📌
Getting started
📂
Data Organization
📝
Labeling
🤝
Collaboration
⚙
Data Manipulation
🔮
Neural Networks
👔
Enterprise Edition
Individual Image Annotations
For each image, we store the annotations in a separate json file named
image_name.image_format.json with the following file structure:1
{
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"description": "food",
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"name": "tomatoes-eggs-dish.jpg",
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"size": {
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"width": 2100,
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"height": 1500
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},
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"tags": [],
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"objects": []
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}
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Fields definitions:
name- string - image namedescription- string - (optional) - This field is used to store the text we want to assign to the image. In the labeling intrface it corresponds to the 'data' filed.size- stores image size. Mostly, it is used to get the image size without the actual image reading to speed up some data processing steps.width- image width in pixelsheight- image height in pixels
Full image annotation example with objects and tags
image example
Example:
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{
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"description": "",
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"tags": [
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{
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"id": 86458971,
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"tagId": 28283797,
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"name": "like",
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"value": null,
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"labelerLogin": "alexxx",
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"createdAt": "2020-08-26T09:12:51.155Z",
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"updatedAt": "2020-08-26T09:12:51.155Z"
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},
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{
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"id": 86458968,
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"tagId": 28283798,
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"name": "situated",
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"value": "outside",
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"labelerLogin": "alexxx",
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"createdAt": "2020-08-26T09:07:26.408Z",
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"updatedAt": "2020-08-26T09:07:26.408Z"
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}
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],
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"size": {
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"height": 952,
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"width": 1200
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},
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"objects": [
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{
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"id": 497521359,
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"classId": 1661571,
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"description": "",
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"geometryType": "bitmap",
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"labelerLogin": "alexxx",
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"createdAt": "2020-08-07T11:09:51.054Z",
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"updatedAt": "2020-08-07T11:09:51.054Z",
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"tags": [],
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"classTitle": "person",
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"bitmap": {
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"data": "eJwBgQd++IlQTkcNChoKAAAADUlIRF",
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"origin": [
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535,
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66
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]
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}
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},
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{
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"id": 497521358,
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"classId": 1661574,
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"description": "",
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"geometryType": "rectangle",
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"labelerLogin": "alexxx",
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"createdAt": "2020-08-07T11:09:51.054Z",
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"updatedAt": "2020-08-07T11:09:51.054Z",
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"tags": [],
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"classTitle": "bike",
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"points": {
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"exterior": [
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[
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0,
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236
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],
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[
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582,
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872
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]
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],
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"interior": []
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}
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}
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]
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}
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Last modified 1yr ago
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