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快捷工具处添加比例尺开关

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李伟
2026-05-13 09:04:14 +08:00
parent f5f449b6fc
commit b9106acdf0
8 changed files with 392 additions and 15 deletions
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XP.ImageProcessing.Processors/定位识别/TemplateMatchingProcessor.cs
+162 -9
View File
@@ -22,18 +22,44 @@ namespace XP.ImageProcessing.Processors;
/// <summary>
/// 模板匹配算子（定位识别）
/// </summary>
/// <remarks>
/// 算法原理：
/// 模板匹配是一种基于图像块的匹配方法，通过在待搜索图像上滑动模板，
/// 计算每个位置与模板的相似度，找到最佳匹配位置。
///
/// 匹配方法说明：
/// 1. CcoeffNormed (归一化相关系数) - 推荐使用，对光照变化有一定的鲁棒性
/// 公式: corr = Σ(I(x,y) * T(x,y)) / sqrt(ΣI² * ΣT²)
/// 分数范围: -1 ~ 1，值越大越相似
///
/// 2. SqdiffNormed (归一化平方差) - 值越小越相似
/// 公式: diff = Σ(I(x,y) - T(x,y))² / (ΣI² + ΣT²)
/// 分数范围: 0 ~ 1，值越小越相似
///
/// 3. CcorrNormed (归一化相关) - 对模板和图像的亮度变化敏感
/// 4. Ccoeff (相关系数) - 未归一化版本
/// 5. Ccorr (相关) - 未归一化版本
/// 6. Sqdiff (平方差) - 未归一化版本
///
/// 性能说明：
/// - 时间复杂度: O(W * H * w * h)，其中W/H为图像尺寸，w/h为模板尺寸
/// - 可通过设置SearchRegion限制搜索范围来提升性能
/// </remarks>
public class TemplateMatchingProcessor : ImageProcessorBase
{
private static readonly ILogger _logger = Log.ForContext<TemplateMatchingProcessor>();
/// <summary>
/// 匹配方法选项列表，供UI下拉选择
/// </summary>
private static readonly string[] MatchMethodOptions =
{
"CcoeffNormed",
"SqdiffNormed",
"CcorrNormed",
"Ccoeff",
"Ccorr",
"Sqdiff"
"CcoeffNormed", // 归一化相关系数（推荐）
"SqdiffNormed", // 归一化平方差
"CcorrNormed", // 归一化相关
"Ccoeff", // 相关系数
"Ccorr", // 相关
"Sqdiff" // 平方差
};
public TemplateMatchingProcessor()
@@ -42,8 +68,16 @@ public class TemplateMatchingProcessor : ImageProcessorBase
Description = LocalizationHelper.GetString("TemplateMatchingProcessor_Description");
}
/// <summary>
/// 初始化参数定义
/// </summary>
protected override void InitializeParameters()
{
// ===== 模板相关参数 =====
/// <summary>
/// 模板图片路径，支持灰度或彩色图片（自动转灰度）
/// </summary>
Parameters.Add("TemplatePath", new ProcessorParameter(
"TemplatePath",
LocalizationHelper.GetString("TemplateMatchingProcessor_TemplatePath"),
@@ -53,25 +87,36 @@ public class TemplateMatchingProcessor : ImageProcessorBase
null,
LocalizationHelper.GetString("TemplateMatchingProcessor_TemplatePath_Desc")));
/// <summary>
/// 匹配算法选择，不同算法对光照和旋转的敏感度不同
/// </summary>
Parameters.Add("MatchMethod", new ProcessorParameter(
"MatchMethod",
LocalizationHelper.GetString("TemplateMatchingProcessor_MatchMethod"),
typeof(string),
"CcoeffNormed",
"CcoeffNormed", // 默认使用归一化相关系数
null,
null,
LocalizationHelper.GetString("TemplateMatchingProcessor_MatchMethod_Desc"),
MatchMethodOptions));
/// <summary>
/// 匹配阈值，判断匹配是否成功的分数门限
/// - CcoeffNormed/CcorrNormed: 建议 0.75-0.95
/// - SqdiffNormed: 建议 0.1-0.3
/// </summary>
Parameters.Add("MatchThreshold", new ProcessorParameter(
"MatchThreshold",
LocalizationHelper.GetString("TemplateMatchingProcessor_MatchThreshold"),
typeof(double),
0.75,
0.75, // 默认阈值
0.0,
1.0,
LocalizationHelper.GetString("TemplateMatchingProcessor_MatchThreshold_Desc")));
/// <summary>
/// 是否在输出图像上绘制匹配矩形框
/// </summary>
Parameters.Add("DrawRectangle", new ProcessorParameter(
"DrawRectangle",
LocalizationHelper.GetString("TemplateMatchingProcessor_DrawMatch"),
@@ -81,6 +126,9 @@ public class TemplateMatchingProcessor : ImageProcessorBase
null,
LocalizationHelper.GetString("TemplateMatchingProcessor_DrawMatch_Desc")));
/// <summary>
/// 匹配矩形框的线条粗细
/// </summary>
Parameters.Add("RectangleThickness", new ProcessorParameter(
"RectangleThickness",
LocalizationHelper.GetString("TemplateMatchingProcessor_RectThickness"),
@@ -90,6 +138,11 @@ public class TemplateMatchingProcessor : ImageProcessorBase
8,
LocalizationHelper.GetString("TemplateMatchingProcessor_RectThickness_Desc")));
// ===== 搜索区域参数（可选，用于限制搜索范围提升性能）=====
/// <summary>
/// 搜索区域左上角X坐标
/// </summary>
Parameters.Add("SearchRegionX", new ProcessorParameter(
"SearchRegionX",
LocalizationHelper.GetString("TemplateMatchingProcessor_SearchRegionX"),
@@ -99,6 +152,9 @@ public class TemplateMatchingProcessor : ImageProcessorBase
null,
LocalizationHelper.GetString("TemplateMatchingProcessor_SearchRegion_Desc")));
/// <summary>
/// 搜索区域左上角Y坐标
/// </summary>
Parameters.Add("SearchRegionY", new ProcessorParameter(
"SearchRegionY",
LocalizationHelper.GetString("TemplateMatchingProcessor_SearchRegionY"),
@@ -108,6 +164,9 @@ public class TemplateMatchingProcessor : ImageProcessorBase
null,
LocalizationHelper.GetString("TemplateMatchingProcessor_SearchRegion_Desc")));
/// <summary>
/// 搜索区域宽度，0表示使用整幅图像
/// </summary>
Parameters.Add("SearchRegionWidth", new ProcessorParameter(
"SearchRegionWidth",
LocalizationHelper.GetString("TemplateMatchingProcessor_SearchRegionWidth"),
@@ -117,6 +176,9 @@ public class TemplateMatchingProcessor : ImageProcessorBase
null,
LocalizationHelper.GetString("TemplateMatchingProcessor_SearchRegion_Desc")));
/// <summary>
/// 搜索区域高度，0表示使用整幅图像
/// </summary>
Parameters.Add("SearchRegionHeight", new ProcessorParameter(
"SearchRegionHeight",
LocalizationHelper.GetString("TemplateMatchingProcessor_SearchRegionHeight"),
@@ -129,8 +191,14 @@ public class TemplateMatchingProcessor : ImageProcessorBase
_logger.Debug("InitializeParameters");
}
/// <summary>
/// 执行模板匹配处理
/// </summary>
/// <param name="inputImage">输入的灰度图像</param>
/// <returns>处理后的图像（可选带匹配矩形框）</returns>
public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
{
// ===== 1. 获取参数 =====
var path = (GetParameter<string>("TemplatePath") ?? string.Empty).Trim();
var methodName = GetParameter<string>("MatchMethod") ?? "CcoeffNormed";
var threshold = GetParameter<double>("MatchThreshold");
@@ -141,10 +209,13 @@ public class TemplateMatchingProcessor : ImageProcessorBase
var searchRw = GetParameter<int>("SearchRegionWidth");
var searchRh = GetParameter<int>("SearchRegionHeight");
// 清除上一次的输出数据
OutputData.Clear();
// 克隆输入图像用于输出（避免修改原图）
var output = inputImage.Clone();
// ===== 2. 参数校验：模板文件 =====
if (string.IsNullOrEmpty(path) || !File.Exists(path))
{
_logger.Warning("TemplateMatching: invalid or missing template file: {Path}", path);
@@ -153,6 +224,7 @@ public class TemplateMatchingProcessor : ImageProcessorBase
return output;
}
// ===== 3. 加载模板图像 =====
using var template = LoadTemplate(path);
if (template == null)
{
@@ -161,17 +233,24 @@ public class TemplateMatchingProcessor : ImageProcessorBase
return output;
}
// ===== 4. 确定搜索区域（ROI）=====
// 如果未指定搜索区域，则使用整幅图像
var searchRoi = ResolveSearchRoi(inputImage.Width, inputImage.Height, searchRx, searchRy, searchRw, searchRh);
var offsetX = searchRoi.X;
var offsetX = searchRoi.X; // 记录ROI偏移，用于还原到全局坐标
var offsetY = searchRoi.Y;
// ===== 5. 在ROI区域内执行模板匹配 =====
Image<Gray, byte>? roiImage = null;
try
{
// 设置输入图像的ROI（感兴趣区域）
inputImage.ROI = searchRoi;
// 复制ROI区域到新图像
roiImage = inputImage.Copy();
// 清除ROI设置
inputImage.ROI = Rectangle.Empty;
// ===== 5.1 校验模板尺寸 =====
if (template.Width > roiImage.Width || template.Height > roiImage.Height)
{
_logger.Warning("TemplateMatching: template larger than search region ({Tw}x{Th} vs {Iw}x{Ih})",
@@ -181,20 +260,34 @@ public class TemplateMatchingProcessor : ImageProcessorBase
return output;
}
// ===== 5.2 执行模板匹配 =====
// OpenCV MatchTemplate 在ROI上滑动模板，计算每个位置的相似度
// 结果是一个 (W-w+1) x (H-h+1) 的分数矩阵
var method = ParseMethod(methodName);
using var resultMat = new Mat();
CvInvoke.MatchTemplate(roiImage, template, resultMat, method);
// ===== 5.3 找到最佳匹配位置 =====
// MinMaxLoc 在分数矩阵中找到最小值和最大值的位置
double minVal = 0, maxVal = 0;
Point minLoc = default, maxLoc = default;
CvInvoke.MinMaxLoc(resultMat, ref minVal, ref maxVal, ref minLoc, ref maxLoc);
// 根据匹配方法选择使用最小值还是最大值
// 平方差类方法：值越小越好（使用minLoc）
// 相关类方法：值越大越好（使用maxLoc）
var useMin = method == TemplateMatchingType.Sqdiff || method == TemplateMatchingType.SqdiffNormed;
var loc = useMin ? minLoc : maxLoc;
var score = useMin ? minVal : maxVal;
// ===== 5.4 判定匹配是否成功 =====
var matched = IsMatchAcceptable(method, minVal, maxVal, threshold);
// ===== 5.5 转换到全局坐标 =====
// 由于是在ROI内匹配的，需要加上ROI的偏移量
var globalLoc = new Point(loc.X + offsetX, loc.Y + offsetY);
// ===== 5.6 输出结果数据 =====
OutputData["Matched"] = matched;
OutputData["MatchScore"] = score;
OutputData["MatchX"] = globalLoc.X;
@@ -203,6 +296,7 @@ public class TemplateMatchingProcessor : ImageProcessorBase
OutputData["TemplateHeight"] = template.Height;
OutputData["MatchMethod"] = methodName;
// ===== 5.7 可选：绘制匹配矩形 =====
if (matched && draw)
{
var rect = new Rectangle(globalLoc.X, globalLoc.Y, template.Width, template.Height);
@@ -216,34 +310,71 @@ public class TemplateMatchingProcessor : ImageProcessorBase
}
finally
{
// 释放ROI图像资源
roiImage?.Dispose();
}
}
/// <summary>
/// 计算实际的搜索ROI区域
/// </summary>
/// <param name="imgW">图像宽度</param>
/// <param name="imgH">图像高度</param>
/// <param name="rx">用户指定的ROI X坐标</param>
/// <param name="ry">用户指定的ROI Y坐标</param>
/// <param name="rw">用户指定的ROI宽度，0表示整幅图像</param>
/// <param name="rh">用户指定的ROI高度，0表示整幅图像</param>
/// <returns>计算后的有效ROI区域</returns>
private static Rectangle ResolveSearchRoi(int imgW, int imgH, int rx, int ry, int rw, int rh)
{
// 宽度或高度为0时，使用整幅图像作为搜索区域
if (rw <= 0 || rh <= 0)
return new Rectangle(0, 0, imgW, imgH);
// 限制坐标在图像范围内
rx = Math.Clamp(rx, 0, Math.Max(0, imgW - 1));
ry = Math.Clamp(ry, 0, Math.Max(0, imgH - 1));
// 限制宽度和高度不超出图像边界
rw = Math.Clamp(rw, 1, Math.Max(1, imgW - rx));
rh = Math.Clamp(rh, 1, Math.Max(1, imgH - ry));
return new Rectangle(rx, ry, rw, rh);
}
/// <summary>
/// 判断匹配结果是否满足阈值条件
/// </summary>
/// <param name="method">匹配方法类型</param>
/// <param name="minVal">最小相似度分数</param>
/// <param name="maxVal">最大相似度分数</param>
/// <param name="threshold">用户设定的阈值</param>
/// <returns>是否满足匹配条件</returns>
/// <remarks>
/// 不同匹配方法的分数含义不同：
/// - 平方差类(Sqdiff/SqdiffNormed): 分数越小越相似，需要 minVal <= threshold
/// - 相关类(Ccoeff/Ccorr/CcoeffNormed/CcorrNormed): 分数越大越相似，需要 maxVal >= threshold
/// </remarks>
private static bool IsMatchAcceptable(TemplateMatchingType method, double minVal, double maxVal, double threshold)
{
return method switch
{
// 平方差类：值越小越好
TemplateMatchingType.SqdiffNormed => minVal <= threshold,
TemplateMatchingType.Sqdiff => minVal <= threshold,
// 相关类：值越大越好
TemplateMatchingType.CcorrNormed or TemplateMatchingType.CcoeffNormed => maxVal >= threshold,
TemplateMatchingType.Ccorr or TemplateMatchingType.Ccoeff => maxVal >= threshold,
// 默认按相关类处理
_ => maxVal >= threshold
};
}
/// <summary>
/// 将字符串方法名转换为OpenCV枚举类型
/// </summary>
/// <param name="name">方法名称字符串</param>
/// <returns>对应的TemplateMatchingType枚举值</returns>
private static TemplateMatchingType ParseMethod(string? name)
{
return name?.Trim() switch
@@ -253,23 +384,45 @@ public class TemplateMatchingProcessor : ImageProcessorBase
"Ccorr" => TemplateMatchingType.Ccorr,
"CcorrNormed" => TemplateMatchingType.CcorrNormed,
"Ccoeff" => TemplateMatchingType.Ccoeff,
// 默认返回归一化相关系数（推荐）
_ => TemplateMatchingType.CcoeffNormed
};
}
/// <summary>
/// 从磁盘加载模板图像并转换为灰度图
/// </summary>
/// <param name="path">模板图片文件路径</param>
/// <returns>灰度模板图像，加载失败返回null</returns>
/// <remarks>
/// 支持的输入格式：
/// - 灰度图像：直接使用
/// - 彩色图像：自动转换为灰度
/// - 支持任意位深度的图像
/// </remarks>
private static Image<Gray, byte>? LoadTemplate(string path)
{
try
{
// 使用任意格式读取（支持灰度、彩色、16位等）
using var raw = CvInvoke.Imread(path, ImreadModes.AnyDepth | ImreadModes.AnyColor);
if (raw.IsEmpty)
return null;
// 创建灰度图像
var templ = new Image<Gray, byte>(raw.Width, raw.Height);
// 根据通道数决定是否需要灰度转换
if (raw.NumberOfChannels == 1)
{
// 已经是灰度图，直接复制
raw.CopyTo(templ.Mat);
}
else
{
// 彩色图转灰度 (BGR -> Gray)
CvInvoke.CvtColor(raw, templ, ColorConversion.Bgr2Gray);
}
return templ;
}
XP.ImageProcessing.RoiControl/Controls/PolygonRoiCanvas.xaml
+90
View File
@@ -14,6 +14,7 @@
<UserControl.Resources>
<behaviors:PointListToPointCollectionConverter x:Key="PointListToPointCollectionConverter" />
<converters:ROITypeToVisibilityConverter x:Key="ROITypeToVisibilityConverter" />
<BooleanToVisibilityConverter x:Key="BoolToVisibilityConverter" />
</UserControl.Resources>
<Border BorderBrush="Transparent" BorderThickness="1" ClipToBounds="True">
<Grid>
@@ -71,6 +72,95 @@
</DataTemplate>
</ItemsControl.ItemTemplate>
</ItemsControl>
<!-- 比例尺：位于图像坐标系内，随 LayoutTransform（缩放）与 RenderTransform（平移）与底图一致 -->
<Grid
x:Name="ScaleBarOverlay"
Canvas.Left="0"
Canvas.Top="0"
Width="{Binding CanvasWidth, ElementName=root}"
Height="{Binding CanvasHeight, ElementName=root}"
Panel.ZIndex="10000"
IsHitTestVisible="False"
Visibility="{Binding ShowScaleBar, ElementName=root, Converter={StaticResource BoolToVisibilityConverter}}">
<Border
Margin="0,0,0,12"
Padding="0"
HorizontalAlignment="Center"
VerticalAlignment="Bottom"
Background="Transparent">
<StackPanel VerticalAlignment="Bottom" Orientation="Horizontal">
<!-- 尺身：底线 + 端部刻度 + 内侧无刻度竖线 -->
<Grid
x:Name="ScaleBarTrack"
Height="18"
MinWidth="8"
VerticalAlignment="Bottom"
Width="{Binding ScaleBarLengthPixels, ElementName=root}">
<Line
X1="0"
Y1="16"
X2="{Binding ScaleBarLengthPixels, ElementName=root}"
Y2="16"
Stroke="Red"
StrokeThickness="2"
SnapsToDevicePixels="True" />
<Line
X1="0"
X2="0"
Y1="9"
Y2="16"
Stroke="Red"
StrokeThickness="1.5"
SnapsToDevicePixels="True" />
<Line
X1="{Binding ScaleBarLengthPixels, ElementName=root}"
X2="{Binding ScaleBarLengthPixels, ElementName=root}"
Y1="9"
Y2="16"
Stroke="Red"
StrokeThickness="1.5"
SnapsToDevicePixels="True" />
<ItemsControl ItemsSource="{Binding ScaleBarMinorTickXs, ElementName=root}">
<ItemsControl.ItemsPanel>
<ItemsPanelTemplate>
<Canvas
IsItemsHost="True"
Width="{Binding ScaleBarLengthPixels, ElementName=root}"
Height="18"
ClipToBounds="False" />
</ItemsPanelTemplate>
</ItemsControl.ItemsPanel>
<ItemsControl.ItemContainerStyle>
<Style TargetType="ContentPresenter">
<Setter Property="Canvas.Left" Value="{Binding}" />
<Setter Property="Canvas.Top" Value="0" />
</Style>
</ItemsControl.ItemContainerStyle>
<ItemsControl.ItemTemplate>
<DataTemplate>
<Line
X1="0"
X2="0"
Y1="11"
Y2="16"
Stroke="Red"
StrokeThickness="1"
SnapsToDevicePixels="True" />
</DataTemplate>
</ItemsControl.ItemTemplate>
</ItemsControl>
</Grid>
<TextBlock
Margin="6,0,0,0"
VerticalAlignment="Center"
FontSize="11"
FontWeight="SemiBold"
Foreground="Red"
Text="{Binding ScaleBarCaption, ElementName=root}" />
</StackPanel>
</Border>
</Grid>
</Canvas>
</Grid>
XP.ImageProcessing.RoiControl/Controls/PolygonRoiCanvas.xaml.cs
+119 -2
View File
@@ -19,6 +19,9 @@ namespace XP.ImageProcessing.RoiControl.Controls
private const double ZoomStep = 1.2;
private Adorner? currentAdorner;
/// <summary>比例尺内侧竖向刻度线的 X 坐标（像素，相对尺身左端），仅画线不标数字。</summary>
public ObservableCollection<double> ScaleBarMinorTickXs { get; } = new();
public PolygonRoiCanvas()
{
InitializeComponent();
@@ -42,6 +45,8 @@ namespace XP.ImageProcessing.RoiControl.Controls
}
}
}
RefreshScaleBar();
}
private void ROIItems_CollectionChanged(object? sender, NotifyCollectionChangedEventArgs e)
@@ -142,6 +147,8 @@ namespace XP.ImageProcessing.RoiControl.Controls
// 图像尺寸变化后刷新十字线
if (control.ShowCrosshair)
control.AddCrosshair();
control.RefreshScaleBar();
}
public static readonly DependencyProperty ROIItemsProperty =
@@ -204,7 +211,7 @@ namespace XP.ImageProcessing.RoiControl.Controls
public static readonly DependencyProperty CanvasWidthProperty =
DependencyProperty.Register(nameof(CanvasWidth), typeof(double), typeof(PolygonRoiCanvas),
new PropertyMetadata(800.0));
new PropertyMetadata(800.0, OnCanvasOrScaleBarParameterChanged));
public double CanvasWidth
{
@@ -214,7 +221,7 @@ namespace XP.ImageProcessing.RoiControl.Controls
public static readonly DependencyProperty CanvasHeightProperty =
DependencyProperty.Register(nameof(CanvasHeight), typeof(double), typeof(PolygonRoiCanvas),
new PropertyMetadata(600.0));
new PropertyMetadata(600.0, OnCanvasOrScaleBarParameterChanged));
public double CanvasHeight
{
@@ -222,6 +229,116 @@ namespace XP.ImageProcessing.RoiControl.Controls
set => SetValue(CanvasHeightProperty, value);
}
/// <summary>是否在图像上显示比例尺（叠在图像坐标系内，随缩放与平移移动）。</summary>
public static readonly DependencyProperty ShowScaleBarProperty =
DependencyProperty.Register(nameof(ShowScaleBar), typeof(bool), typeof(PolygonRoiCanvas),
new PropertyMetadata(false, OnCanvasOrScaleBarParameterChanged));
public bool ShowScaleBar
{
get => (bool)GetValue(ShowScaleBarProperty);
set => SetValue(ShowScaleBarProperty, value);
}
/// <summary>单像素对应的物理长度（mm），用于比例尺刻度换算。</summary>
public static readonly DependencyProperty ScaleBarMmPerPixelProperty =
DependencyProperty.Register(nameof(ScaleBarMmPerPixel), typeof(double), typeof(PolygonRoiCanvas),
new PropertyMetadata(0.139, OnCanvasOrScaleBarParameterChanged));
public double ScaleBarMmPerPixel
{
get => (double)GetValue(ScaleBarMmPerPixelProperty);
set => SetValue(ScaleBarMmPerPixelProperty, value);
}
public static readonly DependencyProperty ScaleBarLengthPixelsProperty =
DependencyProperty.Register(nameof(ScaleBarLengthPixels), typeof(double), typeof(PolygonRoiCanvas),
new PropertyMetadata(100.0));
public double ScaleBarLengthPixels
{
get => (double)GetValue(ScaleBarLengthPixelsProperty);
private set => SetValue(ScaleBarLengthPixelsProperty, value);
}
public static readonly DependencyProperty ScaleBarCaptionProperty =
DependencyProperty.Register(nameof(ScaleBarCaption), typeof(string), typeof(PolygonRoiCanvas),
new PropertyMetadata(string.Empty));
public string ScaleBarCaption
{
get => (string)GetValue(ScaleBarCaptionProperty);
private set => SetValue(ScaleBarCaptionProperty, value);
}
private static void OnCanvasOrScaleBarParameterChanged(DependencyObject d, DependencyPropertyChangedEventArgs e)
{
((PolygonRoiCanvas)d).RefreshScaleBar();
}
/// <summary>按图像宽度选取 1–2–5 标度，使比例尺约占画布宽度的约 22%。</summary>
private void RefreshScaleBar()
{
const double targetFrac = 0.22;
const double maxFrac = 0.88;
const double minPx = 24.0;
if (!ShowScaleBar || CanvasWidth < 16 || ScaleBarMmPerPixel <= 0 || double.IsNaN(ScaleBarMmPerPixel))
{
ScaleBarLengthPixels = minPx;
ScaleBarCaption = string.Empty;
ScaleBarMinorTickXs.Clear();
return;
}
double maxPx = Math.Max(minPx, CanvasWidth * maxFrac);
double idealPx = Math.Min(CanvasWidth * targetFrac, maxPx);
double idealMm = idealPx * ScaleBarMmPerPixel;
double niceMm = RoundToNiceLengthMm(idealMm);
double barPx = niceMm / ScaleBarMmPerPixel;
while (barPx > maxPx && niceMm > ScaleBarMmPerPixel * minPx * 1.5)
{
niceMm /= 2.0;
barPx = niceMm / ScaleBarMmPerPixel;
}
while (barPx < minPx && niceMm < idealMm * 200)
{
niceMm *= 2.0;
barPx = niceMm / ScaleBarMmPerPixel;
}
if (barPx < minPx)
barPx = minPx;
ScaleBarLengthPixels = barPx;
ScaleBarCaption = FormatScaleBarCaptionMm(barPx * ScaleBarMmPerPixel);
ScaleBarMinorTickXs.Clear();
int divisions = barPx >= 120 ? 10 : barPx >= 60 ? 6 : 4;
for (int i = 1; i < divisions; i++)
ScaleBarMinorTickXs.Add(barPx * i / divisions);
}
private static double RoundToNiceLengthMm(double mm)
{
if (mm <= 0 || double.IsNaN(mm) || double.IsInfinity(mm))
return 0.1;
var magnitude = Math.Pow(10.0, Math.Floor(Math.Log10(mm)));
var normalized = mm / magnitude;
var nice = normalized < 1.5 ? 1.0 : normalized < 3.5 ? 2.0 : normalized < 7.5 ? 5.0 : 10.0;
return nice * magnitude;
}
private static string FormatScaleBarCaptionMm(double mm)
{
if (mm >= 100) return $"{mm:F0} mm";
if (mm >= 10) return $"{mm:F1} mm";
if (mm >= 1) return $"{mm:F2} mm";
return $"{mm:F3} mm";
}
public static readonly DependencyProperty SelectedROIProperty =
DependencyProperty.Register(nameof(SelectedROI), typeof(ROIShape), typeof(PolygonRoiCanvas),
new PropertyMetadata(null, OnSelectedROIChanged));
XplorePlane/Assets/Icons/Scale.png
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Width:  |  Height:  |  Size: 717 B

XplorePlane/ViewModels/Main/MainViewModel.cs
+7
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@@ -122,6 +122,13 @@ namespace XplorePlane.ViewModels
public DelegateCommand VoidDetectionCommand { get; }
public DelegateCommand BubbleMeasureCommand { get; }
private bool _isScaleBarVisible;
public bool IsScaleBarVisible
{
get => _isScaleBarVisible;
set => SetProperty(ref _isScaleBarVisible, value);
}
// 辅助线命令
public DelegateCommand ToggleCrosshairCommand { get; }
XplorePlane/Views/Main/ImagePanelView.xaml
+4 -1
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@@ -1,5 +1,6 @@
<UserControl
x:Class="XplorePlane.Views.ImagePanelView"
x:Name="Root"
xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation"
xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml"
xmlns:d="http://schemas.microsoft.com/expression/blend/2008"
@@ -16,6 +17,8 @@
<TextBlock Margin="4,2" HorizontalAlignment="Left" VerticalAlignment="Center"
FontWeight="SemiBold" Foreground="#333333" Text="图像处理" />
</Border>
<ContentControl Grid.Row="1" Content="{Binding ImagePanelContent}" />
<Grid Grid.Row="1">
<ContentControl Content="{Binding ImagePanelContent}" />
</Grid>
</Grid>
</UserControl>
XplorePlane/Views/Main/MainWindow.xaml
+7
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@@ -165,6 +165,13 @@
Size="Medium"
SmallImage="/Assets/Icons/crosshair.png"
Text="辅助线" />
<telerik:RadRibbonToggleButton
telerik:ScreenTip.Description="显示/隐藏图像比例尺"
telerik:ScreenTip.Title="比例尺"
IsChecked="{Binding IsScaleBarVisible, Mode=TwoWay}"
Size="Medium"
SmallImage="/Assets/Icons/Scale.png"
Text="比例尺" />
<telerik:RadRibbonButton
telerik:ScreenTip.Title="白底检测"
Command="{Binding WhiteBackgroundDetectionCommand}"
XplorePlane/Views/Main/ViewportPanelView.xaml
+3 -3
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@@ -10,7 +10,6 @@
d:DesignHeight="400"
d:DesignWidth="600"
mc:Ignorable="d">
<UserControl.Resources />
<Grid Background="#FFFFFF">
<Grid.RowDefinitions>
<RowDefinition Height="Auto" />
@@ -32,8 +31,9 @@
<roi:PolygonRoiCanvas
x:Name="RoiCanvas"
Background="White"
ImageSource="{Binding ImageSource}">
</roi:PolygonRoiCanvas>
ImageSource="{Binding ImageSource}"
ScaleBarMmPerPixel="0.139"
ShowScaleBar="{Binding DataContext.IsScaleBarVisible, RelativeSource={RelativeSource AncestorType=Window}}" />
</Grid>
</Grid>
</UserControl>