"""StereoYoloFrontend 出口契约测试（需求说明 §2.2/§2.3/§2.5/§5）。

全部用注入的假检测器驱动：不需要模型权重、不需要图像素材、不需要硬件；
真并行用双人屏障断言（串行实现会屏障超时）。
"""

import logging
import threading

import numpy as np
import pytest

from stereo_ranger.types import Detection
from stereo_yolo import StereoYoloConfig, StereoYoloFrontend


class ScriptedDetector:
    """按调用顺序返回脚本项：list[Detection] 正常返回；Exception 抛出。"""

    def __init__(self, script):
        self._script = list(script)
        self.calls = 0

    def detect(self, image):
        self.calls += 1
        if not self._script:
            raise AssertionError("假检测器脚本已耗尽（调用次数多于预期）")
        item = self._script.pop(0)
        if isinstance(item, Exception):
            raise item
        return list(item)


class BarrierDetector:
    """两次调用必须同时在途（屏障超时即证明串行或单线程执行）。"""

    def __init__(self, barrier: threading.Barrier, detections):
        self._barrier = barrier
        self._detections = list(detections)

    def detect(self, image):
        self._barrier.wait(timeout=2.0)
        return list(self._detections)


def _img(fill=0, shape=(8, 8, 3)) -> np.ndarray:
    return np.full(shape, fill, dtype=np.uint8)


def _det(x1=1.0, y1=2.0, x2=11.0, y2=12.0, class_id=0, confidence=0.9, track_id=None) -> Detection:
    return Detection(x1, y1, x2, y2, confidence=confidence, class_id=class_id, track_id=track_id)


def _frontend(script, **cfg_kwargs) -> StereoYoloFrontend:
    kwargs = {"concurrency": "sequential"}
    kwargs.update(cfg_kwargs)
    return StereoYoloFrontend(StereoYoloConfig(**kwargs), detector=ScriptedDetector(script))


def test_frames_share_frame_id_and_keep_boxes():
    left_box, right_box = _det(1.0, 2.0, 11.0, 12.0, confidence=0.77), _det(3.0, 4.0, 13.0, 14.0)
    frontend = _frontend([[left_box], [right_box]])
    left_frame, right_frame = frontend.detect(_img(), _img(), frame_id=7)

    assert left_frame.frame_id == right_frame.frame_id == 7
    assert left_frame.detections == (left_box,)
    assert right_frame.detections == (right_box,)
    assert left_frame.detections[0].confidence == pytest.approx(0.77)
    assert left_frame.detections[0].track_id is None  # 无追踪器时留空（§2.1）
    assert frontend._detector.calls == 2


def test_whitelist_filters_by_class():
    frontend = _frontend([[_det(class_id=3)], [_det(class_id=0)]], class_whitelist=(0,))
    left_frame, right_frame = frontend.detect(_img(), _img(), frame_id=1)

    assert left_frame.detections == ()
    assert len(right_frame.detections) == 1 and right_frame.detections[0].class_id == 0


def test_no_whitelist_keeps_all_classes():
    frontend = _frontend([[_det(class_id=3)], [_det(class_id=5)]])
    left_frame, right_frame = frontend.detect(_img(), _img(), frame_id=1)

    assert len(left_frame.detections) == 1 and len(right_frame.detections) == 1


def test_degenerate_boxes_dropped(caplog):
    nan_box = _det(x1=float("nan"))
    zero_width = _det(x1=5.0, x2=5.0)
    inverted = _det(x1=20.0, x2=10.0)
    good = _det()
    frontend = _frontend([[nan_box, zero_width, inverted, good], []])

    with caplog.at_level(logging.WARNING, logger="stereo_yolo"):
        left_frame, right_frame = frontend.detect(_img(), _img(), frame_id=2)

    assert left_frame.detections == (good,)
    assert right_frame.detections == ()
    assert "丢弃退化检测框" in caplog.text
    assert "累计 1 次" in caplog.text


def test_boundary_touching_box_kept():
    hairline = _det(x1=10.0, x2=10.0 + 1e-9)
    frontend = _frontend([[hairline], []])
    left_frame, _ = frontend.detect(_img(), _img(), frame_id=3)
    assert left_frame.detections == (hairline,)


def test_one_eye_failure_isolated(caplog):
    good = _det()
    frontend = _frontend([[good], RuntimeError("boom")])

    with caplog.at_level(logging.WARNING, logger="stereo_yolo"):
        left_frame, right_frame = frontend.detect(_img(), _img(), frame_id=4)

    assert left_frame.detections == (good,)
    assert right_frame.detections == ()
    assert left_frame.frame_id == right_frame.frame_id == 4
    assert "右目推理失败" in caplog.text


def test_shape_mismatch_rejected(caplog):
    frontend = _frontend([])  # 脚本为空：若检测器被调用会抛断言

    with caplog.at_level(logging.WARNING, logger="stereo_yolo"):
        left_frame, right_frame = frontend.detect(_img(shape=(8, 8, 3)), _img(shape=(8, 6, 3)), frame_id=5)

    assert left_frame.detections == () and right_frame.detections == ()
    assert left_frame.frame_id == right_frame.frame_id == 5
    assert frontend._detector.calls == 0
    assert "左右图尺寸不一致" in caplog.text


def test_parallel_eyes_run_concurrently():
    barrier = threading.Barrier(2)
    box = _det()
    frontend = StereoYoloFrontend(
        StereoYoloConfig(concurrency="parallel"),
        detector=BarrierDetector(barrier, [box]),
    )
    try:
        left_frame, right_frame = frontend.detect(_img(), _img(), frame_id=6)
    finally:
        frontend.close()

    assert left_frame.detections == (box,)
    assert right_frame.detections == (box,)


def test_close_is_idempotent():
    frontend = StereoYoloFrontend(StereoYoloConfig(concurrency="parallel"), detector=ScriptedDetector([]))
    frontend.close()
    frontend.close()