"""推理尺寸与训练尺寸的一致性校验。

回归：用 640 整图训练的权重跑 160 切片推理，结果看起来完全正常——照常出框、
照常有置信度，但类别系统性地错（实测 mosquito 的 TP 归零、599/760 被判成 blackdot）。
这种错误不会自己暴露，必须主动核对。
"""


from engine.tiled_inference import check_size_matches, training_imgsz


class _Model:
    def __init__(self, ckpt=None, overrides=None):
        if ckpt is not None:
            self.ckpt = ckpt
        if overrides is not None:
            self.overrides = overrides


def test_reads_imgsz_from_checkpoint():
    assert training_imgsz(_Model(ckpt={"train_args": {"imgsz": 640}})) == 640


def test_reads_imgsz_from_overrides():
    assert training_imgsz(_Model(overrides={"imgsz": 160})) == 160


def test_missing_imgsz_returns_none():
    assert training_imgsz(_Model()) is None
    assert training_imgsz(_Model(ckpt={})) is None


def test_mismatch_is_reported():
    message = check_size_matches(_Model(ckpt={"train_args": {"imgsz": 640}}), 160)
    assert message is not None
    assert "640" in message and "160" in message


def test_matching_sizes_are_silent():
    assert check_size_matches(_Model(ckpt={"train_args": {"imgsz": 160}}), 160) is None


def test_whole_image_mode_is_not_checked():
    """--tile-size 0 是显式退回整图推理，交给 ultralytics letterbox，不该报警。"""
    assert check_size_matches(_Model(ckpt={"train_args": {"imgsz": 640}}), 0) is None


def test_unknown_training_size_is_not_reported():
    """读不到就不报——宁可不说，也不误导。"""
    assert check_size_matches(_Model(), 160) is None


def test_logger_receives_the_warning():
    seen = []

    class _Logger:
        def warning(self, fmt, *args):
            seen.append(fmt % args)

    check_size_matches(_Model(overrides={"imgsz": 640}), 160, _Logger())
    assert seen and "不一致" in seen[0]