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Project Info

HomeDecorAR

Devpost

This project did not submit a demo video on Devpost.

Inspiration

We're participating in the SnapAR Challenge at CalHacks, inspired by the potential of AR technology to revolutionize home decor. We wanted to create a tool that helps users visualize furniture placement and make design decisions interactively using Spectacles.

What it does

HomeDecorAR allows users to place virtual furniture in their space through Spectacles AR glasses. It detects real furniture in the environment, displaying their dimensions in real time, giving users a seamless and immersive way to plan and visualize their home layout.

How we built it

We used Lens Studio, integrating the World Tracking Planes API to detect surfaces and display dimensions. We combined 3D models for virtual furniture and linked them to interactive touch points within Spectacles, allowing users to place and arrange items dynamically.

Challenges we ran into

Setting up accurate surface detection and integrating real-time dimension display was challenging. Ensuring that the AR furniture aligns perfectly with the environment and works consistently across various lighting and surface conditions required numerous adjustments.

Accomplishments we're proud of

We're proud of creating a seamless AR experience that integrates virtual and real furniture while providing accurate dimension measurements. Our app offers an engaging and interactive way for users to plan their home decor.

What we learned

We gained deeper knowledge in AR development, particularly in optimizing for hardware like Spectacles. We also learned about the intricacies of combining real-time object detection and dimension display in AR environments.

What's next

We plan to enhance HomeDecorAR by adding more customization options, such as different furniture styles and color schemes, and further optimizing object detection for improved accuracy across varied environments.

Analysis

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Technology

Found in codeClaimed only
  • JavaScriptIn code
  • TypeScriptIn code

2 of 2 appear in the indexed code.

AI coding agents

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Codebase size

Source size

1.4 MB

Source files

164

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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