208 lines
8.1 KiB
Python
Executable File
208 lines
8.1 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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自动将单模型 evaluation_report.json 转换为中文 Markdown 评测报告。
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用法:
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python generate_eval_report.py <evaluation_report.json 路径>
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python generate_eval_report.py <evaluation_report.json 路径> --output <输出路径>
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python generate_eval_report.py <evaluation_report.json 路径> --model "模型名称" --date 2026-03-01
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示例:
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python eval_tools/model_comparison/generate_eval_report.py \
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evaluation_results/.../evaluation_report.json \
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--model yolov5s-300w-newdata-cncap
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"""
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import json
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import argparse
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import sys
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from datetime import date
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from pathlib import Path
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# Allow importing class_config from the eval_tools root
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from class_config import REPORT_3D_CLASS_LABELS
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def fmt(v: float, decimals: int = 4) -> str:
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return f"{v:.{decimals}f}"
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def fmt2(v: float) -> str:
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return f"{v:.2f}"
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def pct(v: float) -> str:
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return f"{v * 100:.1f}%"
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def build_report(data: dict, model_name: str, report_date: str) -> str:
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lines = []
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# ── 标题 ─────────────────────────────────────────────────────────────────
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lines.append(f"# 模型评测报告: {model_name}")
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lines.append("")
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lines.append(f"**模型**: {model_name} ")
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lines.append(f"**评测日期**: {report_date} ")
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eval_cfg = data.get("evaluation_config", {})
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if eval_cfg:
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lines.append(f"**置信度阈值 (P/R/F1)**: {eval_cfg.get('conf_threshold', '-')} ")
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lines.append(f"**IoU 阈值**: {eval_cfg.get('iou_threshold', '-')} ")
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lines.append(f"**AP 计算方法**: {eval_cfg.get('ap_method', '-')} ")
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lines.append("")
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lines.append("---")
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lines.append("")
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# ── 2D Overall ────────────────────────────────────────────────────────────
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ov2d = data["2d_evaluation"]["overall"]
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lines.append("## 📊 2D检测指标 (Overall)")
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lines.append("")
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lines.append("| 指标 | 数值 |")
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lines.append("|------|------|")
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lines.append(f"| **Precision** | {fmt(ov2d['precision'])} |")
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lines.append(f"| **Recall** | {fmt(ov2d['recall'])} |")
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lines.append(f"| **F1-Score** | {fmt(ov2d['f1_score'])} |")
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lines.append(f"| **mAP** | {fmt(ov2d['map'])} |")
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lines.append(f"| **TP** | {ov2d['tp']:,} |")
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lines.append(f"| **FP** | {ov2d['fp']:,} |")
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lines.append(f"| **FN** | {ov2d['fn']:,} |")
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lines.append("")
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# ── 2D Per-Class ──────────────────────────────────────────────────────────
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lines.append("## 📋 2D检测指标 (Per Class)")
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lines.append("")
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lines.append("| 类别 | Precision | Recall | F1 | AP | GT | TP | FP | FN |")
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lines.append("|------|-----------|--------|----|----|-----|-----|-----|-----|")
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pc2d = data["2d_evaluation"]["per_class"]
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for cls, cd in pc2d.items():
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lines.append(
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f"| **{cls}** | {fmt(cd['precision'])} | {fmt(cd['recall'])} "
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f"| {fmt(cd['f1_score'])} | {fmt(cd['ap'])} "
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f"| {cd['num_gt']:,} | {cd['tp']:,} | {cd['fp']:,} | {cd['fn']:,} |"
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)
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lines.append("")
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lines.append("---")
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lines.append("")
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# ── 3D Overall per class ──────────────────────────────────────────────────
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m3d = data.get("3d_evaluation", {})
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if not m3d:
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return "\n".join(lines)
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lines.append("## 🎯 3D检测指标")
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lines.append("")
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CLS_LABELS = REPORT_3D_CLASS_LABELS
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LONG_RANGES = ["long_0-10m", "long_10-20m", "long_20-30m", "long_30-40m",
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"long_40-50m", "long_50-60m", "long_60-70m", "long_70-80m",
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"long_80-90m", "long_90-100m", "long_100-999m"]
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for cls_key, cls_label in CLS_LABELS.items():
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if cls_key not in m3d:
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continue
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cd = m3d[cls_key]
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ov = cd["overall"]
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n = ov["num_samples"]
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lines.append(f"### {cls_label} ({n:,} 样本)")
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lines.append("")
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# Overall stats
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lines.append("#### 总体指标")
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lines.append("")
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lines.append("| 指标 | Mean | Median | Std | P90 |")
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lines.append("|------|------|--------|-----|-----|")
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def stat_row(label, key):
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s = ov[key]
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return (f"| **{label}** | {fmt2(s['mean'])} | {fmt2(s['median'])} "
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f"| {fmt2(s['std'])} | {fmt2(s['percentile_90'])} |")
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lines.append(stat_row("Lateral Error (m)", "lateral_error"))
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lines.append(stat_row("Longitudinal Error (m)", "longitudinal_error"))
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lines.append(stat_row("Long. Relative Error", "longitudinal_relative_error"))
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lines.append(stat_row("Heading Error (rad)", "heading_error"))
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lines.append(stat_row("Heading Error Relaxed", "heading_error_relaxed"))
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rev_pct = ov['reversal_percentage']
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lines.append(f"| **Reversal** | {ov['reversal_count']:,} ({rev_pct:.2f}%) | - | - | - |")
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lines.append("")
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# Distance range breakdown
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avail_ranges = [r for r in LONG_RANGES if r in cd]
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if avail_ranges:
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lines.append("#### 按距离分段 (纵向误差 Mean / Lateral Mean / Samples)")
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lines.append("")
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lines.append("| 距离段 | 样本数 | Lateral (m) | Longitudinal (m) | Long.Rel | Heading | Reversal% |")
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lines.append("|--------|--------|-------------|------------------|----------|---------|-----------|")
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for rng in avail_ranges:
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r = cd[rng]
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rov = r
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rn = rov["num_samples"]
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if rn == 0:
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continue
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lat = rov["lateral_error"]["mean"]
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lon = rov["longitudinal_error"]["mean"]
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lrel = rov["longitudinal_relative_error"]["mean"]
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hd = rov["heading_error"]["mean"]
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rev = rov["reversal_percentage"]
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lines.append(
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f"| {rng.replace('long_', '')} | {rn:,} | {fmt2(lat)} | {fmt2(lon)} "
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f"| {lrel:.3f} | {fmt2(hd)} | {rev:.1f}% |"
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)
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lines.append("")
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lines.append("---")
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lines.append("")
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return "\n".join(lines)
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def main():
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parser = argparse.ArgumentParser(
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description="将单模型 evaluation_report.json 转换为中文 Markdown 评测报告"
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)
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parser.add_argument("json_path", help="evaluation_report.json 的路径")
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parser.add_argument("--output", "-o", default=None,
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help="输出 Markdown 文件路径（默认与 JSON 同目录，文件名 EVALUATION_REPORT.md）")
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parser.add_argument("--model", default=None,
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help="模型名称（默认从目录名推断）")
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parser.add_argument("--date", default=str(date.today()),
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help="评测日期 (默认今天，格式 YYYY-MM-DD)")
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args = parser.parse_args()
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json_path = Path(args.json_path).resolve()
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if not json_path.exists():
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print(f"错误: 文件不存在: {json_path}", file=sys.stderr)
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sys.exit(1)
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with open(json_path, "r", encoding="utf-8") as f:
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data = json.load(f)
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# 从路径推断模型名称：取 json 所在目录的上级目录名
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if args.model:
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model_name = args.model
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else:
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# e.g. .../yolov5s-300w-newdata-cncap/20260228_102849/evaluation_report.json
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model_name = json_path.parent.parent.name
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if not model_name or model_name == ".":
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model_name = json_path.parent.name
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print(f"模型: {model_name}")
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report = build_report(data, model_name, args.date)
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if args.output:
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out_path = Path(args.output)
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else:
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out_path = json_path.parent / "EVALUATION_REPORT.md"
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out_path.write_text(report, encoding="utf-8")
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print(f"报告已生成: {out_path}")
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if __name__ == "__main__":
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main()
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