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
Powered by GitBook
On this page
  • Parameters
  • Response

Was this helpful?

Export as PDF
  1. Visionaire Snapshot
  2. Analytics
  3. Face Searching & Matching
  4. Face Enrollment
  5. Face and Image Quality Assessment

API

Step by Step on How to Use Face Occlusion Service

PreviousSetup On PremiseNextInsert / Update / Delete Enrollment

Last updated 1 year ago

Was this helpful?

Parameters

In postman, send a POST to coordinator:

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

Payload below if you want to determine specific threshold for each analytics inside FIQA.

{
    "additional_params": {
        "face_detection": {
            "threshold": 0.9
        },
        "face_occlusion": {
            "threshold": 0.6
        },
        "face_iqa": {
            "threshold": 0.435
        }
  },
    "images": ["base64"],
}

images base64 image contains face image that wants to be enrolled

Response

1. Success (Face Accepted for Enrollment)

{
    "job": {
        "id": "20230801100518697b88a670854340c5d452a91786c7ccfcf8149fadb86f2acfb7b2ed1316cb584e2",
        "result": {
            "analytic_type": "FACE IQA PIPELINE",
            "result": [
                {
                    "accepted": true,
                    "face_iqa": {
                        "accepted": true,
                        "iqa_score": 0.4586
                    },
                    "face_occlusion": {
                        "occluded": false,
                        "occluded_features": {
                            "cheek_left": false,
                            "cheek_right": false,
                            "chin": false,
                            "eye_left": false,
                            "eye_right": false,
                            "eyebrow_left": false,
                            "eyebrow_right": false,
                            "forehead": false,
                            "mouth": false,
                            "nose": false
                        }
                    }
                }
            ],
            "status": "success"
        }
    },
    "message": "Your Image accepted.",
    "ok": true
}

2. Unsuccessful (Face not Detected or Multiple Face Detected)

{
    "job": {
        "id": "20230801100154763e7464ad7dab8209e65262a4cbff2f7bc7759a47975a76533f7d479d784cacf45",
        "result": {
            "analytic_type": "FACE IQA PIPELINE",
            "result": [
                {
                    "accepted": false,
                    "face_iqa": {},
                    "face_occlusion": {}
                }
            ],
            "status": "success"
        }
    },
    "message": "Your Image not accepted. Face not detected or Multiple faces detected.",
    "ok": true
}

3. Unsuccessfull (Face Occluded)

{
    "job": {
        "id": "20230801100634730cadbab4b669da921d0c59256dfd1b2dc8a227495e185ea77ed39f990bc3336dd",
        "result": {
            "analytic_type": "FACE IQA PIPELINE",
            "result": [
                {
                    "accepted": false,
                    "face_iqa": {},
                    "face_occlusion": {
                        "occluded": true,
                        "occluded_features": {
                            "cheek_left": false,
                            "cheek_right": false,
                            "chin": false,
                            "eye_left": true,
                            "eye_right": false,
                            "eyebrow_left": false,
                            "eyebrow_right": false,
                            "forehead": false,
                            "mouth": false,
                            "nose": false
                        }
                    }
                }
            ],
            "status": "success"
        }
    },
    "message": "Your Image not accepted. Face is Occluded.",
    "ok": true
}

4. Unsuccessful (Face Quality not Match)

{
    "job": {
        "id": "20230801100653759d0a322b50cc1c6248b63d225619b665a78491e4cdc712006584bb625d4feb9d2",
        "result": {
            "analytic_type": "FACE IQA PIPELINE",
            "result": [
                {
                    "accepted": false,
                    "face_iqa": {
                        "accepted": false,
                        "iqa_score": 0.272
                    },
                    "face_occlusion": {
                        "occluded": false,
                        "occluded_features": {
                            "cheek_left": false,
                            "cheek_right": false,
                            "chin": false,
                            "eye_left": false,
                            "eye_right": false,
                            "eyebrow_left": false,
                            "eyebrow_right": false,
                            "forehead": false,
                            "mouth": false,
                            "nose": false
                        }
                    }
                }
            ],
            "status": "success"
        }
    },
    "message": "Your Image not accepted. Image quality not match.",
    "ok": true
}

Error

{
  "job": {
    "id": "hex",
    "result": null
  },
  "message": "string",
  "ok": false
}
http://localhost:4004/NFFS-FIQA/v1/predict