From Photo to Pattern: Building an AI-Powered Diamond Art Design Platform

Diamond Art Icon

Introduction

Imagine turning any photo into a beautiful, custom diamond art pattern—ready for crafting, sharing, or printing. Our project makes this possible, blending advanced AI-driven image processing with a seamless user experience. Designed for hobbyists, crafters, and creative businesses, this platform automates the complex process of converting images into bead-based or shape-based SVG patterns, complete with color mapping and edge enhancements.

What sets this project apart is its smart use of AI and automation, transforming a traditionally manual, time-consuming task into a fast, accessible, and highly customizable digital service.

General Overview

At its core, the platform allows users to upload any image and receive a ready-to-use SVG pattern for diamond art. Key features include:

  • Edge Detection: Enhance image outlines for clearer, more defined patterns.
  • Color Quantization & Mapping: Reduce image colors and map them to real-world DMC thread/bead colors.
  • SVG Pattern Generation: Create scalable, printable SVG files with color-coded rectangles or overlaid bead/shape images.
  • Cloud Storage Integration: Save and share results via secure cloud links.
  • Flexible Output: Download files locally or access them from anywhere.

Use Cases:
- DIY crafters designing custom diamond art
- Small businesses offering personalized kits
- Artists digitizing their work for new mediums

Tech Stack

Backend:
- Python 3.11+ — Core language
- FastAPI — High-performance API framework
- Uvicorn — ASGI server for running FastAPI
- Poetry — Dependency management

AI/ML & Image Processing:
- OpenCV — Edge detection and image manipulation
- scikit-learn — Color quantization (KMeans clustering)
- Pillow (PIL) — Image loading and processing
- NumPy — Efficient numerical operations

Cloud & Storage:
- AWS S3 (via boto3) — File storage and presigned URL generation

Other:
- Pydantic — Data validation and response schemas
- Custom Logging — For robust monitoring and debugging

How AI Powers the System

The Role of AI

AI is at the heart of the platform’s image transformation pipeline. Here’s how:

  • Color Quantization:
    Using KMeans clustering (scikit-learn), the system reduces the number of colors in an image to a user-specified palette. This is crucial for translating complex images into manageable, craft-friendly patterns.

  • Color Mapping:
    Each quantized color is mapped to the nearest DMC thread/bead color using Euclidean distance in RGB space. This ensures the output pattern uses real, available colors.

  • Edge Detection:
    OpenCV’s Canny edge detection algorithm highlights important outlines, making the final pattern clearer and easier to follow.

Integration

  • All AI/ML operations are performed server-side, triggered by API endpoints.
  • The pipeline is modular, allowing for easy extension (e.g., adding new pattern styles or color sets).

Challenges & Solutions

  • Color Accuracy:
    Mapping arbitrary image colors to a limited set of DMC colors required careful tuning of the quantization and mapping algorithms.
  • Performance:
    Processing large images efficiently was solved by optimizing image loading and using NumPy for fast computations.
  • User Flexibility:
    Parameters like number of colors and bead size are user-configurable, balancing automation with creative control.

Technical Breakdown

Database & Storage

  • No traditional database; files are stored in AWS S3.
  • Temporary files are managed locally during processing, then uploaded or deleted as needed.

Backend Architecture

  • FastAPI serves as the main API layer.
  • Modular service structure:
  • image_processing.py — API endpoints
  • service/ — Core logic for color quantization, edge detection, SVG generation, and overlays
  • job/ — Background jobs for saving to S3
  • utils/ — Logging and helper functions

Key API Endpoints

  • /image/apply-edges/ — Apply edge detection to an uploaded image.
  • /image/generate-rect-svg/ — Generate a rectangle-based SVG pattern from an image.
  • /image/overlay-beads-on-svg/ — Overlay bead images onto an SVG pattern.
  • /image/overlay-shapes-on-svg/ — Overlay shape images onto an SVG pattern.

Engineering Decisions

  • Stateless API: Each request is independent, making scaling and deployment easier.
  • Cloud-first Storage: Using S3 for output files enables easy sharing and remote access.
  • Extensible Design: New pattern types or color sets can be added with minimal changes.

User Journey Walkthrough

  1. Upload Image:
    The user uploads a photo via the web interface (or API client).

  2. Choose Options:
    The user selects parameters like bead size, number of colors, and output type (rectangles, beads, shapes).

  3. Processing Begins:

  4. The backend receives the image.
  5. Edge detection is applied (if selected).
  6. The image is quantized to the chosen number of colors.
  7. Each color is mapped to the nearest DMC color.

  8. An SVG pattern is generated, with rectangles colored and labeled accordingly.

  9. (Optional) Overlay:

  10. The user can request overlays of bead or shape images onto the SVG for a more realistic preview.

  11. Save & Share:

  12. The result is saved locally or uploaded to AWS S3.

  13. The user receives a download link or S3 URL.

  14. Download & Craft:

  15. The user downloads the SVG and uses it to create their diamond art masterpiece.

System Flowchart (Text-Based)

User
  ↓
[Frontend Uploads Image & Options]
  ↓
FastAPI Backend
  ↓
[API Endpoint Receives Request]
  ↓
[Image Processing Pipeline]
    → Edge Detection (OpenCV)
    → Color Quantization (KMeans)
    → Color Mapping to DMC (NumPy)
    → SVG Generation (Pillow, XML)
    → (Optional) Overlay Bead/Shape Images
  ↓
[Temporary File Storage]
  ↓
[Save to AWS S3 or Local]
  ↓
[Return Download Link or S3 URL]
  ↓
User Downloads SVG Pattern

Conclusion

This project demonstrates how AI and modern Python frameworks can revolutionize creative workflows. By automating the transformation of images into craft-ready patterns, we’ve empowered users to bring their ideas to life with unprecedented ease and precision.

Technical highlights:
- Advanced AI-driven image processing
- Robust, cloud-integrated backend
- Extensible, modular architecture

Creative impact:
- Makes custom diamond art accessible to everyone
- Opens new possibilities for artists, crafters, and businesses

What’s next?
- Adding more pattern styles (e.g., circular, mosaic)
- Integrating a frontend for real-time previews
- Expanding to other crafts (cross-stitch, pixel art)