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Upload GT-file

Upload externally created labeling data (GT files).

What is a Ground Truth file?

Ground Truth is a term that came from meteorology, which refers to information collected from a single location. When we look at this from a machine learning perspective, Ground Truth is used for showing the source or actual value of the data that want to learn.

Ground Truth is a term that refers to real-world data used to learn and test AI model outputs in the field of artificial intelligence data. Ground Truth data is necessary for a lot of AI applications such as autonomous driving and audio or voice recognition.

  • The GT file upload format only supports JSON.
  • Upload conditions: It must have the same folder structure and file name as the uploaded resource file, in the JSON file structure.

  • The task type set in the project (box, keypoint, etc.), class, and attribute names and values must be the same.
  • Even if the case and spacing are different, the upload fails.
  • Example of GT file upload failure (1)
    Class name registered in the project: car /
    The class name is written in JSON: Car
  • Failure case due to conditions not in the project (2)
    The value of the attribute ‘weather’ under class A registered in the project: sunny, cloudy, rainy
    The class name is written in JSON: Snow

GT upload format and validity

GT Upload Schema

{
  "annotations": [
    {
      "id": "26-abd21cb9-cb89-4cf4-8de6-b0a6421024b3",
      "type": "poly_seg",
      "attributes": {},
      "points": [
        [
          905,
          44
        ],
        [
          1280,
          228
        ],
        [
          1272,
          232
        ]
      ],
        "label": "Road"
      }
    ],
    "attributes": {},
    "file_id": "6465703408f21776587bbdac",
    "filename": "1020312_0_2023-05-03_17-10-44_1683133844_0001584.jpg",
    "parent_path": "/0000/3576612_0_2023-04-03_17-10-44_1683133844",
    "metadata": {
      "height": 1080,
      "width": 1920
    }
  }

GT Upload Field Definition

NameTypeDescriptionExample
annotationslist[object]Annotation informationReference annotation field
attributesobjectWhen setting an attribute of the task type classification, it is the same as the attribute of the classification

When there is no classification {}
{
"attribute name”: “attribute value”, "attribute name”: “attribute value"
}
When it isn’t set ⇒ {}
labelstringIt exists only when the task type is the classification

*If there is no classification in task type, the field does not exist
“Classification”
file_idobjectThe ID of the file620aea6c1e3c3ccd9cfd8bc9
scene_idstringThe ID of the scene file

* If the resource type is neither Sequence Image nor Point Cloud, the field does not exist
620aea6c1e3c3ccd9cfd8bc8
filenamestringFile names

* In the case of the resource type Sequence Image or Point Cloud, this corresponds to a frame within the scene file
image (28).jpeg
parent_pathstringThe parent path of the file/batch_5/20220624/daytime
last_modifier_idstringLast modifier id5fc7323e8511afbb60e8554b
metadataobjectFile metadata by each resource type
Image: image size
PointCloud, Text: {} empty value
Video:fps (frames)
# If it's an image{
"height": 1080,
"width": 1920
}

# If it's a video{
“fps”: 30
}
last_workersobjectThe last worker at each stage{
"labeling": "5fc7323e8511afbb60e8554b",
"inspection": null,
"final inspection": null
}
tagslist[object]The tag value of the file

*If you do not check whether the tag is included or not, the field does not exist
When the tag is applied ⇒ [”car”]
When the tag is not applied ⇒ no field
parent_tagslist[object]The tag value of the folder
*If you do not check whether the tag is included or not, the field does not exist
If the tag is applied ⇒ [” Primary task”]
If the tag is not applied ⇒ no field

GT file generation guide for each field

  1. Annotations field
    1. ID definition
      1. Starts with number, and the string part is written in uuid format.
      • ex. 26-abd21cb9-cb89-4cf4-8de6-b0a6421024b3
    2. Attributes definition
      1. Key value and value must be registered to labeling setting.
    3. Type definition
      1. [Single/Sequence Image(Vector)] : In case of Bounding Box, Polygon, Polyline, Segmentation
        • annotations > points: Co-ordinate are to be real number or integer value and must not deviate from working range.
  2. Files matching with parent_path and filename must not be started.
    • However, both parent_path and filename must be written.
  3. Attributes field
    1. Key value and value must be registered to labeling setting.
  4. Annotation track_id must not be duplicated in sequence_image.
  5. Upload will not be effected if file_id information is omitted.

Validation

  • Status validation: Check the status that the task has not started.
  • Check for the existence of file paths: Check that the actual file exists in the path name.
  • Annotation check: Check the annotation data that matches your project settings.

Refer to AIMMO enterprise output form



If you have any other inquiries, please get in touch with us at [email protected]