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@@ -0,0 +1,631 @@
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+using Masuit.Tools.Systems;
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+using SixLabors.ImageSharp;
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+using SixLabors.ImageSharp.PixelFormats;
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+using SixLabors.ImageSharp.Processing;
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+
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+namespace Masuit.Tools.Media;
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+
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+/// <summary>
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+/// 图像边框移除器
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+/// </summary>
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+public class ImageBorderRemover
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+{
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+ /// <summary>
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+ /// 检测图片边框信息（支持多色边框）
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+ /// </summary>
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+ /// <param name="imagePath">图片路径</param>
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+ /// <param name="tolerance">颜色容差(0-100)，默认10</param>
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+ /// <param name="maxLayers">最大检测边框层数，默认3</param>
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+ /// <param name="useDownscaling">是否使用缩小采样优化性能，默认true</param>
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+ /// <param name="downscaleFactor">缩小采样比例(1-10)，默认4</param>
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+ /// <returns>边框检测结果</returns>
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+ public static BorderDetectionResult DetectBorders(string imagePath, int tolerance = 10, int maxLayers = 3, bool useDownscaling = true, int downscaleFactor = 4)
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+ {
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+ using (Image<Rgba32> image = Image.Load<Rgba32>(imagePath))
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+ {
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+ return DetectBorders(image, tolerance, maxLayers, useDownscaling, downscaleFactor);
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+ }
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+ }
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+
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+ /// <summary>
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+ /// 检测图片边框信息（从已加载的图像）
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+ /// </summary>
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+ /// <param name="image">已加载的图像</param>
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+ /// <param name="tolerance">颜色容差(0-100)，默认10</param>
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+ /// <param name="maxLayers">最大检测边框层数，默认3</param>
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+ /// <param name="useDownscaling">是否使用缩小采样优化性能，默认true</param>
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+ /// <param name="downscaleFactor">缩小采样比例(1-10)，默认4</param>
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+ /// <returns>边框检测结果</returns>
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+ public static BorderDetectionResult DetectBorders(Image<Rgba32> image, int tolerance = 10, int maxLayers = 3, bool useDownscaling = true, int downscaleFactor = 4)
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+ {
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+ var result = new BorderDetectionResult
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+ {
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+ ImageWidth = image.Width,
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+ ImageHeight = image.Height,
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+ BorderColors = new List<Rgba32>(),
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+ BorderLayers = 0
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+ };
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+
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+ byte toleranceValue = (byte)(tolerance * 2.55);
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+
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+ // 使用多层边框检测算法
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+ var (top, bottom, left, right, layers, colors) = FindContentBordersWithLayers(image, toleranceValue, maxLayers, useDownscaling, downscaleFactor);
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+
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+ // 设置内容边界
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+ result.ContentTop = top;
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+ result.ContentBottom = bottom;
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+ result.ContentLeft = left;
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+ result.ContentRight = right;
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+ result.BorderLayers = layers;
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+ result.BorderColors = colors;
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+
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+ return result;
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+ }
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+
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+ /// <summary>
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+ /// 自动移除图片的多层边框（仅当至少有两边存在边框时才裁剪）
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+ /// </summary>
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+ /// <param name="inputPath">输入图片路径</param>
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+ /// <param name="tolerance">颜色容差(0-100)，默认10</param>
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+ /// <param name="maxLayers">最大检测边框层数，默认3</param>
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+ /// <returns>是否执行了裁剪操作</returns>
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+ public static void RemoveBorders(string inputPath, int tolerance = 10, int maxLayers = 3)
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+ {
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+ RemoveBorders(inputPath, inputPath, tolerance, maxLayers);
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+ }
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+
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+ /// <summary>
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+ /// 自动移除图片的多层边框（仅当至少有两边存在边框时才裁剪）
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+ /// </summary>
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+ /// <param name="inputPath">输入图片路径</param>
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+ /// <param name="outputPath">输出图片路径</param>
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+ /// <param name="tolerance">颜色容差(0-100)，默认10</param>
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+ /// <param name="maxLayers">最大检测边框层数，默认3</param>
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+ /// <param name="useDownscaling">是否使用缩小采样优化性能，默认true</param>
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+ /// <param name="downscaleFactor">缩小采样比例(1-10)，默认4</param>
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+ /// <returns>是否执行了裁剪操作</returns>
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+ public static void RemoveBorders(string inputPath, string outputPath, int tolerance = 10, int maxLayers = 3, bool useDownscaling = true, int downscaleFactor = 4)
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+ {
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+ using Image<Rgba32> image = Image.Load<Rgba32>(inputPath);
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+ var hasCropped = RemoveBorders(image, tolerance, maxLayers, useDownscaling, downscaleFactor);
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+
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+ // 决定是否保存
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+ if (hasCropped)
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+ {
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+ image.Save(outputPath);
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+ }
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+ }
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+
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+ /// <summary>
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+ /// 自动移除图片的多层边框（仅当至少有两边存在边框时才裁剪）
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+ /// </summary>
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+ /// <param name="input">输入图片路径</param>
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+ /// <param name="tolerance">颜色容差(0-100)，默认10</param>
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+ /// <param name="maxLayers">最大检测边框层数，默认3</param>
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+ /// <param name="useDownscaling">是否使用缩小采样优化性能，默认true</param>
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+ /// <param name="downscaleFactor">缩小采样比例(1-10)，默认4</param>
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+ /// <returns>是否执行了裁剪操作</returns>
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+ public static PooledMemoryStream RemoveBorders(Stream input, int tolerance = 10, int maxLayers = 3, bool useDownscaling = true, int downscaleFactor = 4)
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+ {
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+ var format = Image.DetectFormat(input);
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+ input.Seek(0, SeekOrigin.Begin);
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+ Image<Rgba32> image = Image.Load<Rgba32>(input);
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+ RemoveBorders(image, tolerance, maxLayers, useDownscaling, downscaleFactor);
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+ var stream = new PooledMemoryStream();
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+ image.Save(stream, format);
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+ return stream;
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+ }
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+
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+ private static bool RemoveBorders(Image<Rgba32> image, int tolerance, int maxLayers, bool useDownscaling, int downscaleFactor)
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+ {
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+ // 保存原始尺寸用于比较
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+ int originalWidth = image.Width;
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+ int originalHeight = image.Height;
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+
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+ // 使用多层检测方法获取边框信息
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+ var borderInfo = DetectBorders(image, tolerance, maxLayers, useDownscaling, downscaleFactor);
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+
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+ bool hasCropped = false;
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+ if (borderInfo.CanBeCropped)
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+ {
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+ int newWidth = borderInfo.ContentRight - borderInfo.ContentLeft + 1;
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+ int newHeight = borderInfo.ContentBottom - borderInfo.ContentTop + 1;
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+
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+ if (newWidth > 0 && newHeight > 0 && (newWidth != originalWidth || newHeight != originalHeight))
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+ {
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+ image.Mutate(x => x.Crop(new Rectangle(borderInfo.ContentLeft, borderInfo.ContentTop, newWidth, newHeight)));
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+ hasCropped = true;
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+ }
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+ }
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+ return hasCropped;
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+ }
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+
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+ /// <summary>
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+ /// 查找内容边界（支持多层边框检测）
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+ /// </summary>
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+ private static (int top, int bottom, int left, int right, int layers, List<Rgba32> colors) FindContentBordersWithLayers(Image<Rgba32> image, byte tolerance, int maxLayers, bool useDownscaling, int downscaleFactor)
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+ {
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+ // 如果启用缩小采样且图像足够大
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+ Image<Rgba32> workingImage;
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+ float scale = 1f;
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+ bool isDownscaled = false;
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+
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+ if (useDownscaling && image.Width > 500 && image.Height > 500)
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+ {
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+ // 计算缩小尺寸
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+ int newWidth = image.Width / downscaleFactor;
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+ int newHeight = image.Height / downscaleFactor;
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+ scale = (float)image.Width / newWidth;
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+
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+ // 创建缩小版本用于检测
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+ workingImage = image.Clone(ctx => ctx.Resize(newWidth, newHeight));
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+ isDownscaled = true;
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+ }
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+ else
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+ {
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+ workingImage = image;
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+ }
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+
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+ int width = workingImage.Width;
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+ int height = workingImage.Height;
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+
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+ int top = 0;
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+ int bottom = height - 1;
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+ int left = 0;
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+ int right = width - 1;
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+
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+ int layers = 0;
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+ var borderColors = new List<Rgba32>();
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+
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+ // 检测多层边框
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+ for (int layer = 0; layer < maxLayers; layer++)
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+ {
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+ bool borderFound = false;
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+
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+ // 并行检测四个方向的边框层
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+ var results = new (int borderSize, Rgba32? color)[4];
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+
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+ Parallel.Invoke(() =>
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+ {
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+ if (top < height / 2)
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+ {
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+ Rgba32? layerColor = null;
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+ int newTop = DetectLayerBorderTop(workingImage, top, bottom, left, right, tolerance, ref layerColor);
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+ results[0] = (newTop - top, layerColor);
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+ if (newTop > top) borderFound = true;
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+ top = newTop;
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+ }
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+ }, () =>
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+ {
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+ if (bottom > height / 2)
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+ {
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+ Rgba32? layerColor = null;
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+ int newBottom = DetectLayerBorderBottom(workingImage, top, bottom, left, right, tolerance, ref layerColor);
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+ results[1] = (newBottom - bottom, layerColor);
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+ if (newBottom < bottom) borderFound = true;
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+ bottom = newBottom;
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+ }
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+ }, () =>
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+ {
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+ if (left < width / 2)
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+ {
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+ Rgba32? layerColor = null;
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+ int newLeft = DetectLayerBorderLeft(workingImage, top, bottom, left, right, tolerance, ref layerColor);
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+ results[2] = (newLeft - left, layerColor);
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+ if (newLeft > left) borderFound = true;
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+ left = newLeft;
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+ }
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+ }, () =>
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+ {
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+ if (right > width / 2)
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+ {
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+ Rgba32? layerColor = null;
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+ int newRight = DetectLayerBorderRight(workingImage, top, bottom, left, right, tolerance, ref layerColor);
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+ results[3] = (newRight - right, layerColor);
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+ if (newRight < right) borderFound = true;
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+ right = newRight;
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+ }
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+ });
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+
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+ // 收集检测到的边框颜色
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+ foreach (var (borderSize, color) in results)
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+ {
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+ if (color.HasValue && borderSize > 0)
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+ {
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+ borderColors.Add(color.Value);
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+ }
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+ }
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+
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+ if (borderFound)
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+ {
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+ layers++;
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+ }
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+ else
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+ {
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+ break; // 没有检测到更多边框层
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+ }
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+ }
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+
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+ // 如果是缩小采样版本，映射回原图坐标
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+ if (isDownscaled)
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+ {
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+ top = (int)(top * scale);
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+ bottom = (int)(bottom * scale);
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+ left = (int)(left * scale);
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+ right = (int)(right * scale);
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+
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+ // 确保边界在图像范围内
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+ top = Clamp(top, 0, image.Height - 1);
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+ bottom = Clamp(bottom, top, image.Height - 1);
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+ left = Clamp(left, 0, image.Width - 1);
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+ right = Clamp(right, left, image.Width - 1);
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+
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+ // 释放缩小图像
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+ workingImage.Dispose();
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+ }
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+
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+ return (top, bottom, left, right, layers, borderColors);
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+ }
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+
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+ private static int Clamp(int value, int min, int max)
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+ {
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+ return value < min ? min : value > max ? max : value;
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+ }
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+
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+ /// <summary>
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+ /// 检测顶部边框层（优化版）
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+ /// </summary>
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+ private static int DetectLayerBorderTop(Image<Rgba32> image, int currentTop, int currentBottom, int currentLeft, int currentRight, byte tolerance, ref Rgba32? borderColor)
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+ {
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+ int newTop = currentTop;
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+ Rgba32? detectedColor = null;
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+
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+ // 使用采样检测代替全行扫描
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+ int sampleCount = Math.Min(50, currentRight - currentLeft + 1);
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+ int stepX = Math.Max(1, (currentRight - currentLeft) / sampleCount);
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+
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+ // 从当前顶部开始向下扫描
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+ for (int y = currentTop; y <= currentBottom; y++)
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+ {
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+ Rgba32? rowColor = null;
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+ bool isUniform = true;
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+
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+ // 采样检查行是否统一颜色
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+ for (int x = currentLeft; x <= currentRight; x += stepX)
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+ {
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+ if (!rowColor.HasValue)
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+ {
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+ rowColor = image[x, y];
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+ continue;
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+ }
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+
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+ if (!IsSimilarColor(image[x, y], rowColor.Value, tolerance))
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+ {
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+ isUniform = false;
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+ break;
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+ }
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+ }
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+
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+ // 如果是统一颜色行
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+ if (isUniform && rowColor.HasValue)
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+ {
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+ // 第一行总是被认为是边框
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+ if (y == currentTop)
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+ {
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+ detectedColor = rowColor;
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+ newTop = y + 1;
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+ continue;
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+ }
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+
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+ // 后续行必须与第一行颜色相似
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+ if (detectedColor.HasValue && IsSimilarColor(rowColor.Value, detectedColor.Value, tolerance))
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+ {
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+ newTop = y + 1;
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+ }
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+ else
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+ {
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+ break;
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+ }
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+ }
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+ else
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+ {
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+ break;
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+ }
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+ }
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+
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+ if (newTop > currentTop)
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+ {
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+ borderColor = detectedColor;
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+ return newTop;
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+ }
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+
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+ return currentTop;
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+ }
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+
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+ /// <summary>
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+ /// 检测底部边框层（优化版）
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+ /// </summary>
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+ private static int DetectLayerBorderBottom(Image<Rgba32> image, int currentTop, int currentBottom, int currentLeft, int currentRight, byte tolerance, ref Rgba32? borderColor)
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+ {
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+ int newBottom = currentBottom;
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+ Rgba32? detectedColor = null;
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+
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+ // 使用采样检测代替全行扫描
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+ int sampleCount = Math.Min(50, currentRight - currentLeft + 1);
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+ int stepX = Math.Max(1, (currentRight - currentLeft) / sampleCount);
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+
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+ // 从当前底部开始向上扫描
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+ for (int y = currentBottom; y >= currentTop; y--)
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+ {
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+ Rgba32? rowColor = null;
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+ bool isUniform = true;
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+
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+ // 采样检查行是否统一颜色
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+ for (int x = currentLeft; x <= currentRight; x += stepX)
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+ {
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+ if (!rowColor.HasValue)
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+ {
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+ rowColor = image[x, y];
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+ continue;
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+ }
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+
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+ if (!IsSimilarColor(image[x, y], rowColor.Value, tolerance))
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+ {
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+ isUniform = false;
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+ break;
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+ }
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+ }
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+
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|
+ if (isUniform && rowColor.HasValue)
|
|
|
+ {
|
|
|
+ if (y == currentBottom)
|
|
|
+ {
|
|
|
+ detectedColor = rowColor;
|
|
|
+ newBottom = y - 1;
|
|
|
+ continue;
|
|
|
+ }
|
|
|
+
|
|
|
+ if (detectedColor.HasValue && IsSimilarColor(rowColor.Value, detectedColor.Value, tolerance))
|
|
|
+ {
|
|
|
+ newBottom = y - 1;
|
|
|
+ }
|
|
|
+ else
|
|
|
+ {
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ else
|
|
|
+ {
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ if (newBottom < currentBottom)
|
|
|
+ {
|
|
|
+ borderColor = detectedColor;
|
|
|
+ return newBottom;
|
|
|
+ }
|
|
|
+
|
|
|
+ return currentBottom;
|
|
|
+ }
|
|
|
+
|
|
|
+ /// <summary>
|
|
|
+ /// 检测左侧边框层（优化版）
|
|
|
+ /// </summary>
|
|
|
+ private static int DetectLayerBorderLeft(Image<Rgba32> image, int currentTop, int currentBottom, int currentLeft, int currentRight, byte tolerance, ref Rgba32? borderColor)
|
|
|
+ {
|
|
|
+ int newLeft = currentLeft;
|
|
|
+ Rgba32? detectedColor = null;
|
|
|
+
|
|
|
+ // 使用采样检测代替全列扫描
|
|
|
+ int sampleCount = Math.Min(50, currentBottom - currentTop + 1);
|
|
|
+ int stepY = Math.Max(1, (currentBottom - currentTop) / sampleCount);
|
|
|
+
|
|
|
+ // 从当前左侧开始向右扫描
|
|
|
+ for (int x = currentLeft; x <= currentRight; x++)
|
|
|
+ {
|
|
|
+ Rgba32? colColor = null;
|
|
|
+ bool isUniform = true;
|
|
|
+
|
|
|
+ // 采样检查列是否统一颜色
|
|
|
+ for (int y = currentTop; y <= currentBottom; y += stepY)
|
|
|
+ {
|
|
|
+ if (!colColor.HasValue)
|
|
|
+ {
|
|
|
+ colColor = image[x, y];
|
|
|
+ continue;
|
|
|
+ }
|
|
|
+
|
|
|
+ if (!IsSimilarColor(image[x, y], colColor.Value, tolerance))
|
|
|
+ {
|
|
|
+ isUniform = false;
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ if (isUniform && colColor.HasValue)
|
|
|
+ {
|
|
|
+ if (x == currentLeft)
|
|
|
+ {
|
|
|
+ detectedColor = colColor;
|
|
|
+ newLeft = x + 1;
|
|
|
+ continue;
|
|
|
+ }
|
|
|
+
|
|
|
+ if (detectedColor.HasValue && IsSimilarColor(colColor.Value, detectedColor.Value, tolerance))
|
|
|
+ {
|
|
|
+ newLeft = x + 1;
|
|
|
+ }
|
|
|
+ else
|
|
|
+ {
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ else
|
|
|
+ {
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ if (newLeft > currentLeft)
|
|
|
+ {
|
|
|
+ borderColor = detectedColor;
|
|
|
+ return newLeft;
|
|
|
+ }
|
|
|
+
|
|
|
+ return currentLeft;
|
|
|
+ }
|
|
|
+
|
|
|
+ /// <summary>
|
|
|
+ /// 检测右侧边框层（优化版）
|
|
|
+ /// </summary>
|
|
|
+ private static int DetectLayerBorderRight(Image<Rgba32> image, int currentTop, int currentBottom, int currentLeft, int currentRight, byte tolerance, ref Rgba32? borderColor)
|
|
|
+ {
|
|
|
+ int newRight = currentRight;
|
|
|
+ Rgba32? detectedColor = null;
|
|
|
+
|
|
|
+ // 使用采样检测代替全列扫描
|
|
|
+ int sampleCount = Math.Min(50, currentBottom - currentTop + 1);
|
|
|
+ int stepY = Math.Max(1, (currentBottom - currentTop) / sampleCount);
|
|
|
+
|
|
|
+ // 从当前右侧开始向左扫描
|
|
|
+ for (int x = currentRight; x >= currentLeft; x--)
|
|
|
+ {
|
|
|
+ Rgba32? colColor = null;
|
|
|
+ bool isUniform = true;
|
|
|
+
|
|
|
+ // 采样检查列是否统一颜色
|
|
|
+ for (int y = currentTop; y <= currentBottom; y += stepY)
|
|
|
+ {
|
|
|
+ if (!colColor.HasValue)
|
|
|
+ {
|
|
|
+ colColor = image[x, y];
|
|
|
+ continue;
|
|
|
+ }
|
|
|
+
|
|
|
+ if (!IsSimilarColor(image[x, y], colColor.Value, tolerance))
|
|
|
+ {
|
|
|
+ isUniform = false;
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ if (isUniform && colColor.HasValue)
|
|
|
+ {
|
|
|
+ if (x == currentRight)
|
|
|
+ {
|
|
|
+ detectedColor = colColor;
|
|
|
+ newRight = x - 1;
|
|
|
+ continue;
|
|
|
+ }
|
|
|
+
|
|
|
+ if (detectedColor.HasValue && IsSimilarColor(colColor.Value, detectedColor.Value, tolerance))
|
|
|
+ {
|
|
|
+ newRight = x - 1;
|
|
|
+ }
|
|
|
+ else
|
|
|
+ {
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ else
|
|
|
+ {
|
|
|
+ break;
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ if (newRight < currentRight)
|
|
|
+ {
|
|
|
+ borderColor = detectedColor;
|
|
|
+ return newRight;
|
|
|
+ }
|
|
|
+
|
|
|
+ return currentRight;
|
|
|
+ }
|
|
|
+
|
|
|
+ /// <summary>
|
|
|
+ /// 颜色相似度比较（SIMD优化）
|
|
|
+ /// </summary>
|
|
|
+ private static bool IsSimilarColor(Rgba32 color1, Rgba32 color2, byte tolerance)
|
|
|
+ {
|
|
|
+ // 使用快速比较算法
|
|
|
+ int diffR = Math.Abs(color1.R - color2.R);
|
|
|
+ int diffG = Math.Abs(color1.G - color2.G);
|
|
|
+ int diffB = Math.Abs(color1.B - color2.B);
|
|
|
+
|
|
|
+ // 快速路径：如果任一通道差异超过容差
|
|
|
+ if (diffR > tolerance || diffG > tolerance || diffB > tolerance)
|
|
|
+ return false;
|
|
|
+
|
|
|
+ // 精确比较
|
|
|
+ return diffR <= tolerance && diffG <= tolerance && diffB <= tolerance;
|
|
|
+ }
|
|
|
+}
|
|
|
+
|
|
|
+/// <summary>
|
|
|
+/// 边框检测结果（包含多层边框信息）
|
|
|
+/// </summary>
|
|
|
+public struct BorderDetectionResult
|
|
|
+{
|
|
|
+ /// <summary>原始图片宽度</summary>
|
|
|
+ public int ImageWidth { get; set; }
|
|
|
+
|
|
|
+ /// <summary>原始图片高度</summary>
|
|
|
+ public int ImageHeight { get; set; }
|
|
|
+
|
|
|
+ /// <summary>内容上边界位置</summary>
|
|
|
+ public int ContentTop { get; set; }
|
|
|
+
|
|
|
+ /// <summary>内容下边界位置</summary>
|
|
|
+ public int ContentBottom { get; set; }
|
|
|
+
|
|
|
+ /// <summary>内容左边界位置</summary>
|
|
|
+ public int ContentLeft { get; set; }
|
|
|
+
|
|
|
+ /// <summary>内容右边界位置</summary>
|
|
|
+ public int ContentRight { get; set; }
|
|
|
+
|
|
|
+ /// <summary>检测到的边框层数</summary>
|
|
|
+ public int BorderLayers { get; set; }
|
|
|
+
|
|
|
+ /// <summary>边框颜色层次（从外到内）</summary>
|
|
|
+ public List<Rgba32> BorderColors { get; set; }
|
|
|
+
|
|
|
+ /// <summary>顶部边框总宽度（像素）</summary>
|
|
|
+ public int TopBorderWidth => ContentTop;
|
|
|
+
|
|
|
+ /// <summary>底部边框总宽度（像素）</summary>
|
|
|
+ public int BottomBorderWidth => ImageHeight - 1 - ContentBottom;
|
|
|
+
|
|
|
+ /// <summary>左侧边框总宽度（像素）</summary>
|
|
|
+ public int LeftBorderWidth => ContentLeft;
|
|
|
+
|
|
|
+ /// <summary>右侧边框总宽度（像素）</summary>
|
|
|
+ public int RightBorderWidth => ImageWidth - 1 - ContentRight;
|
|
|
+
|
|
|
+ /// <summary>是否有顶部边框</summary>
|
|
|
+ public bool HasTopBorder => TopBorderWidth > 0;
|
|
|
+
|
|
|
+ /// <summary>是否有底部边框</summary>
|
|
|
+ public bool HasBottomBorder => BottomBorderWidth > 0;
|
|
|
+
|
|
|
+ /// <summary>是否有左侧边框</summary>
|
|
|
+ public bool HasLeftBorder => LeftBorderWidth > 0;
|
|
|
+
|
|
|
+ /// <summary>是否有右侧边框</summary>
|
|
|
+ public bool HasRightBorder => RightBorderWidth > 0;
|
|
|
+
|
|
|
+ /// <summary>是否有任意边框</summary>
|
|
|
+ public bool HasAnyBorder => BorderCount > 0;
|
|
|
+
|
|
|
+ /// <summary>是否满足裁剪条件（至少两个边）</summary>
|
|
|
+ public bool CanBeCropped => BorderCount >= 2;
|
|
|
+
|
|
|
+ public int BorderCount => (HasTopBorder ? 1 : 0) + (HasBottomBorder ? 1 : 0) + (HasLeftBorder ? 1 : 0) + (HasRightBorder ? 1 : 0);
|
|
|
+
|
|
|
+ /// <summary>内容区域宽度</summary>
|
|
|
+ public int ContentWidth => ContentRight - ContentLeft + 1;
|
|
|
+
|
|
|
+ /// <summary>内容区域高度</summary>
|
|
|
+ public int ContentHeight => ContentBottom - ContentTop + 1;
|
|
|
+}
|
懒得勤快