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# NeRF++
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Codebase for paper:
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* Work with 360 capture of large-scale unbounded scenes.
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* Support multi-gpu training and inference.
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## Data
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* Download our preprocessed data from [tanks_and_temples](), [lf_data]().
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* Put the data in the code directory.
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* Data format.
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** Each scene consists of 3 splits: train/test/validation.
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** Intrinsics and poses are stored as flattened 4x4 matrices.
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** Opencv camera coordinate system is adopted, i.e., x--->right, y--->down, z--->scene.
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* Scene normalization: move the average camera center to origin, and put all the camera centers inside the unit sphere.
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## Training
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```python
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python ddp_train_nerf.py --config configs/tanks_and_temples/tat_training_truck.txt
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```
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## Testing
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```python
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python ddp_test_nerf.py --config configs/tanks_and_temples/tat_training_truck.txt --render_splits test,camera_path
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```
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