updates.md

Interactive Kernel Convolution Visualizer - Updates Log

Version 0.1.0 - Initial Planning (2026-08-06)

Project Initialization

• Created comprehensive project plan (plan.md)
• Established project directory structure
• Defined core features, technical architecture, and development phases
• Identified target audience and success metrics

Key Decisions

1. Tech Stack: Next.js 14+ with TypeScript, Tailwind CSS, Framer Motion
2. Canvas Approach: HTML5 Canvas API primary, WebGL as performance fallback
3. State Management: Zustand for global state
4. Convolution Implementation: Custom JavaScript (no OpenCV.js dependency)
5. Animation: RequestAnimationFrame with configurable frame batching

Architecture Highlights

• Modular component structure separating concerns
• Step-by-step convolution generator for educational visualization
• Web Worker support for heavy computation
• Progressive rendering to maintain UI responsiveness
• Comprehensive type definitions for type safety

Development Phases Defined

8 phases over ~8 weeks covering:

1. Foundation & Setup
2. Core Convolution Engine
3. Animation & Visualization
4. Interactive Controls
5. Comparison & Analysis
6. Educational Features
7. Export & Polish
8. Advanced Features

Risk Mitigation Strategies

• Performance: Web Workers, progressive rendering, WebGL fallback
• Memory: Canvas pooling, proper cleanup
• Cross-browser: Feature detection, polyfills
• State complexity: Zustand with immutable updates

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Version 0.2.0 - Phase 1 Complete: Foundation & Setup (2026-08-06)

Completed

• Next.js 14+ project initialized with TypeScript, Tailwind CSS, ESLint
• Additional dependencies installed: Zustand, Framer Motion, Lucide React, Radix UI
• Project directory structure created (components, hooks, lib, store, types, utils)
• TypeScript type definitions for all core data structures
• Kernel library with 25+ predefined kernels across 6 categories
• Convolution engine with step-by-step generator and padding strategies
• Zustand store with complete state management for images, kernels, convolution, settings, comparison
• Custom React hooks: useConvolution, useImageLoader, useCanvas, useZoomPan
• UI component library: Button, Input, Select, Slider, Card, Badge, Tooltip
• Canvas visualization components: ConvolutionCanvas, ImageCanvas, SplitView
• Control components: PlaybackControls, OverlayControls, PaddingControls, KernelInfoPanel
• KernelSelector component with search, categories, and custom kernel editor
• Main page with three-panel layout (controls, visualization, info)
• Drag-and-drop image upload with preview
• Responsive layout with resizable sidebars
• Dark mode support
• Help modal and settings modal
• README.md with comprehensive documentation
• Updated package.json with proper metadata and scripts

In Progress

• Phase 2: Core Convolution Engine optimization
• Phase 3: Animation & Visualization polish
• Phase 4: Interactive Controls refinement

Notes

• All foundation components are in place and typed
• Convolution engine implements all 4 padding modes
• Generator-based step-by-step execution for educational visualization
• State management handles complex interactions between components
• Ready for Phase 2 optimization and Phase 3 visualization enhancements

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Version 0.3.0 - Phase 2 Complete: Static Convolution Visualization (2026-08-06)

Completed

• Added computeConvolutionStep() function to convolution engine for single-pixel inspection
• Created useStaticConvolution hook for static inspection capabilities
• Built StaticConvolutionView component with 5 educational tabs:
  • Overview: Input patch, kernel values, computation summary
  • Image Patch: Detailed patch view at clicked position
  • Multiplications: Element-wise pixel × kernel breakdown
  • Summation: Step-by-step Σ(pixel × kernel) with normalization
  • Padding: Visual demonstration of padding strategies at borders
• Implemented click-to-inspect on main ConvolutionCanvas
• Created reusable Tabs UI component with Radix UI
• Integrated static inspector into right sidebar (replaces kernel info when active)
• Added channel selector (Red/Green/Blue/Alpha) for per-channel inspection
• All 4 padding modes (zero, reflect, replicate, wrap) working in static view

Technical Achievements

• Build passes: npm run build ✓
• TypeScript passes: npm run type-check ✓
• Dev server runs without errors ✓
• Efficient single-pixel computation without full generator execution
• Reuses existing ConvolutionStep type for consistency
• Handles edge cases (clamped coordinates, invalid channels)

In Progress

• Phase 3: Animation & Visualization
• Phase 4: Interactive Controls
• Phase 5: Comparison & Analysis