Images
To access the instanceURI mask, make sure you have the proper authentication, then append a query parameter to the end of the URL.
Masks
The image segmentation tool produces a per-instance semantic mask which you can access via the instanceURI. This format supports Panoptic (instance) segmentation, so each object instance will be one row in your export file.
"Label": {
"objects": [
{
"featureId": "ck9bmetz800340za5k073bm7w",
"schemaId": "ck9blmq1lnlxz08892qqlmxto",
"title": "sample-mask",
"value": "sample-mask",
"color": "#2BFF00",
"instanceURI": "https://api.labelbox.com/masks/feature/ck9bme..."
}
],
"classifications": []
}Bounding boxes
The geometric key for Bounding boxes contains coordinates for the top left corner as well as height and width measurements.
| Ymin value |
| Xmin value |
"Label": {
"objects": [
{
"featureId": "ck9bmeej61emf0yf5bgjb4tjw",
"schemaId": "ck9blmq1lnlxw08895jy7zsk4",
"title": "sample-bbox",
"value": "sample-bbox",
"color": "#FF8000",
"bbox": {
"top": 186,
"left": 192,
"height": 300,
"width": 519
},
"instanceURI": "https://api.labelbox.com/masks/feature/ck9bmeej61emf0yf5bgjb4tjw..."
}
],
"classifications": []
}Polygons
The x,y coordinates for Polygons are listed in the order that they were initially created (points added after initial creation will be inserted in the proper position).
"Label": {
"objects": [
{
"featureId": "ck9blnafk1d070yf5bhq4q1fv",
"schemaId": "ck9blmq1lnlxv0889cu4r18mx",
"title": "sample-polygon",
"value": "sample-polygon",
"color": "#FF0000",
"polygon": [
{
"x": 3665.814,
"y": 351.628
},
{
"x": 3762.93,
"y": 810.419
},
{
"x": 3042.93,
"y": 914.233
},
{
"x": 2996.047,
"y": 864
},
{
"x": 3036.233,
"y": 753.488
}
],
"instanceURI": "https://api.labelbox.com/masks/feature/ck9..."
}
],
"classifications": []
}Polylines
For Polylines , the coordinates in the geometric key are in a clockwise direction.
"Label": {
"objects": [
{
"featureId": "ck9bmejeu00c20ya10woo1ml5",
"schemaId": "ck9blmq1lnlxx088964dfy107",
"title": "sample-polyline",
"value": "sample-polyline",
"color": "#FFFF00",
"line": [
{
"x": 328.535,
"y": 308.215
},
{
"x": 613.242,
"y": 735.277
},
{
"x": 958.026,
"y": 907.668
},
{
"x": 1352.437,
"y": 905.056
}
],
"instanceURI": "https://api.labelbox.com/masks/feature/ck9bmejeu00c20ya10woo1ml5?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJjazhwNTVueDYzdG45MDgxMWM3Z3p6dXYyIiwib3JnYW5pemF0aW9uSWQiOiJjamhmbjV5NnMwcGs1MDcwMjRuejFvY3lzIiwiaWF0IjoxNTg3NTc3MTI3LCJleHAiOjE1OTAxNjkxMjd9.U5wynJzDMe3ReL71CTzTZO7aojp1GI2TzaIpNK89XaI"
}
],
"classifications": []
}Points
The Point tool is often used for labeling tasks that require more precision than the other vector tools can offer. The Point tool does not support sub-pixel placement.
"Label": {
"objects": [
{
"featureId": "ck9bmemy91hic10bogwc6sygv",
"schemaId": "ck9blmq1lnlxy0889stzln2ms",
"title": "sample-point",
"value": "sample-point",
"color": "#D4FF00",
"point": {
"x": 116,
"y": 98
},
"instanceURI": "https://api.labelbox.com/masks/feature/..."
}
],
"classifications": []
}Image classification
The Image classification tool produces a semantic classification with no geometric information. The four classification types are radio, checklist, dropdown, and text classification.
"Label": {
"objects": [],
"classifications": [
{
"featureId": "ck9bloche1fy910bom8fgji90",
"schemaId": "ck9blmq1lnlxs0889u7xa8byw",
"title": "Free text question",
"value": "free_text_question",
"answer": "sample text"
},
{
"featureId": "ck9bloham1d1b0yf5870yxzxp",
"schemaId": "ck9blmq4ifi4b09760b4ur5ih",
"title": "Radio question",
"value": "radio_question",
"answer": {
"featureId": "ck9blohbp1d1c0yf523u34azb",
"schemaId": "ck9blmq1lnlxo0889u50lm3dx",
"title": "Yes",
"value": "yes"
}
},
{
"featureId": "ck9bloipe005h10evp9txzhi6",
"schemaId": "ck9blmq4jfi4c0976jzdlk2fw",
"title": "Checklist question",
"value": "checklist_question",
"answers": [
{
"featureId": "ck9bloiqc005i10evlzlv90v5",
"schemaId": "ck9blmq1lnlxq0889oy9h5596",
"title": "Red",
"value": "red"
},
{
"featureId": "ck9blojbm1doo0zdga69rzqdj",
"schemaId": "ck9blmq1lnlxr08893iamqxcz",
"title": "Blue",
"value": "blue"
}
]
},
{
"featureId": "ck9nedyfw05v91276aqbzfsnj",
"schemaId": "ck9nedt5a1kgw0y6tnj17m2i2",
"title": "Dropdown question",
"value": "dropdown_question",
"answer": [
{
"featureId": "ck9nedyhm05va127627ypedfy",
"schemaId": "ck9nedt701kh20y6tqoxgndvv",
"title": "Answer",
"value": "answer"
},
{
"featureId": "ck9nedyi305vb12764xxeuypd",
"schemaId": "ck9nedt8a1khb0y6t37ylx1rb",
"title": "Nested answer",
"value": "nested_answer"
}
]
}
]
}Classifications within objects
Nested classifications appear under objects. The four classification types are radio, checklist, dropdown, and text classification.
"Label": {
"objects": [
{
"featureId": "ck9nkjj6j03341081z1d9dpd4",
"schemaId": "ck9nkgekg00vz109la501ywx2",
"title": "Sample polygon",
"value": "sample-polygon",
"color": "#FF0000",
"instanceURI": "https://api.labelbox.com/masks/feature/ck9nkjj6j03341081z1d9dpd4?token=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VySWQiOiJjazUycnZ4MWtxYXpiMDc3MDBtcTI3eDRsIiwib3JnYW5pemF0aW9uSWQiOiJjazUycnZ4MG1wdzRnMDc2NndncXZqdGw5IiwiaWF0IjoxNTg4Mjk5NTY3LCJleHAiOjE1OTA4OTE1Njd9.vlI_0QUG-wJHZwdk3IZX1E59VAiTkMiF41-QyD1jIGs",
"classifications": [
{
"featureId": "ck9nkjl5d03iu0z945fhjo1gb",
"schemaId": "ck9nkjdm703bl1064fn42xtn5",
"title": "Nested classification",
"value": "nested_classification",
"answer": {
"featureId": "ck9nkjl6f03iv0z94ewv0s74j",
"schemaId": "ck9nkjdnq03bu1064oy6qimtn",
"title": "Answer 1",
"value": "answer_1"
}
}
]
}
]
}