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  # Hypernerf Practice
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- This README contains overview on applyiing two custom scenes to reproduce the hypernerf project.
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  - hand
 
 
 
 
 
 
 
 
 
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  ![Image 1](hand-interpolate.gif)
 
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  ![Image 2](hand-novelview.gif)
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  PSNR: <br>
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  coarse metrics: metric/psnr≈31.7468 <br>
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  fine metrics: metric/psnr≈32.5462
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  ---
 
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  # Hypernerf Practice
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+ This README contains overview on applyiing several custom scenes to reproduce the hypernerf project.
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  - hand
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+ - dvd
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+ - tomato-mark
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+
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+
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+ ## hand
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+ most successful one, trained extensively on V100
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+ ### interpolation:
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  ![Image 1](hand-interpolate.gif)
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+ ### novelview:
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  ![Image 2](hand-novelview.gif)
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  PSNR: <br>
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  coarse metrics: metric/psnr≈31.7468 <br>
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  fine metrics: metric/psnr≈32.5462
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+ ## dvd
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+
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+ not so great
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+
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+ ### interpolation & novelview:
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+ ![Image 3](dvd-interpolate-novelview.gif)
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+
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+ PSNR: <br>
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+ coarse metrics: metric/psnr≈ <br>
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+ fine metrics: metric/psnr≈
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+
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+ ## tomato-mark
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+
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+ more artifacts
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+
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+ ![Image 4](dvd-interpolate-novelview.gif)
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+ PSNR: <br>
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+ coarse metrics: metric/psnr≈ <br>
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+ fine metrics: metric/psnr≈
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+
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+ # reproduction steps
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+
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+ Due to deprecation, the hypernerf project doesn't work out of the box. <br>
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+ We need code modifications to the environments, dependencies set up and rendering part. <br>
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+ For this reproduction, I only used the notebooks. <br>
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+ The provided instructions below are guaranteed to work.
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+
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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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