VisionAIre
  • About Nodeflux
  • Visionaire Stream
    • Overview
    • Requirements
      • Credential Keys
      • Tested Hardware
      • Bandwith Requirements
    • Installation Guide
      • Dependencies
      • Simple Installation
      • Advanced Installation
      • Clustering Installation
      • Add-ons Analytics Installation
        • People Attributes Installation
        • Vehicle Attributes Installation
        • OVOD Installation
        • OVIC Installation
        • VM Installation
        • VLM Installation
    • Analytics
      • Face Recognition
        • Additional Information
          • Overview
          • Disclaimer
          • Metrics
          • Testing
      • People Analytics
      • Crowd Estimation
      • PPE Detection
      • License Plate Recognition
      • Vehicle Analytics
      • Water Level Monitoring
        • Camera Guideline
      • Pre-Flood Monitoring
      • Person Smoking Detection
      • Person with Handphone Detection
      • Smoke and Fire Detection
      • Person Using Firearms Detection
      • Vandalism Attempt Recognition
      • ATM Burglary Incident Recognition
      • Road Crash Monitoring
      • People Fighting Recognition
      • Riot Recognition
    • Developer Guide
      • How our APIs work
      • HTTP APIs
      • Websocket
      • Database Structure
    • Changelogs
  • Visionaire Snapshot
    • Overview
    • Requirements
    • Installation Guide
      • Face Searching & Matching
        • Single Node
        • Clustering
      • Helmet Detection
      • Chicken Estimation
      • Face Detection
      • Over Dimension Over Load
      • Frontal License Plate Recognition
    • Analytics
      • Face Searching & Matching
        • Face Enrollment
          • Image Guideline
          • Face and Image Quality Assessment
            • Setup On Premise
            • API
          • Insert / Update / Delete Enrollment
          • Batch Enrollment
      • Helmet Detection
      • Chicken Estimation
      • People Demography
      • Face Detection
      • Over Dimension Over Load
      • License Plate Recognition -Frontal
    • Developer Guide
      • APIs
        • Face Searching & Matching
        • Helmet Detection
        • Chicken Estimation
        • People Demography
        • Face Detection
        • Over Dimension Over Load
        • Frontal License Plate Recognition
      • Vanilla APIs for Face Enrollment
      • Porting Enrollment Database Cluster to Docker
    • Changelogs
  • VisionAIre Dashboard
    • Introduction
    • Add Analytic Assignment
    • Accessing Vanilla Database
    • Connect to Vanilla Websocket
    • Create your own visualization
      • Migration from Old Streamer to New Streamer
      • Drawing Region of Interest
      • Additional Visualization Query
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  • Parameters
  • Response

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  1. Visionaire Snapshot
  2. Developer Guide
  3. APIs

Over Dimension Over Load

Parameters

In postman, send a POST to localhost:4004/NFFS-ODOL/v1/odol-classification

{
  "images": ["base64", "base64", ...]
}

Response

Success

{
    "job": {
        "id": "2022122814242800807d33521b3af452ffc366c361adf30f082265c42ea43aef1e59139396c892f28",
        "result": {
            "analytic_type": "ODOL_CLASSIFICATION_PIPELINE",
            "result": [
                {
                    "odol_classification": [
                        {
                            "confidence": 0.9501259922981262,
                            "odol": false
                        },
                        {
                            "confidence": 0.9956569671630859,
                            "odol": true
                        },
                        {
                            "confidence": 0.0000014172385363053763,
                            "odol": false
                        }
                    ]
                }
            ],
            "status": "success"
        }
    },
    "message": "ODOL Classification Success",
    "ok": true
}

Error

{
  "job": {
    "id": "hex",
    "result": null
  },
  "message": "string",
  "ok": false
}
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Last updated 2 years ago

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