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@@ -118,7 +118,7 @@ bash environment/run_tensorboard.sh
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To evaluate the trained NeRF, we provide an evaluation script that allows you to do benchmarking (see our [benchmarking workflow](../tooling/benchmarking.md)) or to render out the scene with a custom trajectory and save the output to a video.
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```bash
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python scripts/run_eval.py --method=traj --traj=spiral --output-filename=output.mp4 --config-name=graph_instant_ngp.yaml --checkpoint-dir=outputs/blender_lego/instant_ngp/2022-07-07_230905/checkpoints
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python scripts/run_eval.py render-trajectory --load-config=outputs/blender_lego/instant_ngp/2022-07-07_230905/config.yml --traj=spiral --output-path=output.mp4
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```
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Please note, this quickstart allows you to preform everything in a headless manner. We also provide a web-based visualizer that allows you to easily monitor training or render out trajectories. See our [viewer docs](../tutorials/viewer/viewer_quickstart.md) for more.
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