from PIL import Image

import detection_utils as utils


DETECTIONS = [
    {
        "class_id": 0,
        "class_name": "person",
        "confidence": 0.9,
        "x1": 1.0,
        "y1": 2.0,
        "x2": 10.0,
        "y2": 20.0,
    },
    {
        "class_id": 2,
        "class_name": "car",
        "confidence": 0.7,
        "x1": 12.0,
        "y1": 4.0,
        "x2": 30.0,
        "y2": 18.0,
    },
    {
        "class_id": 2,
        "class_name": "car",
        "confidence": 0.5,
        "x1": 32.0,
        "y1": 5.0,
        "x2": 45.0,
        "y2": 17.0,
    },
]


def test_detection_summary_groups_and_sorts_classes():
    assert utils.build_detection_summary(DETECTIONS) == [
        ["car", 2, 0.6, 0.7],
        ["person", 1, 0.9, 0.9],
    ]


def test_street_indicators_are_transparent_counts():
    assert utils.build_street_indicators(DETECTIONS) == {
        "people": 1,
        "active_mobility": 1,
        "motor_vehicles": 2,
        "all_transport": 2,
    }


def test_detection_overlay_matches_input_size():
    image = Image.new("RGB", (60, 40), "white")
    rendered = utils.render_detection(image, DETECTIONS)
    assert rendered.size == image.size
    assert rendered.getpixel((1, 2)) != (255, 255, 255)


def test_label_boxes_avoid_existing_labels():
    first = utils._label_box([20, 30, 30, 40], 20, 10, (100, 100), [])
    second = utils._label_box([22, 30, 32, 40], 20, 10, (100, 100), [first])
    assert not utils._boxes_overlap(first, second)