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readme
Browse files- README.md +45 -0
- environment.yaml +1 -1
README.md
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## π‘ Setup Environment
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Our method is tested using cuda12.1, fp16 of accelerator and xformers on a single L40.
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```bash
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conda create -n s python=3.10
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conda activate st-modulator
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conda install pytorch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 pytorch-cuda=12.1 -c pytorch -c nvidia
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conda env create -f environment.yaml
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pip install diffusters=0.19.0
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```
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`xformers` is recommended for A100 GPU to save memory and running time.
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</details>
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```
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You may download all data and checkpoints using the following bash command
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```
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bash download_all.sh
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```
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## βοΈ ST-Modulator Editing
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You could reproduce multi-grained editing results in our teaser by running:
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```bash
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sh test.sh
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#or accelerate launch test.py --config config/run_two_man.yaml
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```
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<details><summary>The result is saved at `./result` . (Click for directory structure) </summary>
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```
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result
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βββ run_two_man
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β βββ infer_samples
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β βββ sample
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β βββ step_0 # result image folder
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β βββ step_0.mp4 # result video
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β βββ source_video.mp4 # the input video
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```
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</details>
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environment.yaml
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@@ -182,4 +182,4 @@ dependencies:
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- wcwidth==0.2.13
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- werkzeug==3.0.3
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- zipp==3.19.2
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prefix: /Data/env/anaconda3/envs/
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- wcwidth==0.2.13
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- werkzeug==3.0.3
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- zipp==3.19.2
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prefix: /Data/env/anaconda3/envs/st-modulator
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