Classification
Overview
There are two ways to configure the classification tool: classification only and nested classification on an object.
Follow the steps below once you have create a project and upload your image data.
Set up classification only
- Bypass the "Add Object" step.
- Add a classification question(s).
- Select answer choice type and add answer(s).
- Click "Confirm".
Set up nested classification on an object
- Click "Add Object".
- Name your object and choose a labeling tool from the dropdown menu.
- Click on the right arrow on the object to open the Settings for that object.
- Add a classification question(s).
- Select answer choice type and add answer(s).
- Click "Done".
The classification tool only produces a semantic classification and does not include any geometric annotation or pixel classification information. There are four ways for labelers to provide a value for classification: radio, checklist, dropdown, and free-form text.
Radio
Use the radio format if you would like a labeler to choose a single answer from a selection of answer choices.
The nested radio format allows the labeler to select multiple answers from a nested taxonomy.
Configuration
This is what your JSON file will look like when you export classifications configured with radio answer choices.
//Radio
"classifications: [
{
"featureId": "",
"schemaId": "",
"title": "",
"value": "",
"answer": {
"featureId": "",
"schemaId": "",
"title": "",
"value": ""
}
}
]
Checklist or Dropdown
Use the checklist or dropdown format if you would like a labeler to choose multiple answers from a selection of answer choices.
The nested dropdown allows labelers to select answers from a nested taxonomy.
Configuration
This is what your JSON file will look like when you export classifications configured with checklist or dropdown answer choices.
//Checklist OR Dropdown
"classifications: [
{
"featureId": "",
"schemaId": "",
"title": "",
"value": "",
"answers": [
{
"featureId": "",
"schemaId": "",
"title": "",
"value": ""
}
]
}
]
Free-form text
Use the text classification format if you would like a labeler to enter a free-form text answer in response to a classification question.
There are various cases where you might want to use free-form text input such as for optical character recognition (OCR) tasks. Often OCR tasks have use the bounding box tool along with the nested free-form text classification tool.
Configuration
This is what your JSON file will look like when you export classifications configured with free-form text answer choices.
// Text classification
"classifications": [
{
"featureId": "",
"schemaId": "",
"title": "",
"value": "",
"answer": ""
}
]
