feat: 算法升级、整车配准集成与性能分析文档

算法更新: delivery v1.2.1、平整度v1.5、测距v2.2、整车配准v1.3
适配器: vehicle-registration 新增、各算法 manifest 和 adapter 更新
后端: taskCadFiles/source 字段迁移、derivedPointClouds 注册、取消任务联动
前端: ElapsedTime 时长显示、两步算法流程、canRun 逻辑修复
文档: 新增5份算法性能分析报告

alg/delivery_v1.2.1/underframe_deflection/visualization.py

@@ -0,0 +1,180 @@
+from __future__ import annotations
+
+from pathlib import Path
+
+import matplotlib
+
+matplotlib.use("Agg")
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from .beams import candidate_rows
+from .fitting import evaluate_line
+from .reference import evaluate_reference_line
+from .structures import FittedLine, FrameHypothesis, RepresentativePoint, SliceResult, TrackSolution
+
+
+def _sample_points(points: np.ndarray, limit: int) -> np.ndarray:
+    if len(points) <= limit:
+        return points
+    indices = np.linspace(0, len(points) - 1, limit, dtype=int)
+    return points[indices]
+
+
+def plot_frame_hypotheses(
+    hypotheses: list[FrameHypothesis],
+    output_path: str | Path,
+    dpi: int,
+) -> None:
+    fig, ax = plt.subplots(figsize=(10, 4.5))
+    names = [item.name for item in hypotheses]
+    scores = [item.score for item in hypotheses]
+    ax.bar(names, scores, color="#2f5c7e")
+    ax.set_title("Frame Hypothesis Scores")
+    ax.set_ylabel("Score")
+    ax.tick_params(axis="x", rotation=30)
+    fig.tight_layout()
+    fig.savefig(output_path, dpi=dpi)
+    plt.close(fig)
+
+
+def plot_roi_overview(
+    work_points_vehicle: np.ndarray,
+    roi_points_vehicle: np.ndarray,
+    output_path: str | Path,
+    dpi: int,
+    limit: int,
+) -> None:
+    full_sample = _sample_points(work_points_vehicle, limit)
+    roi_sample = _sample_points(roi_points_vehicle, limit)
+    fig, axes = plt.subplots(1, 2, figsize=(12, 5))
+    axes[0].scatter(full_sample[:, 0], full_sample[:, 2], s=1, c="#d3d3d3", alpha=0.6)
+    axes[0].scatter(roi_sample[:, 0], roi_sample[:, 2], s=1.5, c="#1f77b4", alpha=0.7)
+    axes[0].set_title("ROI in X-Z")
+    axes[0].set_xlabel("x (mm)")
+    axes[0].set_ylabel("z (mm)")
+    axes[1].scatter(full_sample[:, 1], full_sample[:, 2], s=1, c="#d3d3d3", alpha=0.6)
+    axes[1].scatter(roi_sample[:, 1], roi_sample[:, 2], s=1.5, c="#1f77b4", alpha=0.7)
+    axes[1].set_title("ROI in Y-Z")
+    axes[1].set_xlabel("y (mm)")
+    axes[1].set_ylabel("z (mm)")
+    fig.tight_layout()
+    fig.savefig(output_path, dpi=dpi)
+    plt.close(fig)
+
+
+def plot_beam_candidates(
+    slices: list[SliceResult],
+    left_track: TrackSolution | None,
+    right_track: TrackSolution | None,
+    output_path: str | Path,
+    dpi: int,
+) -> None:
+    rows = candidate_rows(slices)
+    fig, axes = plt.subplots(1, 2, figsize=(13, 5))
+    if rows:
+        x = np.asarray([row["x_center"] for row in rows])
+        y = np.asarray([row["y_center"] for row in rows])
+        z = np.asarray([row["z_low"] for row in rows])
+        colors = ["#4a90e2" if row["side"] == "left" else "#ff7f50" for row in rows]
+        axes[0].scatter(x, y, c=colors, s=10, alpha=0.45)
+        axes[1].scatter(x, z, c=colors, s=10, alpha=0.45)
+
+    for track, color in ((left_track, "#0b5394"), (right_track, "#b45f06")):
+        if not track:
+            continue
+        track_x = [candidate.x_center for candidate in track.candidates]
+        track_y = [candidate.y_center for candidate in track.candidates]
+        track_z = [candidate.z_low for candidate in track.candidates]
+        axes[0].plot(track_x, track_y, color=color, linewidth=2.5)
+        axes[1].plot(track_x, track_z, color=color, linewidth=2.5)
+
+    axes[0].set_title("Beam Candidate Bands and Tracks (X-Y)")
+    axes[0].set_xlabel("x (mm)")
+    axes[0].set_ylabel("y (mm)")
+    axes[1].set_title("Beam Candidate Bands and Tracks (X-Z)")
+    axes[1].set_xlabel("x (mm)")
+    axes[1].set_ylabel("z (mm)")
+    fig.tight_layout()
+    fig.savefig(output_path, dpi=dpi)
+    plt.close(fig)
+
+
+def plot_representatives_and_lines(
+    left_points: list[RepresentativePoint],
+    right_points: list[RepresentativePoint],
+    left_line: FittedLine | None,
+    right_line: FittedLine | None,
+    left_reference,
+    right_reference,
+    output_path: str | Path,
+    dpi: int,
+) -> None:
+    fig, axes = plt.subplots(1, 2, figsize=(13, 5))
+    for reps, color, label in (
+        (left_points, "#0b5394", "Left beam"),
+        (right_points, "#b45f06", "Right beam"),
+    ):
+        if not reps:
+            continue
+        x = np.asarray([item.x for item in reps])
+        y = np.asarray([item.y for item in reps])
+        z = np.asarray([item.z for item in reps])
+        axes[0].scatter(x, y, s=12, color=color, alpha=0.7, label=f"{label} reps")
+        axes[1].scatter(x, z, s=12, color=color, alpha=0.7, label=f"{label} reps")
+
+    for line, reference, color, label in (
+        (left_line, left_reference, "#0b5394", "Left beam"),
+        (right_line, right_reference, "#b45f06", "Right beam"),
+    ):
+        if line is None:
+            continue
+        x_grid = np.linspace(float(line.x_support.min()), float(line.x_support.max()), 300)
+        y, z, _ = evaluate_line(line, x_grid)
+        axes[0].plot(x_grid, y, color=color, linewidth=2.2, label=f"{label} fit")
+        axes[1].plot(x_grid, z, color=color, linewidth=2.2, label=f"{label} fit")
+        ref_eval, _ = evaluate_reference_line(reference, x_grid)
+        if np.ndim(ref_eval) == 2 and not np.isnan(ref_eval[:, 0]).all():
+            axes[0].plot(x_grid, ref_eval[:, 0], color=color, linestyle="--", linewidth=1.4)
+            axes[1].plot(x_grid, ref_eval[:, 1], color=color, linestyle="--", linewidth=1.4)
+
+    axes[0].set_title("Representative Points and Lines (X-Y)")
+    axes[0].set_xlabel("x (mm)")
+    axes[0].set_ylabel("y (mm)")
+    axes[1].set_title("Representative Points and Lines (X-Z)")
+    axes[1].set_xlabel("x (mm)")
+    axes[1].set_ylabel("z (mm)")
+    handles, labels = axes[0].get_legend_handles_labels()
+    if handles:
+        fig.legend(handles, labels, loc="upper center", ncol=4)
+    fig.tight_layout()
+    fig.savefig(output_path, dpi=dpi)
+    plt.close(fig)
+
+
+def plot_deflection_curves(
+    deflection_rows: list[dict],
+    output_path: str | Path,
+    dpi: int,
+) -> None:
+    fig, ax = plt.subplots(figsize=(11, 4.5))
+    if deflection_rows:
+        rows = deflection_rows
+        x = np.asarray([row["x"] for row in rows], dtype=np.float64)
+        left = np.asarray([row["left_deflection"] for row in rows], dtype=np.float64)
+        right = np.asarray([row["right_deflection"] for row in rows], dtype=np.float64)
+        if not np.isnan(left).all():
+            ax.plot(x, left, color="#0b5394", linewidth=2.0, label="Left deflection")
+        if not np.isnan(right).all():
+            ax.plot(x, right, color="#b45f06", linewidth=2.0, label="Right deflection")
+    ax.axhline(0.0, color="#666666", linewidth=1.0, linestyle=":")
+    ax.set_title("Deflection Curves")
+    ax.set_xlabel("x (mm)")
+    ax.set_ylabel("Deflection Δz (mm)")
+    handles, labels = ax.get_legend_handles_labels()
+    if handles:
+        ax.legend(loc="best")
+    fig.tight_layout()
+    fig.savefig(output_path, dpi=dpi)
+    plt.close(fig)