🌟 3dgs_render_python

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🚀 Introduction

3dgs_render_python is a project aimed at reimplementing the CUDA code part of 3DGS using Python. As a result, we have not only preserved the core functionality of the algorithm but also greatly enhanced the readability and maintainability of the code.

🌈 Advantages

• Transparency: Rewriting CUDA code in Python makes the internal logic of the algorithm clearer, facilitating understanding and learning.
• Readability: For beginners and researchers, this is an excellent opportunity to delve into parallel computing and 3DGS algorithms.

🔍 Disadvantages

• Performance: Since the project uses the CPU to simulate tasks originally handled by the GPU, the execution speed is slower than the native CUDA implementation.
• Resource Consumption: Simulating GPU operations with the CPU may lead to high CPU usage and memory consumption.

🛠️ Objective

The goal of this project is to provide an implementation of the 3DGS rendering part algorithm that is easier to understand and to offer a platform for users who wish to learn and experiment with 3D graphics algorithms without GPU hardware support.

📚 Applicable Scenarios

• Education and Research: Providing the academic community with the opportunity to delve into the study of 3DGS algorithms.
• Personal Learning: Helping individual learners understand the complexities of parallel computing and 3DGS.

Through 3dgs_render_python, we hope to stimulate the community's interest in 3D graphics algorithms and promote broader learning and innovation.

🔧 Quick Start

Installation Steps

# Clone the project using Git
git clone https://github.com/SY-007-Research/3dgs_render_python.git 

# Enter the project directory
cd 3dgs_render_python

# install requirements
pip install -r requirements.txt

Running the Project

# Transformation demo
python transformation.py

transformation 3d	transformation 2d

# 3DGS demo
python 3dgs.py

🏅 Support

If you like this project, you can support us in the following ways:

• GitHub Star
• bilibili