102 lines
3.6 KiB
Python
102 lines
3.6 KiB
Python
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import pytest
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from app.algorithm_ipc.schema import WhitelistSpec
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from app.algorithm_runner.actionformer_gated.runner import ActionFormerSegmentRecord
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from app.algorithm_runner.segment_policy import (
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events_for_tear_record,
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pad_ranked_candidates_for_voice,
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rank_topk_for_candidates,
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)
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from app.domain.vision_prediction import PredictionCandidate
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from app.services.voice_confirm import build_prompt_text
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def test_rank_preserves_model_order_within_whitelist() -> None:
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"""清单顺序可能与模型置信度顺序不同；播报「第n个」应与模型 top1/top2 一致。"""
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topk = [
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PredictionCandidate(label="缝线", confidence=0.9),
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PredictionCandidate(label="纱布", confidence=0.5),
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]
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ordered = ["纱布", "缝线"]
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ranked = rank_topk_for_candidates(topk, ordered)
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assert [c.label for c in ranked] == ["缝线", "纱布"]
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def test_rank_without_candidates_keeps_model_order() -> None:
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topk = [
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PredictionCandidate(label="a", confidence=0.9),
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PredictionCandidate(label="b", confidence=0.5),
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]
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ranked = rank_topk_for_candidates(topk, [])
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assert [c.label for c in ranked] == ["a", "b"]
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def test_rank_drops_labels_not_on_surgery_whitelist() -> None:
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topk = [
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PredictionCandidate(label="缝线", confidence=0.9),
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PredictionCandidate(label="陌生类", confidence=0.5),
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PredictionCandidate(label="纱布", confidence=0.1),
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]
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ordered = ["纱布", "缝线"]
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ranked = rank_topk_for_candidates(topk, ordered)
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assert [c.label for c in ranked] == ["缝线", "纱布"]
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def test_pad_voice_options_fills_from_surgery_list() -> None:
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ranked = [PredictionCandidate(label="手套", confidence=0.88)]
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order = ["手套", "纱布", "缝线", "钳子"]
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out = pad_ranked_candidates_for_voice(ranked, order)
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assert [c.label for c in out] == ["手套", "纱布", "缝线"]
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assert out[0].confidence == pytest.approx(0.88)
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assert out[1].confidence == 0.0 and out[2].confidence == 0.0
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def test_pad_voice_respects_max_options() -> None:
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out = pad_ranked_candidates_for_voice([], ["a", "b", "c"], max_options=2)
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assert [c.label for c in out] == ["a", "b"]
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def test_events_for_tear_record_voice_has_three_options(monkeypatch: pytest.MonkeyPatch) -> None:
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from app.baked import pipeline as p
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monkeypatch.setattr(p, "VOICE_CONFIRMATION_ENABLED", True, raising=False)
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monkeypatch.setattr(p, "VIDEO_AUTO_CONFIRM_CONFIDENCE", 0.99, raising=False)
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monkeypatch.setattr(p, "VIDEO_VOICE_CONFIRM_MIN_CONFIDENCE", 0.1, raising=False)
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wl = WhitelistSpec(
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candidate_consumables=["手套", "纱布", "缝线"],
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name_to_id={"手套": "g1", "纱布": "g2", "缝线": "g3"},
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)
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rec = ActionFormerSegmentRecord(
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segment_index=1,
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start_sec=0.0,
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end_sec=2.0,
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mid_stream_sec=1.0,
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item_id="g1",
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item_name="手套",
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top1_conf=0.55,
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top2_name="",
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top2_conf=0.0,
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top3_name="",
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top3_conf=0.0,
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majority_ref="",
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)
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evs = events_for_tear_record(
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rec,
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wl=wl,
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camera_id="cam",
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wall_lo=100.0,
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wall_hi=102.0,
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cooldown_key="k",
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)
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assert len(evs) == 1
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assert evs[0]["type"] == "needs_voice_confirm"
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opts = evs[0]["options"]
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assert len(opts) == 3
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assert [o["label"] for o in opts] == ["手套", "纱布", "缝线"]
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text = build_prompt_text([(str(o["label"]), float(o["confidence"])) for o in opts])
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assert "第1个，手套。" in text
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assert "第2个，纱布。" in text
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assert "第3个，缝线。" in text
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