Dataset

Dataset object

{
"info": {
"description": "Intenseye Dataset",
"url": "https://intenseye.com",
"version": "1.0",
"year": 2021,
"contributor": "Team Intenseye",
"date_created": "2021-02-12T06:52:08Z",
"creation_parameters": {
"name": "test.json",
"email": "[email protected]",
"inimgcats": [
"head",
"person"
],
"eximgcats": [],
"abeximgcats": [
"truck"
],
"inlabelcats": [
"forklift",
"hearing_muff",
"mask",
"reflective_vest",
"face",
"person",
"glasses",
"respiratory_protective_equipment",
"hardhat",
"head",
"car",
"helmet",
"motorcycle",
"truck"
],
"exlabelcats": [],
"trainSize": 0,
"unlabelledRatio": 1,
"partitionRatio": 0.8999999761581421,
"shuffle": true,
"abexImgCats": [
{
"id": 8,
"supercategory": "vehicle",
"name": "truck"
}
],
"incamids": null,
"excamids": null,
"indatasets": null,
"exdatasets": null,
"inobjecttags": [
"mask"
],
"exobjecttags": null
}
},
"images": {
"validation": [
{
"id": 79355,
"file_name": "efc0ed60-6514-4612-81e4-b4477423605e.jpg",
"height": 1080,
"width": 1920,
"dataset": "intenseye",
"storage_class": "S3",
"url": "https://blog.intenseye.com/content/images/size/w2000/2019/11/blog-post---1-1.png",
"md5": null,
"created_at": "2021-02-12T09:30:49Z",
"category_ids": [
92
]
}
],
"train": [
{
"id": 363758,
"image_id": 79355,
"bbox": [
263.76237623762376,
435.4455445544554,
114.05940594059405,
66.53465346534654
],
"category_id": 92,
"area": 7588.903048720713,
"segmentation": [],
"iscrowd": 0,
"object_tags": [
1,
2,
8
]
}
]
},
"annotations": [
{
"id": 363758,
"image_id": 79355,
"bbox": [
263.76237623762376,
435.4455445544554,
114.05940594059405,
66.53465346534654
],
"category_id": 92,
"area": 7588.903048720713,
"segmentation": [],
"iscrowd": 0,
"object_tags": [
1,
2,
8
]
}
],
"categories": [
{
"id": 1,
"supercategory": "person",
"name": "person"
},
{
"id": 3,
"supercategory": "vehicle",
"name": "car"
},
{
"id": 4,
"supercategory": "vehicle",
"name": "motorcycle"
},
{
"id": 8,
"supercategory": "vehicle",
"name": "truck"
},
{
"id": 91,
"supercategory": "accessory",
"name": "helmet"
},
{
"id": 92,
"supercategory": "accessory",
"name": "head"
},
{
"id": 93,
"supercategory": "vehicle",
"name": "forklift"
},
{
"id": 95,
"supercategory": "accessory",
"name": "hardhat"
}
],
"object_tags": [
{
"id": 1,
"name": "helmet",
"categoryId": 92,
"attribute": 91
},
{
"id": 2,
"name": "motorcycle_helmet",
"categoryId": 92,
"attribute": 91
},
{
"id": 3,
"name": "hearing_muff",
"categoryId": 92,
"attribute": 122
},
{
"id": 4,
"name": "glasses",
"categoryId": 92,
"attribute": 97
},
{
"id": 5,
"name": "respiratory_protective_equipment",
"categoryId": 92,
"attribute": 123
},
{
"id": 6,
"name": "frontal_face",
"categoryId": 92,
"attribute": 108
},
{
"id": 7,
"name": "side_face",
"categoryId": 92,
"attribute": 108
},
{
"id": 8,
"name": "mask",
"categoryId": 92,
"attribute": 94
}
]
}

Endpoints


Import images

POST/dataset/image

Arguments

MULTIPART FORM UPLOAD
  • file binary required Binary Image to upload

Returns

Returns a success message

{
"status": "ok",
"message": "Gotcha"
}

Add category

POST/dataset/category

Arguments

BODY
  • id Int required Id of the category
  • supercategory String required Super category of the category
  • name String required Name of the category

Returns

Returns a success message

{
"status": "ok",
"message": "Gotcha"
}

Get annotation file

GET/dataset/annotation

Arguments

QUERY STRING PARAMETERS
  • cat List[String] required List of categories

Returns

Downloads a file named "annotations.json"


Get category file

GET/dataset/category

Arguments

QUERY STRING PARAMETERS
  • cat List[String] required List of categories

Returns

Downloads a file named "categories.json"


Create dataset

GET/dataset/complete

Arguments

BODY
  • name String Annotation file name in S3 bucket
  • email List[String] Email address to send callback
  • inimgcats List[String] Image categories to be included
  • eximgcats List[String] Image categories to be excluded
  • abeximgcats List[String] Image categories to be absolutely excluded
  • inlabelcats List[String] Label categories to be included
  • exlabelcats List[String] Label categories to be excluded
  • incamids List[UUID] Camera ids to be included
  • excamids List[UUID] Camera ids to be excluded
  • indatasets List[String] Datasets to be included
  • exdatasets List[String] Datasets to be excluded
  • inobjecttags List[String] Object tags to be included
  • exobjecttags List[String] Object tags to be excluded
  • shuffle Boolean Remove randomness
  • partitionRatio Float Proportion of the trainset to dataset, should be between 0 and 1
  • unlabelledRatio Float The ratio of unlabelled images
  • trainSize Int The total number of labelled images in the train set, "0" loads all images
  • useCache Boolean Use cache

Returns

Returns a success message and sends an email

{
"status": "ok",
"message": {
"url": "s3://bucketname/key",
"cacheHit": false
}
}

Annotation callback

POST/scale/callback/annotation

Arguments

QUERY STRING PARAMETERS
  • isTest Boolean optional
BODY
  • task Object[AnnotationTask] required
  • taskId String required
  • response String optional

Returns

{
"status": "ok",
"message": "Thanks!"
}

Create annotation task from dataset

POST/scale/callback/annotation

Arguments

BODY
  • bucket String required
  • folder String required
  • datasetName String optional
  • params Object[ScaleAnnotationParams] optional
    • objectsToAnnotate List[String]
    • instruction String
    • project String
    • batch `String
    • withLabels Boolean
    • minHeight Int
    • minWidth Int
    • attachmentType String
    • metadata Object]
    • layers Object

Returns

{
"status": "ok",
"message": "Initiating annotation task with given dataset ${datasetName}"
}