Trimble Visual Intelligence API

A unified segmentation microservice SDK that enables any Trimble product to detect and segment Trimble equipment in images using AI-powered visual intelligence.

🎯 Purpose

The Trimble Visual Intelligence API provides a standardized way for all Trimble products (Connect, SiteVision, Ag Software, etc.) to:

• Detect Trimble equipment in images (excavators, GPS receivers, total stations, tractors, scanners)
• Segment objects with pixel-perfect masks
• Return standardized metadata (bounding boxes, masks, categories, coverage stats)
• Export results in multiple formats (PNG, JSON, ZIP)

One API. All Trimble Products. Instant Equipment Detection.

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⚡ Quick Start

Prerequisites

• Node.js (v16 or higher)
• Gemini API key (Get one here)

Installation

# 1. Install dependencies
npm install

# 2. Configure API key
# Windows (PowerShell):
Set-Content -Path ".env.local" -Value "GEMINI_API_KEY=your_actual_api_key_here"

# Mac/Linux:
echo "GEMINI_API_KEY=your_actual_api_key_here" > .env.local

# Then edit .env.local and replace 'your_actual_api_key_here' with your real key
# Get API key from: https://aistudio.google.com/app/apikey

# 3. Run development server
npm run dev

Open browser: http://localhost:3000

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🚀 Usage

1. Upload Image - Click "Upload Image" or select example
2. Specify Equipment - Enter Trimble products to detect (e.g., "excavator with GPS, R12 receiver")
3. Detect & Segment - Click button to run AI detection
4. Export Results - Download ZIP with PNG visualization + JSON metadata

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📦 Export Format

JSON Metadata

{
  "timestamp": "2025-10-09T02:00:00Z",
  "api_version": "1.0.0",
  "detections": [
    {
      "id": 1,
      "product": "Trimble R12 GNSS Receiver",
      "category": "positioning",
      "bounding_box": {"x": 0.2, "y": 0.3, "width": 0.4, "height": 0.5},
      "mask_data": "data:image/png;base64,...",
      "metadata": {
        "area_pixels": 45000,
        "coverage_percent": 12.5
      }
    }
  ]
}

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🎯 Use Cases

Construction: Auto-inventory job sites, safety compliance, progress tracking
Surveying: Equipment verification, setup QC, field documentation
Agriculture: Fleet tracking, GPS system adoption, equipment compliance
Enterprise: Cross-site visibility, asset management, analytics

See TRIMBLE_USE_CASES.md for 100+ detailed use cases.

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🏗️ Project Structure

src/
├── components/       # UI components
├── services/         # State management (Jotai)
├── config/          # Trimble products catalog & prompts
├── types/           # TypeScript definitions
├── utils/           # Export & utility functions
└── styles/          # Trimble enterprise theme

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🔧 Development

# Development server
npm run dev

# Production build
npm run build

# Preview production build
npm run preview

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🎨 Supported Trimble Products (100+)

Construction: Earthworks, Siteworks, Machine Control, SiteVision, FieldLink, Stratus
Positioning: R12i, R12, R10, R2, R780, R750 receivers, Base stations, Antennas, Catalyst
Surveying: S9, S7, S5, VX, SX10, SX12 stations, TSC7/TSC5/TSC3, T10/T7 tablets
Agriculture: Autopilot, NAV-900, NAV-500, EZ-Pilot, CFX-750, GFX-750, GFX-350, FMX, WeedSeeker 2
Geospatial: X7, X12, TX8, TX6 scanners, MX9, MX7, MX2 mapping, UX5, ZX5 drones
Software: Connect, Business Center, Access, RealWorks, eCognition, TILOS, Quantm
MEP: SysQue, AutoBid, Accubid
Transportation: Dock & Yard Management, Smart Workflow, TruETA, Freight Procurement
Railway: GEDO CE, GEDO IMS, GEDO Scan
Accessories: Survey poles, prisms, tribrachs, tripods

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🔌 Integration Example

// Upload image and detect equipment
const response = await fetch('/api/detect', {
  method: 'POST',
  body: formData
});

const results = await response.json();
// Returns: segmentation masks + metadata

👥 Built For

Proof Of Concept - Demonstrating unified visual intelligence across Trimble product ecosystem

Contact: Team Falcon