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README.md

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@@ -18,8 +18,8 @@ conda create -n som python=3.10
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conda activate som
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```
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Update `requirements.txt` with correct CUDA version for PyTorch and cuUML,
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i.e., replacing `cu122` and `cu12` with your CUDA version.
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Update `requirements.txt` with correct CUDA version for PyTorch and cuUML,
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i.e., replacing `cu122` and `cu12` with your CUDA version.
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```
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pip install -r requirements.txt
@@ -35,20 +35,30 @@ Please follow the guide in the [preprocessing README](./preproc/README.md).
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### Fitting to a Video
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```
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python run_training.py --work-dir <OUTPUT_DIR> --data:davis --data.seq-name horsejump-low
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```python
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python run_training.py \
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--work-dir <OUTPUT_DIR> \
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data:davis \
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--data.seq-name horsejump-low
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```
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## Evaluation on iPhone Dataset
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First, download our processed iPhone dataset from [this](https://drive.google.com/drive/folders/1xJaFS_3027crk7u36cue7BseAX80abRe?usp=sharing) link. To train on a sequence, e.g., *paper-windmill*, run:
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```
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python run_training.py --work-dir <OUTPUT_DIR> --port <PORT> --data:iphone --data.data-dir </path/to/paper-windmill/>
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```python
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python run_training.py \
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--work-dir <OUTPUT_DIR> \
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--port <PORT> \
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data:iphone \
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--data.data-dir </path/to/paper-windmill/>
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```
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After optimization, the numerical result can be evaluated via:
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```
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PYTHONPATH='.' python scripts/evaluate_iphone.py --data_dir </path/to/paper-windmill/> --result_dir <OUTPUT_DIR> --seq_names paper-windmill
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PYTHONPATH='.' python scripts/evaluate_iphone.py \
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--data_dir </path/to/paper-windmill/> \
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--result_dir <OUTPUT_DIR> \
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--seq_names paper-windmill
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```
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