Project Details
- I got the idea for ColorVision-App after talking to a friend with color blindness. He shared how difficult it can be to distinguish certain colors in everyday life—whether picking out clothes, reading signs, or choosing the right item at a store. That conversation got me thinking: What if there were a simple, offline tool to help?
- I wanted to create something more than just another test—a real-time companion that helps users both check their vision and identify colors around them. That’s why I combined the Ishihara test for detecting color blindness with an AR-based color identifier, ensuring a seamless experience.
- To achieve a smooth and efficient experience, I used ARKit, RealityKit, CoreImage, and SwiftUI.
- Features:
- ARKit & RealityKit (Live Camera Color Detection):
- Enables real-time color recognition through the camera.
- Provides lightweight AR processing without complex 3D models.
- Works best on simple, distinct colors and may not handle highly complex images.
- CoreImage (Photo-Based Color Detection):
- Allows users to upload or capture an image.
- Detects colors when users tap on an image, providing an intuitive way to analyze colors.
- Optimized for simple, distinct color detection but may not perform well on highly detailed or blended images.
- SwiftUI (Seamless User Experience):
- Used to design a clean, intuitive interface that is simple to navigate.
- Ensures smooth performance across different device sizes.
- To align with the Swift Student Challenge requirements, I designed ColorVision-App to be fully offline and under 25MB. I did not incorporate AI models for color recognition. Instead, I leveraged native Apple frameworks to deliver a fast and reliable experience without external processing.
- Currently, ColorVision-App is optimized for identifying simple, distinct colors, making it a reliable everyday tool. While it may not yet handle highly complex images, it provides quick and clear color recognition for those who need it most.
- Goal
- Ultimately, my goal is to make color identification effortless and fun, helping users navigate the world with confidence—no matter how they see it.