{
    "types": {
        "row": [
            "T[float]",
            "T[float]",
            "T[float]",
            "T[float]",
            "T[float]",
            "T[integer]"
        ]
    },
    "enums": {},
    "structure": {
        "pred": [
            [
                "T[row]"
            ]
        ],
        "xyxy": [
            [
                "T[row]"
            ]
        ],
        "xywh": [
            [
                "T[row]"
            ]
        ],
        "xyxyn": [
            [
                "T[row]"
            ]
        ],
        "xywhn": [
            [
                "T[row]"
            ]
        ],
        "files": [
            "T[string]"
        ],
        "names": "T[object] | [T[string]]"
    },
    "notes": {
        "scope": "Relevant fields of Detections; one tensor per image, not a JSON object. This is the AutoShape wrapper output, not the raw network forward output.",
        "columns": "All rows end in confidence, class. pred and xyxy begin x1,y1,x2,y2 in original pixels. xywh begins center_x,center_y,width,height in pixels. The n-suffixed views divide x/width by image width and y/height by image height.",
        "ids": "Class IDs occupy floating tensor entries; use names for their meaning.",
        "empty": "An image without detections has a zero-row tensor, not a missing batch entry.",
        "id": "yolov5-detect-results",
        "models": [
            "yolov5"
        ],
        "serialization": "Python object / tensors",
        "producer": "AutoShape.forward -> Detections",
        "sources": [
            {
                "url": "https://github.com/ultralytics/yolov5/blob/402e17ddf820996f51a191cbb798376e1144f069/models/common.py",
                "revision": "402e17ddf820996f51a191cbb798376e1144f069"
            }
        ],
        "representation": "Nested arrays describe the batch list and per-image tensor rows. They do not indicate JSON serialization. names is a class-index dictionary or an index-ordered list of class names, depending on the loaded model.",
        "numeric_storage": "Box tensors store floating-point entries, including class and tracking IDs. Those ID columns are declared integer because that is their expected safe cast target. Storage precision depends on the producer/runtime; consumers must preserve ID values during conversion."
    }
}