48 lines
1.7 KiB
Python
48 lines
1.7 KiB
Python
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"""与离线 demo main.py 同结构的段级文本报告（可选落盘）。"""
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from __future__ import annotations
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from pathlib import Path
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from app.services.tear_gated_segment_consumption.runner import TearGatedSegmentRecord
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def write_tear_segment_txt(
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*,
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path: Path,
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surgery_id: str,
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camera_id: str,
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labels_source: str,
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records: list[TearGatedSegmentRecord],
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) -> None:
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path.parent.mkdir(parents=True, exist_ok=True)
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lines: list[str] = []
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lines.append("耗材消耗推断（撕段模式 / FastAPI）")
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lines.append(f"手术: {surgery_id} camera: {camera_id}")
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lines.append(f"类名→label_id YAML: {labels_source}")
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lines.append(
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"说明: 人手检测 -> 撕二分类 -> 好帧门控(坏帧不判耗材) -> 41 类; "
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"段内为概率向量平均; 众数作展示对照"
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)
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lines.append("")
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for rec in records:
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line = "\t".join(
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[
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f"段{rec.segment_index}",
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f"时间戳(秒)={rec.mid_stream_sec:.3f};范围={rec.start_sec:.2f}~{rec.end_sec:.2f}",
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f"物品id={rec.item_id}",
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f"物品名称(模型top1)={rec.item_name}",
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f"top1置信度(段内平均)={rec.top1_conf:.4f}",
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f"top2={rec.top2_name}",
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f"top2_conf={rec.top2_conf:.4f}",
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f"top3={rec.top3_name}",
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f"top3_conf={rec.top3_conf:.4f}",
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f"段内众数(参考)={rec.majority_ref}",
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f"消耗数量=1",
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f"医生id=暂无",
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]
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)
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lines.append(line)
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lines.append("")
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path.write_text("\n".join(lines) + "\n", encoding="utf-8")
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