Inspection

Inspection shows how the input image is processed for each module, where detected objects are displayed for each image, providing detailed information such as rectangle coordinates, ID, image size, confidence percentage, etc.

The Context (application variable), is displayed in JSON format for each module. The data will be available in Inspection after you activate a model for any module within the Flow.

Module-independent data

Image Dimension (Pixels)

{
  "globalData": null,
  "image": {
    "type": "<numpy>",
    "shape": [
      837,
      1305,
      3
    ]
  }

Anomaly Detector - JSON Data

Detected Rectangle Data - XY Coordinates, Dimensions[px], Area[px], ID, Color, Class Name

  "detectedRectangles": [
    {
      "x": 1086,
      "y": 510,
      "width": 3,
      "height": 3,
      "area": 2,
      "id": 1603111484990003,
      "classNames": [
        {
          "color": "#ff00ff",
          "color_bgr": [
            255,
            0,
            255
          ],
          "id": 1603111688057,
          "label": "Scratch"
        }
        ....

Heatmap Data - Dimension, Color, ID & Class Name

 "heatmaps": [
    [
      {
        "type": "<numpy>",
        "shape": [
          768,
          1024,
          1
        ]
      },
      {
        "color": "#ff0000",
        "color_bgr": [
          0,
          0,
          255
        ],
        "id": 1,
        "label": "Defect"
      }
    ]
    ....

Classifier - JSON Data

Detected Rectangle Data - Class Names, ID & Confidence % (Accuracy)

Accuracy is represented as [0-1] value. To get the percentage → Accuracy * 100 = Accuracy %

Detected Rectangle for Product A has 99.99% confidence

Surface Detection - JSON Data

Detected Rectangle Data - XY Coordinates, Dimension, Area, ID, Color, Class Name

Heatmap Data - Dimension, Color, ID & Class Name

Detector - JSON Data

Detected Rectangle Data - Coordinates, Dimension, ID, Class Name, Confidence Percentage

Accuracy is represented as [0-1] value. To get the percentage → Accuracy * 100 = Accuracy %

Knowledge Base 3.18

Inspection

Analytics

Module-independent data

Image Dimension (Pixels)

Anomaly Detector - JSON Data

Detected Rectangle Data - XY Coordinates, Dimensions[px], Area[px], ID, Color, Class Name

Heatmap Data - Dimension, Color, ID & Class Name

Classifier - JSON Data

Detected Rectangle Data - Class Names, ID & Confidence % (Accuracy)

Surface Detection - JSON Data

Detected Rectangle Data - XY Coordinates, Dimension, Area, ID, Color, Class Name

Heatmap Data - Dimension, Color, ID & Class Name

Detector - JSON Data

Detected Rectangle Data - Coordinates, Dimension, ID, Class Name, Confidence Percentage

OCR - JSON Data

Detected Rectangle Info - ID, Dimension, OCR Text, Confidence Percentage

Measure - JSON Data

Lines - Name, Start & End coordinates, Angle, Measured length

Related content