Data format: object detection

Introduce

Object detection due to Label Multiple field contents. So use a separate one JSON File as annotation, 001.jpg It's an original picture, 001.json Then it refers to the annotations and corresponding labels of several target objects in the figure.

Example

meta.csv

json_Label,image_Source
labels/001.json,images/001.jpg

Object detection JSON Annotated content. It is the annotation box and its corresponding content and attributes. The annotation box includes two point boxes and four point boxes:

• The two-point box is located in the upper left corner (x_min and y_min)And the bottom right corner (x_max and y_max)Two points
• The four point box is from any point (Top left point)Starting in a clockwise direction4Point coordinates. A four point box can be a rectangular box or a regular quadrilateral

The annotation coordinates use the relative positions of points on the image, for example: Image size (800, 600), Point coordinates (10, 30), The representation of the annotation box is (10/800, 30/600), That is (0.125, 0.05).

Field Description

• image_width - The width of this image
• image_height - The height of the image
• image_path - The relative path of the image file
• num_box - The number of annotation boxes on this image
• bboxes - List of annotation boxes on this image
  • attributions - Custom attribute values used in the dataset (Training not used. But there are reserved annotations)
  • label - The type annotation of this box
  • x_min / y_min - Coordinates of the upper left corner of the two-point box
  • x_max / y_max - Coordinate at the bottom right corner of the two-point box
  • x_arr - Four point box, four point sequence x coordinate
  • y_arr - Four point box, four point sequence y coordinate

Two point box annotation example

{
  "num_box": 2,
  "bboxes": [
    {
      "attributions": {
        "group": 0
      },
      "id": 0,
      "label": "ball",
      "x_max": 0.853887,
      "x_min": 0.700299,
      "y_max": 0.099826,
      "y_min": 0.050272
    },
    {
      "attributions": {
        "group": 0
      },
      "id": 1,
      "label": "ball",
      "x_max": 0.719806,
      "x_min": 0.692791,
      "y_max": 0.163233,
      "y_min": 0.110261
    }
  ],
  "image_path": "8/ballet_106_0.jpg",
  "image_width": 600,
  "image_height": 419
}

Four point box annotation example

{
  "num_box": 2,
  "bboxes": [
    {
      "id": 0,
      "attributions": {
        "group": 0
      },
      "label": "ball",
      "x_arr": [0.700982, 0.853886, 0.853203, 0.700299],
      "y_arr": [0.050271, 0.055058, 0.099825, 0.095039]
    },
    {
      "id": 1,
      "attributions": {
        "group": 0
      },
      "label": "ball",
      "x_arr": [0.698083, 0.719805, 0.714512, 0.69279],
      "y_arr": [0.11026, 0.115165, 0.163232, 0.158328]
    }
  ],
  "image_path": "8/ballet_106_0.jpg",
  "image_width": 600,
  "image_height": 419
}