This project has been created as part of the 42 curriculum by jiyawang, mhnatovs.

miniRT

Description

miniRT is a simple Raytracer developed in C. The goal of the project is to implement the fundamentals of ray tracing to render 3D scenes. It supports the rendering of basic geometric primitives (spheres, planes, and cylinders) with ambient and point light sources. The program handles camera positioning and orientation, providing a windowed display of the rendered scene using the MLX42 library.

Instructions

Prerequisites

• Linux/macOS
• cc compiler
• cmake (required for MLX42)
• glfw (dependency for MLX42)
• make

Compilation

To compile the project, run the following command in the root of the repository:

make

This will build the MLX42 library and the miniRT executable.

Usage: To run the Raytracer with a scene description file:

./miniRT scenes/test_multi_objects.rt

Controls:

• ESC - close the window and exit the program.
• W/S - move camera forward/backward
• A/D - move camera left/right
• Q/E - move camera up/down
• Z/X - rotate camera
• Scroll - Zoom (FOV)

Scene Format

The project uses .rt files to define scenes. Each line represents a scene element:

• A: Ambient lighting (ratio, RGB)
• C: Camera (position, direction, FOV)
• L: Light source (position, brightness, RGB)
• sp: Sphere (center, diameter, RGB)
• pl: Plane (point, normal, RGB)
• cy: Cylinder (center, axis, diameter, height, RGB)

Example .rt file:

A 0.2 255,255,255
C -50,0,20 1,0,0 70
L -40,0,30 0.7 255,255,255
pl 0,0,0 0,1,0 255,0,225
sp 0,0,20 20 255,0,0
cy 50.0,0.0,20.6 0,0,1.0 14.2 21.42 10,0,255

Resources

• Scratchapixel: Comprehensive guides on computer graphics and ray tracing.
• Ray Tracing in One Weekend: A popular tutorial series for building a ray tracer from scratch.

Mathematical Background

• Linear algebra: vectors, dot product, cross product
• Analytic geometry: ray-sphere, ray-plane, ray-cylinder intersection
• Lighting models: ambient, diffuse (Lambertian)

AI Usage

AI was used during development for:

Learning support:

• Explaining mathematical concepts (quadratic equation for ray-sphere intersection, vector projections)
• Breaking down complex algorithms into understandable steps
• Providing visual analogies and examples

Debugging assistance:

• Identifying logic errors in intersection calculations
• Reviewing code structure

What we did NOT use AI for:

• Writing complete functions (we wrote all code ourselves)
• Copy-pasting solutions without understanding
• Bypassing the learning process

All mathematical formulas were derived step-by-step with explanations. Every function was written by hand after understanding the underlying logic. The project represents genuine learning and comprehension of ray tracing principles.