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Codebase for paper: Codebase for paper:
* Work with 360 capture of large-scale unbounded scenes. * Work with 360 capture of large-scale unbounded scenes.
* Support multi-gpu training and inference with PyTorch DistributedDataParallel (DDP). * Support multi-gpu training and inference with PyTorch DistributedDataParallel (DDP).
* Optimize per-image autoexposure (ongoing work) * Optimize per-image autoexposure (*experimental feature*)
## Data ## Data
* Download our preprocessed data from [tanks_and_temples](https://drive.google.com/file/d/11KRfN91W1AxAW6lOFs4EeYDbeoQZCi87/view?usp=sharing), [lf_data](https://drive.google.com/file/d/1gsjDjkbTh4GAR9fFqlIDZ__qR9NYTURQ/view?usp=sharing). * Download our preprocessed data from [tanks_and_temples](https://drive.google.com/file/d/11KRfN91W1AxAW6lOFs4EeYDbeoQZCi87/view?usp=sharing), [lf_data](https://drive.google.com/file/d/1gsjDjkbTh4GAR9fFqlIDZ__qR9NYTURQ/view?usp=sharing).
@ -28,4 +28,4 @@ python ddp_train_nerf.py --config configs/tanks_and_temples/tat_training_truck.t
```python ```python
python ddp_test_nerf.py --config configs/tanks_and_temples/tat_training_truck.txt \ python ddp_test_nerf.py --config configs/tanks_and_temples/tat_training_truck.txt \
--render_splits test,camera_path --render_splits test,camera_path
``` ```