Image detection related model data format

yolox

Data sets

The format of the table of contents is as follows （ After transformation ）

folder
    |——annotations
          |——train.json
          |——val.json
          |——test.json
    |——JPEGImages
          |——*.jpg

Dimension data format

{
    "categories":[
        {
            "id":0,
            "name":"cat",
            "supercategory":""
        },
        {
            "id":1,
            "name":"people",
            "supercategory":""
        }
    ],
    "images":[
        {
            "id":1,
            "file_name":"1654506696.jpg",
            "width":1920,
            "height":1080
        },
        {
            "id":2,
            "file_name":"1654506697.jpg",
            "width":1920,
            "height":1080
        },
        ...
    ],
  "annotations":[
        {
            "id":1,
            "image_id":1,
            "category_id":2,
            "bbox":[
                622,
                840,
                396,
                237
            ]
        },
        {
            "id":2,
            "image_id":1,
            "category_id":1,
            "bbox":[
                537,
                478,
                209,
                358
            ]
        },
        {
            "id":3,
            "image_id":2,
            "category_id":2,
            "bbox":[
                555,
                732,
                406,
                337
            ]
        },
        ...
      ]

bbox meaning ：[ l, t, w, h]

yolo5

Data sets

The format of the table of contents is as follows （ After transformation ）

folder
    |——images
          |——train
               |——*.jpg
          |——val
               |——*.jpg
          |——test
               |——*.jpg
    |——labels
          |——train
               |——*.txt
          |——val
               |——*.txt
          |——test
               |——*.txt

Dimension data format

# （ label   centerx centery  width height）    The proportion 
0	0.9143518518518519	0.32317708333333334	0.1712962962962963	0.2578125
0	0.4111111111111111	0.34609375	0.3074074074074074	0.2671875
0	0.0824074074074074	0.4140625	0.1648148148148148	0.18541666666666667

paddleseg