip and place them in `./pretrained_weights` ensuring the directory structure is as follows:
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```text
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pretrained_weights
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βββ insightface
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β βββ models
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β βββ buffalo_l
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β βββ 2d106det.onnx
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β βββ det_10g.onnx
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βββ liveportrait
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βββ base_models
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β βββ appearance_feature_extractor.pth
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β βββ motion_extractor.pth
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β βββ spade_generator.pth
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β βββ warping_module.pth
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βββ landmark.onnx
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βββ retargeting_models
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βββ stitching_retargeting_module.pth
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```
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### 3. Inference π
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#### Fast hands-on
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```bash
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python inference.py
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```
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If the script runs successfully, you will get an output mp4 file named `animations/s6--d0_concat.mp4`. This file includes the following results: driving video, input image, and generated result.
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<p align="center">
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<img src="./assets/docs/inference.gif" alt="image">
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</p>
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Or, you can change the input by specifying the `-s` and `-d` arguments:
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```bash
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python inference.py -s assets/examples/source/s9.jpg -d assets/examples/driving/d0.mp4
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# disable pasting back to run faster
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python inference.py -s assets/examples/source/s9.jpg -d assets/examples/driving/d0.mp4 --no_flag_pasteback
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# more options to see
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python inference.py -h
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```
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For video: you can change the input by specifying the `-sd` and `-d` arguments:
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```bash
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python inference.py -sd assets/examples/driving/d3.mp4 -d assets/examples/driving/d0.mp4 -vd True
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# disable pasting back to run faster
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python inference.py -sd assets/examples/driving/d3.mp4 -d assets/examples/driving/d0.mp4 -vd True --no_flag_pasteback
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```
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#### Driving video auto-cropping
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π To use your own driving video, we **recommend**:
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- Crop it to a **1:1** aspect ratio (e.g., 512x512 or 256x256 pixels), or enable auto-cropping by `--flag_crop_driving_video`.
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- Focus on the head area, similar to the example videos.
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- Minimize shoulder movement.
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- Make sure the first frame of driving video is a frontal face with **neutral expression**.
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Below is a auto-cropping case by `--flag_crop_driving_video`:
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```bash
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python inference.py -s assets/examples/source/s9.jpg -d assets/examples/driving/d13.mp4 --flag_crop_driving_video
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```
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If you find the results of auto-cropping is not well, you can modify the `--scale_crop_video`, `--vy_ratio_crop_video` options to adjust the scale and offset, or do it manually.
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#### Template making
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You can also use the `.pkl` file auto-generated to speed up the inference, and **protect privacy**, such as:
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```bash
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python inference.py -s assets/examples/source/s9.jpg -d assets/examples/driving/d5.pkl
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```
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**Discover more interesting results on our [Homepage](https://liveportrait.github.io)** π
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### 4. Gradio interface π€
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We also provide a Gradio interface for a better experience, just run by:
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```bash
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python app.py
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```
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You can specify the `--server_port`, `--share`, `--server_name` arguments to satisfy your needs!
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## Acknowledgements
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We would like to thank the contributors of [FOMM](https://github.com/AliaksandrSiarohin/first-order-model), [Open Facevid2vid](https://github.com/zhanglonghao1992/One-Shot_Free-View_Neural_Talking_Head_Synthesis), [SPADE](https://github.com/NVlabs/SPADE), [InsightFace](https://github.com/deepinsight/insightface), [LivePortrait](https://github.com/KwaiVGI/LivePortrait) repositories, for their open research and contributions.
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## Citation π
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```bibtex
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@article{guo2024liveportrait,
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title = {LivePortrait: Efficient Portrait Animation with Stitching and Retargeting Control},
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author = {Guo, Jianzhu and Zhang, Dingyun and Liu, Xiaoqiang and Zhong, Zhizhou and Zhang, Yuan and Wan, Pengfei and Zhang, Di},
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journal = {arXiv preprint arXiv:2407.03168},
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year = {2024}
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}
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```
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# coding: utf-8
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import os.path as osp
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import tyro
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from src.config.argument_config import ArgumentConfig
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from src.config.inference_config import InferenceConfig
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from src.config.crop_config import CropConfig
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from src.live_portrait_pipeline import LivePortraitPipeline
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def partial_fields(target_class, kwargs):
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return target_class(**{k: v for k, v in kwargs.items() if hasattr(target_class, k)})
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def fast_check_args(args: ArgumentConfig):
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if not osp.exists(args.source_image):
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raise FileNotFoundError(f"source image not found: {args.source_image}")
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if not osp.exists(args.driving_info):
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raise FileNotFoundError(f"driving info not found: {args.driving_info}")
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21 |
+
|
22 |
+
def main():
|
23 |
+
# set tyro theme
|
24 |
+
tyro.extras.set_accent_color("bright_cyan")
|
25 |
+
args = tyro.cli(ArgumentConfig)
|
26 |
+
|
27 |
+
# fast check the args
|
28 |
+
fast_check_args(args)
|
29 |
+
|
30 |
+
# specify configs for inference
|
31 |
+
inference_cfg = partial_fields(InferenceConfig, args.__dict__) # use attribute of args to initial InferenceConfig
|
32 |
+
crop_cfg = partial_fields(CropConfig, args.__dict__) # use attribute of args to initial CropConfig
|
33 |
+
|
34 |
+
live_portrait_pipeline = LivePortraitPipeline(
|
35 |
+
inference_cfg=inference_cfg,
|
36 |
+
crop_cfg=crop_cfg
|
37 |
+
)
|
38 |
+
|
39 |
+
# run
|
40 |
+
if args.flag_svideo:
|
41 |
+
live_portrait_pipeline.execute_source_video(args)
|
42 |
+
|
43 |
+
else:
|
44 |
+
live_portrait_pipeline.execute(args)
|
45 |
+
|
46 |
+
|
47 |
+
|
48 |
+
if __name__ == '__main__':
|
49 |
+
main()
|
requirements.txt
ADDED
@@ -0,0 +1,22 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
--extra-index-url https://download.pytorch.org/whl/cu118
|
2 |
+
torch==2.3.0
|
3 |
+
torchvision==0.18.0
|
4 |
+
torchaudio==2.3.0
|
5 |
+
|
6 |
+
numpy==1.26.4
|
7 |
+
pyyaml==6.0.1
|
8 |
+
opencv-python==4.10.0.84
|
9 |
+
scipy==1.13.1
|
10 |
+
imageio==2.34.2
|
11 |
+
lmdb==1.4.1
|
12 |
+
tqdm==4.66.4
|
13 |
+
rich==13.7.1
|
14 |
+
ffmpeg-python==0.2.0
|
15 |
+
onnxruntime-gpu==1.18.0
|
16 |
+
onnx==1.16.1
|
17 |
+
scikit-image==0.24.0
|
18 |
+
albumentations==1.4.10
|
19 |
+
matplotlib==3.9.0
|
20 |
+
imageio-ffmpeg==0.5.1
|
21 |
+
tyro==0.8.5
|
22 |
+
gradio==4.37.1
|