"""
Class configuration for the eval_tools evaluation framework.

This is the single source of truth for all class definitions.
To adapt the evaluator to a different class taxonomy, only edit this file.

Current taxonomy matches ultralytics/cfg/datasets/mono3d_ground.yaml class_map.
"""

# ---------------------------------------------------------------------------
# ID → display name  (used by GT parser, reports, logging)
# Keep this aligned with the first-seen canonical name for each ID in
# ultralytics/cfg/datasets/mono3d_ground.yaml:class_map.
# ---------------------------------------------------------------------------
CLASS_NAMES: dict[int, str] = {
    0: "car",
    1: "suv",
    2: "pickup",
    3: "medium_car",
    4: "van",
    5: "bus",
    6: "truck",
    7: "special_vehicle",
    8: "unknown",
    9: "pedestrian",
    10: "bicyclist",
    11: "bicycle",
    12: "tricycle",
    13: "traffic_sign",
    14: "wheel",
    15: "plate",
    16: "face",
}

# Total number of classes
NUM_CLASSES: int = len(CLASS_NAMES)

# ---------------------------------------------------------------------------
# Raw label string → ID  (used by detection result parser)
# Supports all original annotation names that map to the same ID in
# ultralytics/cfg/datasets/mono3d_ground.yaml:class_map.
# ---------------------------------------------------------------------------
CLASS_NAME_TO_ID: dict[str, int] = {
    "car": 0,
    "suv": 1,
    "pickup": 2,
    "medium_car": 3,
    "van": 4,
    "bus": 5,
    "truck": 6,
    "tanker": 6,
    "large_truck": 6,
    "construction_vehicle": 6,
    "special_vehicle": 7,
    "unknown": 8,
    "pedestrian": 9,
    "bicyclist": 10,
    "motorcyclist": 10,
    "bicycle": 11,
    "motorcycle": 11,
    "tricycle": 12,
    "tricyclist": 12,
    "traffic_sign": 13,
    "wheel": 14,
    "plate": 15,
    "face": 16,
}

# ---------------------------------------------------------------------------
# 3D-annotated class IDs
#   face_3d_classes    [0-8]: vehicle-like classes with 4-face annotations
#                             (51-col / full JSON face fields)
#   complete_3d_classes[9-12]: pedestrian / rider / bike / trike classes with
#                              whole-box 3D only (19-col labels)
# ---------------------------------------------------------------------------
FACE_3D_CLASSES: list[int] = [0, 1, 2, 3, 4, 5, 6, 7, 8]
COMPLETE_3D_CLASSES: list[int] = [9, 10, 11, 12]
CLASSES_3D: list[int] = FACE_3D_CLASSES + COMPLETE_3D_CLASSES

# ---------------------------------------------------------------------------
# Report labels: which 3D classes appear in evaluation reports, and how they
# are labelled. vehicle_large / vehicle_small are legacy synthetic keys from
# Metrics3D's class-0 size split; under the current taxonomy they are displayed
# as CAR_LARGE / CAR_SMALL.
# ---------------------------------------------------------------------------
REPORT_3D_CLASS_LABELS: dict[str, str] = {
    "car":           "CAR",
    "vehicle_large": "CAR_LARGE",
    "vehicle_small": "CAR_SMALL",
    "suv":           "SUV",
    "pickup":        "PICKUP",
    "medium_car":    "MEDIUM_CAR",
    "van":           "VAN",
    "bus":           "BUS",
    "truck":         "TRUCK",
    "special_vehicle": "SPECIAL_VEHICLE",
    "unknown":       "UNKNOWN",
    "pedestrian":    "PEDESTRIAN",
    "bicyclist":     "BICYCLIST",
    "bicycle":       "BICYCLE",
    "tricycle":      "TRICYCLE",
}

# Ordered list of 3D class keys for iteration in comparison/report scripts.
# Includes the legacy size-split sub-buckets immediately after "car".
REPORT_3D_CLASS_KEYS: list[str] = list(REPORT_3D_CLASS_LABELS.keys())