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# Hypernerf practice reproduction instruction |
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## before getting started |
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Python 3.8 and Python 3.9 has been tested to work flawlessly. Python 3.10 will fail. |
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### Colab |
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Important Information: in May 2023, colab is updated to python 3.10, in order for this reproduction to work, select tools- command palatte - use fallback runtime. |
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This will change the runtime back to python 3.9. <br> |
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The fallback runtime is supported until mid May 2023, after that, we could only use other tricks to change the colab python version. <br> |
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Colab TPU doesnot work here anymore, GPU runs flawlessly. |
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### local machine |
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Start with python 3.8 or python 3.9 |
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Install the following: |
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sudo apt-get install libilmbase-dev libopenexr-dev ffmpeg |
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Follow official colmap project to install with cuda support, or use default package manager to install colmap, but might only has cpu support. |
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Then install pip requirements: |
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wget https://raw.githubusercontent.com/xieyizheng/hypernerf/main/requirements.txt |
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pip install -r requirements.txt |
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With this, everything is set! The Processing, Training and Rendering notebooks should now work! |
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## using the notebooks |
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There are three notebooks: Processing, Training and Rendering. <br> |
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- Processing turn raw video into Dataset |
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- Training turn Dataset into a experiment/checkpoint |
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- Rendering load a checkpoint and render desired video |
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For our custom scenes, we can start at any notebook, just set the correct data_dir and experiment_dir at the beginning. <br> |
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For rendering from a existing experiment/checkpoint, get into the config.gin and set the correct dir. |
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## Dataset Downloading: |
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- hand: |
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- dvd: |
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- tomato-mark: |