修改色准测试结果显示

app/plots/plot_accuracy.py

@@ -1,98 +1,33 @@
 """色准测试结果绘制。
 
-Step 2 重构：从 pqAutomationApp.PQAutomationApp.plot_accuracy 原样搬迁。
+布局：
+- 左侧：大尺寸 ColorChecker 条形图（每个条形使用对应颜色）。
+- 右侧：CIE 1976 u'v' 色度图（目标点/实测点/偏移连线）。
 """
 
-from matplotlib.patches import Rectangle
-
 from typing import TYPE_CHECKING
 
+from matplotlib.patches import Rectangle
+from matplotlib.lines import Line2D
+
+from app.plots.gamut_background import get_cie1976_background
+from app.tests.color_accuracy import get_accuracy_color_standards
+
 if TYPE_CHECKING:
     from pqAutomationApp import PQAutomationApp
 
 
+# ============================================================
+# 常量
+# ============================================================
 
-def plot_accuracy(self: "PQAutomationApp", accuracy_data, test_type):
+_COLOR_MAP = {
-    """绘制色准测试结果 - 29色显示 - 简洁版布局（显示 Gamma）"""
-
-    self.accuracy_ax.clear()
-    self.accuracy_ax.set_xlim(0, 1)
-    self.accuracy_ax.set_ylim(0, 1)
-    self.accuracy_ax.axis("off")
-
-    self.accuracy_fig.subplots_adjust(
-        left=0.05,
-        right=0.95,
-        top=0.95,
-        bottom=0.02,
-    )
-
-    # 获取色准数据
-    color_patches = accuracy_data.get("color_patches", [])
-    delta_e_values = accuracy_data.get("delta_e_values", [])
-    avg_delta_e = accuracy_data.get("avg_delta_e", 0)
-    max_delta_e = accuracy_data.get("max_delta_e", 0)
-    min_delta_e = accuracy_data.get("min_delta_e", 0)
-    excellent_count = accuracy_data.get("excellent_count", 0)
-    good_count = accuracy_data.get("good_count", 0)
-    poor_count = accuracy_data.get("poor_count", 0)
-
-    # 获取 Gamma 值
-    target_gamma = accuracy_data.get("target_gamma", 2.2)
-
-    test_type_name = self.get_test_type_name(test_type)
-
-    # ========== 标题（动态显示 Gamma）==========
-    if test_type == "sdr_movie":
-        title = f"{test_type_name} - 色准测试（全 29色 | Gamma {target_gamma}）"
-    elif test_type == "hdr_movie":
-        title = f"{test_type_name} - 色准测试（全 29色 | PQ EOTF）"
-    else:  # screen_module
-        title = f"{test_type_name} - 色准测试（全 29色 | Gamma {target_gamma}）"
-
-    self.accuracy_fig.suptitle(
-        title,
-        fontsize=11,
-        y=0.98,
-        fontweight="bold",
-        color="#111111",
-    )
-
-    # ========== 29色：6行5列布局 ==========
-    cols = 5
-    rows = 6
-
-    patch_width = 0.135
-    patch_height = 0.085
-    x_start = 0.08
-    y_start = 0.90
-    x_gap = 0.035
-    y_gap = 0.050
-
-    # ========== 绘制色块 ==========
-    for i, (color_name, delta_e) in enumerate(zip(color_patches, delta_e_values)):
-        row = i // cols
-        col = i % cols
-
-        x = x_start + col * (patch_width + x_gap)
-        y = y_start - row * (patch_height + y_gap)
-
-        # 颜色映射
-        color_map = {
-            # 灰阶
     "White": "#FFFFFF",
     "Gray 80": "#E6E6E6",
     "Gray 65": "#D1D1D1",
     "Gray 50": "#BABABA",
     "Gray 35": "#9E9E9E",
-            # 饱和色
+    "Black": "#000000",
-            "100% Red": "#FF0000",
-            "100% Green": "#00FF00",
-            "100% Blue": "#0000FF",
-            "100% Cyan": "#00FFFF",
-            "100% Magenta": "#FF00FF",
-            "100% Yellow": "#FFFF00",
-            # ColorChecker 颜色
     "Dark Skin": "#735242",
     "Light Skin": "#C29682",
     "Blue Sky": "#5E7A9C",
@@ -111,217 +46,245 @@ def plot_accuracy(self: "PQAutomationApp", accuracy_data, test_type):
     "Yellow (Legacy)": "#EDC721",
     "Magenta (Legacy)": "#BA5491",
     "Cyan (Legacy)": "#0085A3",
+    "100% Red": "#FF0000",
+    "100% Green": "#00FF00",
+    "100% Blue": "#0000FF",
+    "100% Cyan": "#00FFFF",
+    "100% Magenta": "#FF00FF",
+    "100% Yellow": "#FFFF00",
 }
 
-        patch_color = color_map.get(color_name, "#808080")
 
-        # ΔE 等级颜色
+def _grade_color(delta_e: float) -> str:
     if delta_e < 3:
-            edge_color = "green"
+        return "#1FAE45"   # 绿
-        elif delta_e < 5:
+    if delta_e < 5:
-            edge_color = "orange"
+        return "#E08A00"   # 橙
-        else:
+    return "#D81B1B"       # 红
-            edge_color = "red"
 
-        # 绘制色块
-        rect = Rectangle(
-            (x, y),
-            patch_width,
-            patch_height,
-            transform=self.accuracy_ax.transAxes,
-            facecolor=patch_color,
-            edgecolor=edge_color,
-            linewidth=1.8,
-        )
-        self.accuracy_ax.add_patch(rect)
 
-        # ========== 标注色块名称（上方）==========
+def _xy_to_uv(x: float, y: float):
-        self.accuracy_ax.text(
+    """CIE 1931 xy → CIE 1976 u'v'"""
-            x + patch_width / 2,
+    denom = -2.0 * x + 12.0 * y + 3.0
-            y + patch_height + 0.015,
+    if abs(denom) < 1e-10:
-            color_name,
+        return 0.0, 0.0
-            ha="center",
+    return (4.0 * x) / denom, (9.0 * y) / denom
-            va="bottom",
-            fontsize=5.5,
-            fontweight="bold",
-            transform=self.accuracy_ax.transAxes,
-            clip_on=False,
-        )
 
-        # ========== 标注 ΔE 值（中心）==========
-        dark_colors = [
-            "100% Red",
-            "100% Green",
-            "100% Blue",
-            "Gray 35",
-            "Dark Skin",
-            "Foliage",
-            "Purple",
-            "Purplish Blue",
-            "Blue (Legacy)",
-            "Green (Legacy)",
-            "Red (Legacy)",
-            "Magenta (Legacy)",
-            "Cyan (Legacy)",
-        ]
 
-        text_color = "white" if color_name in dark_colors else "black"
+# ============================================================
+# 子图：左侧 Calman 风格面板
+# ============================================================
 
-        self.accuracy_ax.text(
+def _draw_left_panel(ax, color_patches, delta_e_values):
-            x + patch_width / 2,
+    """左侧仅保留大条形图。"""
-            y + patch_height / 2,
+    ax.clear()
-            f"ΔE\n{delta_e:.2f}",
+
-            ha="center",
+    n = len(color_patches)
-            va="center",
+    if n == 0:
-            fontsize=5.2,
+        ax.set_axis_off()
-            fontweight="bold",
+        return
-            color=text_color,
+
-            transform=self.accuracy_ax.transAxes,
+    y_pos = list(range(n))
-            bbox=dict(
+    bar_colors = [_COLOR_MAP.get(name, "#888888") for name in color_patches]
-                boxstyle="round,pad=0.22",
+    edge_colors = [_grade_color(dE) for dE in delta_e_values]
-                facecolor="white" if text_color == "black" else "black",
+
-                alpha=0.75,
+    ax.barh(
-                edgecolor=edge_color,
+        y_pos,
+        delta_e_values,
+        height=0.72,
+        color=bar_colors,
+        edgecolor=edge_colors,
         linewidth=1.0,
-            ),
+        zorder=3,
     )
 
-    # ========== 统计信息卡片（只保留外框）==========
+    ax.set_yticks(y_pos)
-    card_width = 0.84
+    ax.set_yticklabels(color_patches, fontsize=7)
-    card_height = 0.15
+    ax.invert_yaxis()
-    card_x = 0.08
-    card_y = 0.01
 
-    info_card = Rectangle(
+    x_max = max(15.0, max(delta_e_values) * 1.15)
-        (card_x, card_y),
+    ax.set_xlim(0, x_max)
-        card_width,
+    ax.grid(axis="x", linestyle="-", linewidth=0.6, alpha=0.3, zorder=0)
-        card_height,
+    ax.grid(axis="y", linestyle=":", linewidth=0.35, alpha=0.15, zorder=0)
-        transform=self.accuracy_ax.transAxes,
+
-        facecolor="#F0F0F0",
+    ax.set_facecolor("#FFFFFF")
-        edgecolor="black",
+    for spine in ax.spines.values():
-        linewidth=1.5,
+        spine.set_color("#9A9A9A")
+        spine.set_linewidth(0.9)
+
+
+# ============================================================
+# 子图：CIE 1976 u'v' 色度图（目标 vs 实测）
+# ============================================================
+
+def _draw_uv_diagram(ax, color_patches, measurements, standards):
+    """绘制 CIE 1976 u'v' 上的色准对比。"""
+    ax.clear()
+    try:
+        bg, bbox = get_cie1976_background()
+        xmin, xmax, ymin, ymax = bbox
+        ax.imshow(
+            bg, extent=(xmin, xmax, ymin, ymax),
+            origin="upper", interpolation="bicubic",
+            zorder=0, aspect="auto",
         )
-    self.accuracy_ax.add_patch(info_card)
+        ax.set_xlim(xmin, xmax)
+        ax.set_ylim(ymin, ymax)
+    except Exception:
+        ax.set_xlim(0.0, 0.65)
+        ax.set_ylim(0.0, 0.60)
 
-    # ========== 标题（带说明）==========
+    ax.set_facecolor("#000")
-    self.accuracy_ax.text(
+    ax.set_aspect("equal", adjustable="box")
-        card_x + card_width / 2,
+    ax.set_title("CIE 1976 u'v'", fontsize=11, fontweight="bold",
-        card_y + card_height - 0.008,
+                 color="#111", pad=4)
-        "色准统计（5灰阶 + 18 ColorChecker + 6饱和色 | ΔE 2000 标准）",
+    ax.set_xlabel("u'", fontsize=9, color="#222", labelpad=1)
-        ha="center",
+    ax.set_ylabel("v'", fontsize=9, color="#222", labelpad=1)
-        va="top",
+    ax.tick_params(axis="both", labelsize=8, colors="#222")
-        fontsize=7.5,
+    for sp in ax.spines.values():
-        fontweight="bold",
+        sp.set_color("#666")
-        color="#111111",
+        sp.set_linewidth(0.9)
-        transform=self.accuracy_ax.transAxes,
+
+    for name, meas in zip(color_patches, measurements):
+        if meas is None or len(meas) < 2:
+            continue
+        mx, my = meas[0], meas[1]
+        sxy = standards.get(name)
+        if sxy is None:
+            continue
+        sx, sy = sxy
+
+        m_u, m_v = _xy_to_uv(mx, my)
+        s_u, s_v = _xy_to_uv(sx, sy)
+
+        face = _COLOR_MAP.get(name, "#FFFFFF")
+
+        # 目标点：仅空心方框（不填充标准颜色）
+        ax.scatter(
+            [s_u], [s_v],
+            s=56, marker="s",
+            facecolors="none", edgecolors="#FFFFFF",
+            linewidths=1.25, zorder=18,
+        )
+        # 实测点：白色外圈 + 内层圆点
+        ax.scatter(
+            [m_u], [m_v],
+            s=52, marker="o",
+            facecolors="none", edgecolors="#FFFFFF",
+            linewidths=1.0, zorder=19,
+        )
+        ax.scatter(
+            [m_u], [m_v],
+            s=24, marker="o",
+            facecolors=face, edgecolors="#111111",
+            linewidths=0.85, zorder=20,
         )
 
-    # ========== 统计内容（无内部框）==========
+    legend_handles = [
-    stats_y = card_y + card_height * 0.55
+        Line2D([0], [0], marker="s", linestyle="none",
-
+               markerfacecolor="#CCCCCC", markeredgecolor="#FFFFFF",
-    # 左侧：ΔE 统计
+               markersize=7, label="目标 (Target)"),
-    left_x = card_x + 0.02
+        Line2D([0], [0], marker="o", linestyle="none",
-    stats_text = [
+               markerfacecolor="#CCCCCC", markeredgecolor="#000000",
-        f"平均 ΔE: {avg_delta_e:.2f}",
+               markersize=7, label="实测 (Actual)"),
-        f"最大 ΔE: {max_delta_e:.2f}",
-        f"最小 ΔE: {min_delta_e:.2f}",
     ]
+    leg = ax.legend(
+        handles=legend_handles,
+        loc="lower right", fontsize=8,
+        framealpha=0.88, labelcolor="#FFF",
+    )
+    if leg is not None:
+        leg.get_frame().set_facecolor("#111")
+        leg.get_frame().set_edgecolor("#FFF")
+        leg.set_zorder(50)
 
-    for i, text in enumerate(stats_text):
+
-        self.accuracy_ax.text(
+def _draw_result_judgement(ax, accuracy_data):
-            left_x,
+    """底部结果条"""
-            stats_y - i * 0.030,
+    ax.clear()
-            text,
+    ax.set_xlim(0, 1)
-            ha="left",
+    ax.set_ylim(0, 1)
-            va="center",
+    ax.axis("off")
-            fontsize=7,
+
-            fontweight="bold",
+    avg = accuracy_data.get("avg_delta_e", 0.0)
-            color="#111111",
+    mx = accuracy_data.get("max_delta_e", 0.0)
-            transform=self.accuracy_ax.transAxes,
+
+    ax.add_patch(Rectangle(
+        (0.0, 0.10), 1.0, 0.80,
+        transform=ax.transAxes,
+        facecolor="#FFFFFF", edgecolor="#C6C6C6", linewidth=1.0,
+    ))
+
+    ax.text(
+        0.03, 0.50,
+        f"Avg dE2000: {avg:.2f}",
+        ha="left", va="center",
+        fontsize=20, fontweight="normal", color="#111111",
+        transform=ax.transAxes,
+    )
+    ax.text(
+        0.52, 0.50,
+        f"Max dE2000: {mx:.2f}",
+        ha="left", va="center",
+        fontsize=20, fontweight="normal", color="#111111",
+        transform=ax.transAxes,
     )
 
-    # 中间：色块统计
-    middle_x = card_x + card_width * 0.32
 
-    self.accuracy_ax.text(
+# ============================================================
-        middle_x,
+# 主入口
-        stats_y,
+# ============================================================
-        f"优秀 (ΔE<3): {excellent_count} 个",
-        ha="left",
-        va="center",
-        fontsize=7,
-        color="green",
-        fontweight="bold",
-        transform=self.accuracy_ax.transAxes,
-    )
 
-    self.accuracy_ax.text(
+def plot_accuracy(self: "PQAutomationApp", accuracy_data, test_type):
-        middle_x,
+    """绘制色准测试结果 - Calman 风格（色块 + CIE 1976 u'v' + 统计）。"""
-        stats_y - 0.030,
-        f"良好 (3≤ΔE<5): {good_count} 个",
-        ha="left",
-        va="center",
-        fontsize=7,
-        color="orange",
-        fontweight="bold",
-        transform=self.accuracy_ax.transAxes,
-    )
 
-    self.accuracy_ax.text(
+    fig = self.accuracy_fig
-        middle_x,
+    fig.clear()
-        stats_y - 0.060,
-        f"偏差 (ΔE≥5): {poor_count} 个",
-        ha="left",
-        va="center",
-        fontsize=7,
-        color="red",
-        fontweight="bold",
-        transform=self.accuracy_ax.transAxes,
-    )
 
-    # 右侧：总体评价
+    color_patches = accuracy_data.get("color_patches", []) or []
-    right_x = card_x + card_width - 0.02
+    delta_e_values = accuracy_data.get("delta_e_values", []) or []
+    measurements = accuracy_data.get("color_measurements", []) or []
 
-    if avg_delta_e < 2:
+    try:
-        grade = "专业级"
+        target_gamma = float(accuracy_data.get("target_gamma", 2.2))
-        grade_icon = "★★★"
+    except (TypeError, ValueError):
-        grade_color = "darkgreen"
+        target_gamma = 2.2
-    elif avg_delta_e < 3:
+
-        grade = "优秀"
+    test_type_name = self.get_test_type_name(test_type)
-        grade_icon = "OK"
+
-        grade_color = "green"
+    if test_type == "sdr_movie":
-    elif avg_delta_e < 5:
+        title = f"{test_type_name} - 色准测试（全 29色 | Gamma {target_gamma}）"
-        grade = "良好"
+    elif test_type == "hdr_movie":
-        grade_icon = "PASS"
+        title = f"{test_type_name} - 色准测试（全 29色 | PQ EOTF）"
-        grade_color = "orange"
     else:
-        grade = "需要校准"
+        title = f"{test_type_name} - 色准测试（全 29色 | Gamma {target_gamma}）"
-        grade_icon = "[Error]"
-        grade_color = "red"
 
-    self.accuracy_ax.text(
+    fig.suptitle(title, fontsize=11, y=0.975, fontweight="bold", color="#111")
-        right_x,
+
-        stats_y + 0.020,
+    gs = fig.add_gridspec(
-        "总体评价:",
+        2, 2,
-        ha="right",
+        width_ratios=[1.12, 1.0],
-        va="bottom",
+        height_ratios=[4.0, 0.62],
-        fontsize=7,
+        left=0.08, right=0.985,
-        fontweight="bold",
+        top=0.91, bottom=0.06,
-        color="#111111",
+        wspace=0.14, hspace=0.10,
-        transform=self.accuracy_ax.transAxes,
     )
 
-    self.accuracy_ax.text(
+    ax_left = fig.add_subplot(gs[0, 0])
-        right_x,
+    ax_uv = fig.add_subplot(gs[0, 1])
-        stats_y - 0.025,
+    ax_judge = fig.add_subplot(gs[1, :])
-        f"{grade} {grade_icon}",
+
-        ha="right",
+    # 兼容外部对 self.accuracy_ax 的引用
-        va="top",
+    self.accuracy_ax = ax_judge
-        fontsize=11,
+
-        fontweight="bold",
+    _draw_left_panel(ax_left, color_patches, delta_e_values)
-        color=grade_color,
+
-        transform=self.accuracy_ax.transAxes,
+    try:
-    )
+        standards = get_accuracy_color_standards(test_type)
+    except Exception:
+        standards = {}
+    _draw_uv_diagram(ax_uv, color_patches, measurements, standards)
+    _draw_result_judgement(ax_judge, accuracy_data)
 
     self.accuracy_canvas.draw()
     self.chart_notebook.select(self.accuracy_chart_frame)

tools/demo_accuracy_plot.py

@@ -0,0 +1,188 @@
+"""离线色准图 Demo。
+
+运行后会在 tools/demo_outputs/ 下生成一张 PNG，
+用于在没有 UCD 设备时预览当前色准图表的 Calman 风格布局。
+"""
+
+from __future__ import annotations
+
+import argparse
+import math
+import sys
+from pathlib import Path
+
+import matplotlib
+
+matplotlib.use("Agg")
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.rcParams["font.family"] = ["sans-serif"]
+plt.rcParams["font.sans-serif"] = ["Microsoft YaHei", "SimHei", "DejaVu Sans"]
+plt.rcParams["axes.unicode_minus"] = False
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+if str(REPO_ROOT) not in sys.path:
+    sys.path.insert(0, str(REPO_ROOT))
+
+from app.plots.plot_accuracy import plot_accuracy
+from app.tests.color_accuracy import (
+    calculate_delta_e_2000,
+    get_accuracy_color_standards,
+)
+
+
+COLOR_NAMES = [
+    "White",
+    "Gray 80",
+    "Gray 65",
+    "Gray 50",
+    "Gray 35",
+    "Dark Skin",
+    "Light Skin",
+    "Blue Sky",
+    "Foliage",
+    "Blue Flower",
+    "Bluish Green",
+    "Orange",
+    "Purplish Blue",
+    "Moderate Red",
+    "Purple",
+    "Yellow Green",
+    "Orange Yellow",
+    "Blue (Legacy)",
+    "Green (Legacy)",
+    "Red (Legacy)",
+    "Yellow (Legacy)",
+    "Magenta (Legacy)",
+    "Cyan (Legacy)",
+    "100% Red",
+    "100% Green",
+    "100% Blue",
+    "100% Cyan",
+    "100% Magenta",
+    "100% Yellow",
+]
+
+
+class _DummyNotebook:
+    def select(self, *_args, **_kwargs):
+        return None
+
+
+class _DummyCanvas:
+    def draw(self):
+        return None
+
+
+class _DemoApp:
+    def __init__(self, fig):
+        self.accuracy_fig = fig
+        self.accuracy_canvas = _DummyCanvas()
+        self.chart_notebook = _DummyNotebook()
+        self.accuracy_chart_frame = object()
+
+    def get_test_type_name(self, test_type):
+        mapping = {
+            "sdr_movie": "SDR Movie",
+            "hdr_movie": "HDR Movie",
+            "screen_module": "屏模组",
+        }
+        return mapping.get(test_type, str(test_type))
+
+
+def _build_demo_data(test_type: str = "sdr_movie"):
+    standards = get_accuracy_color_standards(test_type)
+    rng = np.random.default_rng(20260527)
+
+    measured = []
+    color_patches = []
+    delta_e_values = []
+
+    for idx, name in enumerate(COLOR_NAMES):
+        sx, sy = standards[name]
+
+        # 构造一些“看起来像真实测量”的偏移：
+        # 大部分点轻微偏移，少数点更明显，便于看出方向和等级差异。
+        if idx < 5:
+            offset_scale = 0.0012
+        elif idx < 23:
+            offset_scale = 0.0028
+        else:
+            offset_scale = 0.0045
+
+        angle = rng.uniform(0, 2 * math.pi)
+        radius = offset_scale * (0.55 + 0.85 * rng.random())
+        dx = math.cos(angle) * radius
+        dy = math.sin(angle) * radius
+
+        # 为了让图上连线不完全随机，给部分饱和色再加一点定向偏移。
+        if idx >= 23:
+            dx += 0.002 * (1 if idx % 2 == 0 else -1)
+            dy += 0.0015 * (1 if idx % 3 == 0 else -1)
+
+        mx = min(max(sx + dx, 0.0), 0.8)
+        my = min(max(sy + dy, 0.0), 0.9)
+
+        # 亮度也做一点微小变化，避免所有点完全同一层。
+        measured_lv = 70.0 + rng.normal(0, 4.0)
+        measured_lv = max(measured_lv, 1.0)
+
+        delta_e = calculate_delta_e_2000(mx, my, measured_lv, sx, sy)
+
+        measured.append((mx, my, measured_lv))
+        color_patches.append(name)
+        delta_e_values.append(delta_e)
+
+    avg_delta_e = float(np.mean(delta_e_values))
+    max_delta_e = float(np.max(delta_e_values))
+    min_delta_e = float(np.min(delta_e_values))
+
+    return {
+        "color_patches": color_patches,
+        "delta_e_values": delta_e_values,
+        "color_measurements": measured,
+        "avg_delta_e": avg_delta_e,
+        "max_delta_e": max_delta_e,
+        "min_delta_e": min_delta_e,
+        "excellent_count": sum(1 for value in delta_e_values if value < 3),
+        "good_count": sum(1 for value in delta_e_values if 3 <= value < 5),
+        "poor_count": sum(1 for value in delta_e_values if value >= 5),
+        "avg_delta_e_gray": float(np.mean(delta_e_values[0:5])),
+        "avg_delta_e_colorchecker": float(np.mean(delta_e_values[5:23])),
+        "avg_delta_e_saturated": float(np.mean(delta_e_values[23:29])),
+        "target_gamma": 2.2,
+    }
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Generate an offline color accuracy demo PNG.")
+    parser.add_argument(
+        "--output",
+        type=Path,
+        default=Path(__file__).resolve().parent / "demo_outputs" / "accuracy_demo.png",
+        help="Output PNG path.",
+    )
+    parser.add_argument(
+        "--test-type",
+        choices=["sdr_movie", "hdr_movie", "screen_module"],
+        default="sdr_movie",
+        help="Test type used for the title and standard color set.",
+    )
+    args = parser.parse_args()
+
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+
+    fig = plt.Figure(figsize=(14, 8), dpi=120, tight_layout=False)
+    app = _DemoApp(fig)
+    accuracy_data = _build_demo_data(args.test_type)
+
+    plot_accuracy(app, accuracy_data, args.test_type)
+    fig.savefig(args.output, dpi=220)
+
+    print(f"Saved demo image to: {args.output}")
+
+
+if __name__ == "__main__":
+    main()