"""Object-detection tests with a fake YOLO predictor (no torch/weights)."""

from __future__ import annotations

import io

from fastapi.testclient import TestClient
from PIL import Image

from extractors.app import app
from extractors.features import detect


class _Box:
    def __init__(self, cls_id, conf, xyxy):
        self.cls = [cls_id]
        self.conf = [conf]
        self.xyxy = [xyxy]


class _Result:
    names = {0: "person", 2: "car"}

    def __init__(self, boxes):
        self.boxes = boxes


class FakeYOLO:
    def __init__(self, boxes):
        self._boxes = boxes

    def predict(self, img, **kwargs):
        return [_Result(self._boxes)]


def _png() -> bytes:
    buf = io.BytesIO()
    Image.new("RGB", (64, 64), (0, 0, 0)).save(buf, format="PNG")
    return buf.getvalue()


def test_summarize_counts():
    dets = [
        {"label": "person", "confidence": 0.9, "box": [0, 0, 10, 10]},
        {"label": "person", "confidence": 0.8, "box": [5, 5, 20, 20]},
        {"label": "car", "confidence": 0.7, "box": [0, 0, 30, 30]},
    ]
    res = detect._summarize(dets)
    assert res.results["count"] == 3
    assert res.results["by_label"] == {"person": 2, "car": 1}
    assert "person×2" in res.evidence[0]


def test_analyze_parses_and_sorts():
    fake = FakeYOLO([_Box(2, 0.6, [1, 1, 9, 9]), _Box(0, 0.95, [0, 0, 8, 8])])
    res = detect.analyze(_png(), model=fake)
    assert res.ok is True
    assert res.results["count"] == 2
    # sorted by confidence desc → person (0.95) first
    assert res.results["detections"][0]["label"] == "person"
    assert res.results["detections"][0]["confidence"] == 0.95


def test_analyze_empty_image():
    res = detect.analyze(b"", model=FakeYOLO([]))
    assert res.ok is False


def test_detect_endpoint_503_without_ml_extra():
    client = TestClient(app)
    r = client.post("/v1/detect", files={"file": ("x.png", _png(), "image/png")})
    assert r.status_code == 503


def test_detect_endpoint_with_monkeypatched_model(monkeypatch):
    monkeypatch.setattr(detect, "get_model", lambda: FakeYOLO([_Box(0, 0.9, [0, 0, 5, 5])]))
    client = TestClient(app)
    r = client.post("/v1/detect", files={"file": ("x.png", _png(), "image/png")})
    assert r.status_code == 200
    assert r.json()["results"]["by_label"] == {"person": 1}