{
    "types": {
        "box": {
            "x1": "T[float]",
            "y1": "T[float]",
            "x2": "T[float]",
            "y2": "T[float]"
        },
        "instance": {
            "name": "T[string]",
            "class": "T[integer]",
            "confidence": "T[float]",
            "box": "T[box]",
            "track_id": "? : T[integer]",
            "segments": "T[segments]"
        },
        "segments": {
            "x": [
                "T[float]"
            ],
            "y": [
                "T[float]"
            ]
        }
    },
    "enums": {},
    "structure": [
        "T[instance]"
    ],
    "notes": {
        "scope": "One image per call; top-level array of instances. No image path, dimensions or class-name lookup table in the JSON.",
        "coordinates": "Default: original-image pixel corner coordinates. normalize=True divides x by image width and y by height, including segmentation coordinates.",
        "precision": "Confidence and coordinates rounded to decimals (default 5). Class and tracking IDs are integers.",
        "tracking": "track_id is omitted for ordinary predictions; present for tracking results.",
        "empty": "No detections produces an empty array.",
        "implementation": "DataExportMixin.to_json serializes a Polars DataFrame built from Results.summary. Definition covers horizontal detection and instance segmentation only.",
        "segments": "Parallel x and y arrays, not an array of [x,y] pairs. Segments are included when masks exist; binary masks and holes are not encoded.",
        "id": "ultralytics-segment-json",
        "models": [
            "YOLO11-seg",
            "YOLO26-seg"
        ],
        "serialization": "application/json",
        "producer": "Results.to_json(normalize=False, decimals=5)",
        "sources": [
            {
                "url": "https://github.com/ultralytics/ultralytics/blob/8a55f07e379d0d0f66cc23d09e35f54588fd1435/ultralytics/engine/results.py",
                "revision": "8a55f07e379d0d0f66cc23d09e35f54588fd1435"
            },
            {
                "url": "https://github.com/ultralytics/ultralytics/blob/8a55f07e379d0d0f66cc23d09e35f54588fd1435/ultralytics/utils/__init__.py",
                "revision": "8a55f07e379d0d0f66cc23d09e35f54588fd1435"
            },
            {
                "url": "https://github.com/ultralytics/ultralytics/blob/8a55f07e379d0d0f66cc23d09e35f54588fd1435/ultralytics/models/yolo/segment/predict.py",
                "revision": "8a55f07e379d0d0f66cc23d09e35f54588fd1435"
            }
        ],
        "example": [
            {
                "name": "insect",
                "class": 0,
                "confidence": 0.9,
                "box": {
                    "x1": 10.0,
                    "y1": 20.0,
                    "x2": 50.0,
                    "y2": 60.0
                },
                "segments": {
                    "x": [
                        10.0,
                        50.0,
                        30.0
                    ],
                    "y": [
                        20.0,
                        20.0,
                        60.0
                    ]
                }
            }
        ]
    }
}