Getting Started with NVIDIA Instant NeRFs

NVIDIA's Instant NeRF is a user-friendly tool for creating neural radiance fields (NeRFs), offering a streamlined process for generating high-quality 3D visuals from a set of images. This guide provides a step-by-step walkthrough, covering code compilation, image preparation, training, and animation creation.

Compiling the Codebase

The Instant NeRF codebase is relatively straightforward to compile, especially for experienced programmers. Beginners can follow the detailed instructions available in the bycloudai fork of the main GitHub repository. Key tips for a smooth installation include:

• Re-installing Visual Studio 2019
• Re-installing the latest version of the CUDA Toolkit
• Installing Python 3.9 (Note: This might not be the latest Python version)
• Using CMake 3.22 and ensuring Python 3.9 is used during compilation

Capturing Imagery

Instant NeRF accepts both photos and videos as input. The process begins with COLMAP, which determines camera positions. Therefore, adhering to basic photogrammetry principles—ensuring sufficient image overlap and sharpness—is crucial. The accompanying video demonstrates ideal image capture examples.

Launching the GUI and Training

Once image positions are prepared, launch the GUI via Anaconda using the Testbed.exe file. Training begins automatically. Significant visual improvements occur within the first 30 seconds, but the NeRF continues to refine over several minutes. Monitor the loss graph in the GUI; when it flattens, stop training to optimize the viewer's frame rate.

The GUI offers various visualization options, including camera controls and debug visualizations. Saving frequently used command-line prompts in a text file is recommended for future use.

Creating Animations

NVIDIA Instant NeRF provides a user-friendly camera path editor. Add keyframes by navigating the scene and selecting "Add from Cam." The GUI generates a camera trajectory using Bézier curves. Preview the animation using "Read," and once satisfied, save the camera path and render a high-quality video using the render script in the scripts folder.

Conclusion

Instant NeRF's ability to capture the entire background as part of the scene is a significant advantage over traditional photogrammetry methods. This opens up exciting possibilities for capturing and visualizing the world in innovative ways. The speed and ease of use make Instant NeRF an excellent tool for learning and experimenting with NeRF technology.

Bonus: Cropping Instant NeRF Renderings

Learn how to crop the background from your Instant NeRF renderings in this additional tutorial (link omitted as per instructions).