Cogniac
A JSON annotation format used by Cogniac.
Overview
The proprietary JSON annotation format used by the Cogniac computer vision platform.
Format Description
Below, learn the structure of Cogniac.
JSON
{
"frame": 0,
"filename": "./PATH_TO_FILE.ext",
"object_name_1": [
{
"class_name_1": {
"x0": 1334,
"x1": 1657,
"y0": 242,
"y1": 553,
"probability": 0.8974609375
},
"class_name_2": [],
"class_name_3": []
},
{
"class_name_1": {
"x0": 7,
"x1": 201,
"y0": 31,
"y1": 337,
"probability": 0.87353515625
},
"class_name_2": [
{
"text": "476240",
"x0": 137,
"x1": 156,
"y0": 128,
"y1": 206,
"probability": 0.755047082901001
}
],
"class_name_3": []
},
{
"class_name_1": {
"x0": 547,
"x1": 844,
"y0": 157,
"y1": 442,
"probability": 0.7021484375
},
"numbers": [],
"initials": []
}
],
"object_name_2": [],
"object_name_3": [],
"object_name_4": [
{
"text": "36",
"x0": 628,
"x1": 728,
"y0": 571,
"y1": 641,
"probability": 0.9057629108428955
},
{
"text": "37",
"x0": 987,
"x1": 1101,
"y0": 652,
"y1": 730,
"probability": 0.9051821231842041
},
{
"text": "38",
"x0": 1418,
"x1": 1542,
"y0": 757,
"y1": 839,
"probability": 0.9096717238426208
}
]
}Convert Data from Cogniac
- COCO JSON
- COCO Run-Length Encoding (RLE)
- CreateML JSON
- Florence-2
- Google Cloud AutoML Vision CSV
- meituan/yolov6
- Multiclass Classification CSV
- OpenAI CLIP Classification
- OpenAI GPT-4o Object Detection JSONL
- PaliGemma JSONL
- Pascal VOC XML
- RetinaNet Keras CSV
- Sagemaker GroundTruth Manifest
- Scaled-YOLOv4 TXT
- Segment Anything 2
- Tensorflow Object Detection CSV
- Tensorflow TFRecord
- YOLO Darknet TXT
- YOLO Keras TXT
- YOLOv10 PyTorch TXT
- YOLOv11 PyTorch TXT
- YOLOv4 PyTorch TXT
- YOLOv5 Oriented Bounding Boxes
- YOLOv5 PyTorch TXT
- YOLOv7 PyTorch TXT
- YOLOv8 Oriented Bounding Boxes
- YOLOv8 PyTorch TXT
- YOLOv9 PyTorch TXT