mirror of
https://github.com/babalae/better-genshin-impact.git
synced 2026-04-27 22:49:46 +08:00
525 lines
26 KiB
C#
525 lines
26 KiB
C#
using BetterGenshinImpact.Core.Simulator;
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using BetterGenshinImpact.GameTask;
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using BetterGenshinImpact.GameTask.Common;
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using BetterGenshinImpact.GameTask.Model.Area;
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using Fischless.WindowsInput;
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using Microsoft.Extensions.Logging;
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using OpenCvSharp;
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using System;
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using System.Collections;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using System.Threading;
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using System.Threading.Tasks;
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namespace BetterGenshinImpact.GameTask.Model.GameUI
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{
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public class GridScreen : IAsyncEnumerable<ImageRegion>
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{
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private readonly Rect gridRoi;
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private readonly CancellationToken ct;
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private readonly ILogger logger;
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private readonly InputSimulator input = Simulation.SendInput;
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private readonly int columns;
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private readonly int s1Round;
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private readonly int roundMilliseconds;
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private readonly int s2Round;
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private readonly double s3Scale;
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/// <summary>
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/// 对Gird类型界面的操作封装类
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/// 直接对此类对象进行遍历即可获取所有项
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/// 每次的截图是上次滚动后的，如果实时性要求高，应每次迭代自行截图
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/// 在末页可能重复返回GridItem，须自行处理
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/// </summary>
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/// <param name="gridRoi">Grid所在位置</param>
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/// <param name="logger"></param>
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/// <param name="ct"></param>
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public GridScreen(Rect gridRoi, GridScreenParams @params, ILogger logger, CancellationToken ct)
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{
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this.gridRoi = gridRoi;
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this.ct = ct;
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this.logger = logger;
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if (@params.Columns < 4)
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{
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throw new ArgumentOutOfRangeException(nameof(@params.Columns));
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}
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this.columns = @params.Columns;
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this.s1Round = @params.S1Round;
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this.roundMilliseconds = @params.RoundMilliseconds;
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this.s2Round = @params.S2Round;
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this.s3Scale = @params.S3Scale;
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}
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public IAsyncEnumerator<ImageRegion> GetAsyncEnumerator(CancellationToken cancellationToken = default)
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{
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return new GridEnumerator(gridRoi, columns, s1Round, roundMilliseconds, s2Round, s3Scale, logger, input, ct);
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}
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public class GridEnumerator : IAsyncEnumerator<ImageRegion>
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{
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private readonly Rect roi;
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private readonly CancellationToken ct;
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private readonly ILogger logger;
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private readonly InputSimulator input = Simulation.SendInput;
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private readonly int columns;
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private readonly int s1Round;
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private readonly int roundMilliseconds;
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private readonly int s2Round;
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private readonly double s3Scale;
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/// <summary>
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/// 单次滚动得到的页面
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/// </summary>
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/// <param name="ImageRegion">供枚举输出的队列</param>
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/// <param name="AntiRecycling">为了防止Grid的页面元素自动回收复用技术导致item高亮干扰，每次滚动后记录靠近下方的一个item，在下次滚动前主动点击该item</param>
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private record Page(Queue<ImageRegion> ImageRegions, Rect? AntiRecycling);
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private Page? currentPage;
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private ImageRegion current;
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ImageRegion IAsyncEnumerator<ImageRegion>.Current => current;
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/// <summary>
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/// 滚动操作枚举器
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/// </summary>
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/// <param name="roi"></param>
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/// <param name="columns">有几列</param>
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/// <param name="s1Round">测试是否能滚动时发出的滚动命令次数</param>
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/// <param name="roundMilliseconds">滚动命令间隔毫秒</param>
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/// <param name="s2Round">滚过一整页时发出的滚动命令次数</param>
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/// <param name="s3Scale">微调滚动时控制首行距离上边界的参数</param>
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/// <param name="logger"></param>
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/// <param name="input"></param>
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/// <param name="ct"></param>
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public GridEnumerator(Rect roi, int columns, int s1Round, int roundMilliseconds, int s2Round, double s3Scale, ILogger logger, InputSimulator input, CancellationToken ct)
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{
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this.roi = roi;
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this.ct = ct;
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this.logger = logger;
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this.input = input;
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this.columns = columns;
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this.s1Round = s1Round;
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this.roundMilliseconds = roundMilliseconds;
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this.s2Round = s2Round;
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this.s3Scale = s3Scale;
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}
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public async Task<bool> TryVerticalScollDown()
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{
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using var ra = TaskControl.CaptureToRectArea();
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using ImageRegion prevGrid = ra.DeriveCrop(roi);
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for (int i = 0; i < this.s1Round; i++)
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{
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this.input.Mouse.VerticalScroll(-2);
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await TaskControl.Delay(this.roundMilliseconds, this.ct);
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}
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await TaskControl.Delay(300, this.ct);
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using var ra2 = TaskControl.CaptureToRectArea();
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using ImageRegion scrolledGrid = ra2.DeriveCrop(this.roi);
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bool isScrolling = IsScrolling(prevGrid.CacheGreyMat, scrolledGrid.CacheGreyMat, out Point2d shift, logger: this.logger);
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return isScrolling;
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}
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/// <summary>
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/// 判断是否还能继续滚动，如果到底了则只能滚动一丝并很快地回弹
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/// </summary>
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/// <param name="prevGray">先前的灰度图</param>
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/// <param name="nextGray">尝试滚动并等待可能的回弹后的灰度图</param>
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/// <param name="shift">估计的位移</param>
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/// <param name="lowerThreshold">低于下限则可能不存在平移</param>
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/// <param name="upperThreshold">上限用于抵消微小的其他差异，比如高亮图标的呼吸闪烁</param>
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/// <param name="logger"></param>
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/// <returns></returns>
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public static bool IsScrolling(Mat prevGray, Mat nextGray, out Point2d shift, double lowerThreshold = 0.5, double upperThreshold = 0.95, ILogger? logger = null)
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{
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using Mat prev = new Mat();
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prevGray.ConvertTo(prev, MatType.CV_32FC1);
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using Mat next = new Mat();
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nextGray.ConvertTo(next, MatType.CV_32FC1);
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using Mat window = new Mat();
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shift = Cv2.PhaseCorrelate(prev, next, window, out double response); // 相位相关性
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//logger?.LogInformation($"response={response:F3}, shift=({shift.X:F2}, {shift.Y:F2})");
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return response > lowerThreshold && response < upperThreshold;
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}
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/// <summary>
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/// 将图标按Y轴高度简单地进行聚簇，避免因微小差异而乱序
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/// 已知每行的图标之间的Y不会差得太多
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/// </summary>
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/// <param name="numbers">传入的Y列表</param>
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/// <param name="threshold"></param>
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/// <returns>外层是各行从上到下，内层是一行从左到右</returns>
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static List<List<ImageRegion>> ClusterRows(IEnumerable<ImageRegion> regions, int threshold)
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{
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// 先对Y排序，便于聚簇
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var sortedRegions = regions.OrderBy(r => r.Y).ToList();
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List<List<ImageRegion>> clusters = new List<List<ImageRegion>>();
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if (sortedRegions.Count == 0)
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return clusters;
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// 初始化第一个聚簇
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List<ImageRegion> currentCluster = new List<ImageRegion> { };
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foreach (ImageRegion r in sortedRegions)
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{
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if (currentCluster.Count <= 0)
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{
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currentCluster.Add(r);
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continue;
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}
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ImageRegion lastInCluster = currentCluster.Last();
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// 如果当前数字与聚簇中最后一个数字的差值小于阈值，则加入当前聚簇
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if (r.Y - lastInCluster.Y <= threshold)
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{
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currentCluster.Add(r);
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}
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else
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{
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// 否则，创建一个新的聚簇
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clusters.Add(currentCluster.OrderBy(r => r.X).ToList());
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currentCluster = new List<ImageRegion> { r };
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}
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}
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// 添加最后一个聚簇
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clusters.Add(currentCluster.OrderBy(r => r.X).ToList());
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return clusters;
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}
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/// <summary>
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/// 返回未经排序的所有GridItem
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/// </summary>
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/// <param name="src"></param>
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/// <param name="columns"></param>
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/// <param name="findContoursAlpha"></param>
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/// <returns></returns>
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public static IEnumerable<Rect> GetGridItems(Mat src, int columns, bool findContoursAlpha = false)
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{
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Point[][] contours = findContoursAlpha ? FindContoursAlpha(src) : FindContours(src);
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IEnumerable<Point[]> Crop()
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{
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foreach (var contour in contours)
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{
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Rect rect = Cv2.BoundingRect(contour);
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// 把右上角的点去掉
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var topRightPoints = contour.Where(p => (p.X - rect.X) > (rect.Width * 0.60) && (p.Y - rect.Y) < (rect.Height * 0.28));
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yield return contour.Except(topRightPoints).ToArray();
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}
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}
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contours = Crop().ToArray();
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//foreach (var c in contours)
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//{
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// RotatedRect rect = Cv2.MinAreaRect(c);
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// Point2f[] rectPoints = rect.Points();
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// Point[] rectPointsInt = Array.ConvertAll(rectPoints, p => new Point((int)p.X, (int)p.Y));
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// // 在图像上绘制最小外接旋转矩形
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// for (int i = 0; i < 4; i++)
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// {
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// Cv2.Line(src, rectPointsInt[i], rectPointsInt[(i + 1) % 4], Scalar.Pink, 2);
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// }
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//}
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contours = contours
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.Where(c =>
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{
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Rect r = Cv2.BoundingRect(c);
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if (r.Width < src.Width / columns * 0.66) // 剔除太小的
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{
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return false;
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}
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if (r.Height == 0)
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{
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return false;
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}
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return Math.Abs((float)r.Width / r.Height - 0.8) < 0.05; // 按形状筛选
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}).ToArray();
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IEnumerable<Rect> boxes = contours.Select(Cv2.BoundingRect);
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//if (boxes.Count() != 32)
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//{
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// src.DrawContours(contours, -1, Scalar.Red);
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// foreach (Rect box in boxes)
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// {
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// Cv2.Rectangle(src, box.TopLeft, box.BottomRight, Scalar.AliceBlue);
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// }
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// Cv2.ImShow("src", src);
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// Cv2.WaitKey();
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// Cv2.DestroyAllWindows();
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//}
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return boxes;
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}
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/// <summary>
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/// 像“分解圣遗物”界面的背景是纯色的，用简单的算法就能提取轮廓
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/// </summary>
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/// <param name="src"></param>
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/// <returns></returns>
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public static Point[][] FindContours(Mat src)
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{
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using Mat grey = src.CvtColor(ColorConversionCodes.BGR2GRAY);
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//Cv2.ImShow("grey", grey);
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using Mat canny = grey.Canny(20, 40);
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//Cv2.ImShow("canny", canny);
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//Cv2.WaitKey();
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//闭运算把一些断裂的边缘粘合一下
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//局限：提纳里的耳朵太长了一直连到了正上方的另一个图标，这里闭运算就会把最后一丝空隙也连起来，仅凭亮度边缘无法分隔轮廓……
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//todo：使用头像识别，先行去掉头像
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using Mat closeKernel = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
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using Mat close = canny.MorphologyEx(MorphTypes.Close, closeKernel);
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//Cv2.ImShow("close", close);
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//Cv2.WaitKey();
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Cv2.FindContours(close, out Point[][] contours, out _, RetrievalModes.External, ContourApproximationModes.ApproxNone, null);
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return contours;
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}
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/// <summary>
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/// 背包界面的背景是把打开界面之前的画面进行了模糊+黑白渐变滤镜+左上角水印叠加处理
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/// 放任五彩斑斓的输入，并且允许点击高亮的话处理起来就复杂了
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/// 所以这个Alpha版方法留在这里只是想说明：
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/// 越是琢磨算法，就越会发现传统算法的能力是有极限的
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/// 既然是游戏画面，不如在输入的时候就尽量获得没有噪声的画面
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/// </summary>
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/// <param name="src"></param>
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/// <returns></returns>
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public static Point[][] FindContoursAlpha(Mat src)
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{
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Point[][] contours;
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void getLine(Mat edge, Scalar color)
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{
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using Mat threshold = edge.Threshold(30, 255, ThresholdTypes.Binary);
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LineSegmentPoint[] lines = threshold.HoughLinesP(1, (Cv2.PI / 180) / 4, 100, maxLineGap: 3);
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lines = lines.Where(l => (Math.Abs(l.P1.X - l.P2.X) == 0) || (Math.Abs(l.P1.Y - l.P2.Y) == 0)).ToArray();
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foreach (var line in lines)
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{
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Cv2.Line(src, line.P1, line.P2, color, 1);
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}
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}
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Mat Laplacian(Mat src)
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{
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//拉普拉斯算子
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//Canny的sobel算子太偏向于横平竖直，而在噪声干扰太厉害的地方会产生分叉
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using Mat laplacian = src.Laplacian(MatType.CV_64F, ksize: 3);
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Mat result = laplacian.ConvertScaleAbs();
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return result;
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}
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using Mat edge = new Mat(src.Size(), MatType.CV_8UC1);
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edge.SetTo(0);
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//除了明度，饱和度也纳入考虑
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//另外色度带来的噪声实在太多了所以不用，但其实有些地方色度的边缘比另两个维度的边缘好得多
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using Mat hsv = src.CvtColor(ColorConversionCodes.BGR2HSV);
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using Mat satChannel = hsv.ExtractChannel(1);
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//Cv2.ImShow("satChannel", satChannel);
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using Mat satEdge = Laplacian(satChannel);
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Cv2.BitwiseOr(satEdge, edge, edge);
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//Cv2.ImShow("satEdge", satEdge);
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//getLine(satEdge, Scalar.Red);
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using Mat valChannel = hsv.ExtractChannel(2);
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//Cv2.ImShow("valChannel", valChannel);
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using Mat valEdge = Laplacian(valChannel);
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Cv2.BitwiseOr(valEdge, edge, edge);
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//Cv2.ImShow("valEdge", valEdge);
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//getLine(valEdge, Scalar.Lime);
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//Cv2.WaitKey();
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//Cv2.ImShow("edge", edge);
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//Cv2.WaitKey();
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//高斯模糊方便去噪点
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//但毕竟是模糊，轮廓会被扩大，并且很难说是均匀的扩大
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using Mat blurred = edge.GaussianBlur(new Size(3, 3), 0.5);
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//Cv2.ImShow("blurred", blurred);
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//Cv2.WaitKey();
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//合并明度饱和度的边缘后再二值化
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Mat threshold = blurred.Threshold(50, 255, ThresholdTypes.Binary);
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//Cv2.ImShow("threshold", threshold);
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//Cv2.WaitKey();
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/*
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* 如果不用高斯模糊去噪点，自己搞一些形态学操作也行
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* 有些边缘会比高斯效果好
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//把太小的轮廓丢掉
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//Cv2.FindContours(threshold, out contours, out _, RetrievalModes.External, ContourApproximationModes.ApproxSimple, null);
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contours = contours.Where(c =>
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{
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Rect rect = Cv2.BoundingRect(c);
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if ((rect.Width > 10) || (rect.Height > 10))
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{
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return true;
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}
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return false;
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}).ToArray();
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threshold.SetTo(0);
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threshold.DrawContours(contours, -1, Scalar.White, thickness: 1);
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Cv2.ImShow("threshold", threshold);
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Cv2.WaitKey();
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//闭运算把一些断裂的边缘粘合一下
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using Mat closeKernel = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
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using Mat close = threshold.MorphologyEx(MorphTypes.Close, closeKernel);
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Cv2.ImShow("close", close);
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Cv2.WaitKey();
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//因为后面要做的开运算会把毛刺给去掉，但太细的边缘会被一起腐蚀掉，所以查找并填充一下轮廓
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Cv2.FindContours(close, out contours, out _, RetrievalModes.External, ContourApproximationModes.ApproxSimple, null);
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close.DrawContours(contours, -1, Scalar.White, thickness: -1);
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Cv2.ImShow("close", close);
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Cv2.WaitKey();
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//开运算去毛刺
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using Mat openKernel = Cv2.GetStructuringElement(MorphShapes.Rect, new Size(5, 5));
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using Mat open = close.MorphologyEx(MorphTypes.Open, openKernel);
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Cv2.ImShow("open", open);
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Cv2.WaitKey();
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*/
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//得到有噪点的边缘
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Cv2.FindContours(threshold, out contours, out _, RetrievalModes.External, ContourApproximationModes.ApproxNone, null);
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return contours;
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}
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public async ValueTask<bool> MoveNextAsync()
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{
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if (this.currentPage == null || this.currentPage.ImageRegions.Count < 1)
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{
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if (this.currentPage != null)
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{
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if (this.currentPage.AntiRecycling.HasValue)
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{
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using DesktopRegion desktop = new DesktopRegion(this.input.Mouse);
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var (x, y, w, h) = (this.currentPage.AntiRecycling.Value.X, this.currentPage.AntiRecycling.Value.Y, this.currentPage.AntiRecycling.Value.Width, this.currentPage.AntiRecycling.Value.Height);
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var (gcX, gcY) = (TaskContext.Instance().SystemInfo.CaptureAreaRect.X, TaskContext.Instance().SystemInfo.CaptureAreaRect.Y);
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desktop.ClickTo(gcX + this.roi.X + x + (w / 2d), gcY + this.roi.Y + y + (h / 2d));
|
||
await TaskControl.Delay(500, ct);
|
||
desktop.ClickTo(gcX + this.roi.X + x + (w / 2d), gcY + this.roi.Y + y + (h / 2d));
|
||
await TaskControl.Delay(500, ct);
|
||
}
|
||
|
||
//BetterGenshinImpact.View.Drawable.VisionContext.Instance().DrawContent.ClearAll();
|
||
|
||
using var ra4 = TaskControl.CaptureToRectArea();
|
||
ra4.MoveTo(this.roi.X + this.roi.Width / 2, this.roi.Y + this.roi.Height / 2);
|
||
await TaskControl.Delay(300, ct);
|
||
|
||
bool canScoll = await TryVerticalScollDown();
|
||
|
||
if (canScoll)
|
||
{
|
||
for (int i = 0; i < this.s2Round; i++) // 再滚动差不多（最多行数-1）行
|
||
{
|
||
input.Mouse.VerticalScroll(-2);
|
||
await TaskControl.Delay(this.roundMilliseconds, ct);
|
||
}
|
||
|
||
DateTimeOffset rollingEndTime = DateTime.Now.AddSeconds(2);
|
||
while (DateTime.Now < rollingEndTime)
|
||
{
|
||
await TaskControl.Delay(60, ct);
|
||
using var ra2 = TaskControl.CaptureToRectArea();
|
||
using ImageRegion grid2 = ra2.DeriveCrop(this.roi);
|
||
IEnumerable<Rect> gridItems2 = GetGridItems(grid2.SrcMat, this.columns);
|
||
if (gridItems2.Min(i => i.Y) > (ra2.Width * this.s3Scale)) // 最后精细滚动，保证完整地显示最多行
|
||
{
|
||
input.Mouse.VerticalScroll(-1);
|
||
}
|
||
else
|
||
{
|
||
break;
|
||
}
|
||
}
|
||
using var ra3 = TaskControl.CaptureToRectArea();
|
||
using ImageRegion grid3 = ra3.DeriveCrop(this.roi);
|
||
grid3.MoveTo(grid3.Width, grid3.Height);
|
||
await TaskControl.Delay(300, ct);
|
||
}
|
||
else
|
||
{
|
||
await TaskControl.Delay(300, ct);
|
||
this.logger.LogInformation("滚动到底部了");
|
||
return false;
|
||
}
|
||
}
|
||
|
||
IEnumerable<ImageRegion> gridItems;
|
||
if (this.currentPage == null)
|
||
{
|
||
// 第一页采集时，主动操作来避免图标高亮
|
||
// 双击第四列，采集第一、二列
|
||
using DesktopRegion desktop = new DesktopRegion(this.input.Mouse);
|
||
var (gcX, gcY) = (TaskContext.Instance().SystemInfo.CaptureAreaRect.X, TaskContext.Instance().SystemInfo.CaptureAreaRect.Y);
|
||
desktop.ClickTo(gcX + this.roi.X + this.roi.Width * 3.5 / this.columns, gcY + this.roi.Y + this.roi.Width * 0.5 / this.columns);
|
||
await TaskControl.Delay(500, ct);
|
||
desktop.ClickTo(gcX + this.roi.X + this.roi.Width * 3.5 / this.columns, gcY + this.roi.Y + this.roi.Width * 0.5 / this.columns);
|
||
await TaskControl.Delay(500, ct);
|
||
|
||
using ImageRegion ra12 = TaskControl.CaptureToRectArea();
|
||
using ImageRegion imageRegion12 = ra12.DeriveCrop(this.roi);
|
||
using Mat columns12 = new Mat(imageRegion12.SrcMat, new Rect(0, 0, (int)(this.roi.Width * 2.5 / this.columns), this.roi.Height));
|
||
IEnumerable<Rect> columns12Items = GetGridItems(columns12, 2);
|
||
// 双击第一列，采集第三列以后的列
|
||
desktop.ClickTo(gcX + this.roi.X + this.roi.Width * 0.5 / this.columns, gcY + this.roi.Y + this.roi.Width * 0.5 / this.columns);
|
||
await TaskControl.Delay(500, ct);
|
||
desktop.ClickTo(gcX + this.roi.X + this.roi.Width * 0.5 / this.columns, gcY + this.roi.Y + this.roi.Width * 0.5 / this.columns);
|
||
await TaskControl.Delay(500, ct);
|
||
|
||
using ImageRegion raRest = TaskControl.CaptureToRectArea();
|
||
using ImageRegion imageRegionRest = raRest.DeriveCrop(this.roi);
|
||
int restStartX = (int)(this.roi.Width * 1.5 / this.columns);
|
||
using Mat columnsRest = new Mat(imageRegionRest.SrcMat, new Rect(restStartX, 0, this.roi.Width - restStartX, this.roi.Height));
|
||
IEnumerable<Rect> columnsRestItems = GetGridItems(columnsRest, this.columns - 2).Select(r => new Rect(r.X + restStartX, r.Y, r.Width, r.Height));
|
||
|
||
gridItems = columns12Items.Select(imageRegion12.DeriveCrop).Union(columnsRestItems.Select(imageRegionRest.DeriveCrop)).ToArray();
|
||
}
|
||
else
|
||
{
|
||
using ImageRegion ra = TaskControl.CaptureToRectArea();
|
||
using ImageRegion imageRegion = ra.DeriveCrop(this.roi);
|
||
gridItems = GetGridItems(imageRegion.SrcMat, this.columns).Select(imageRegion.DeriveCrop);
|
||
}
|
||
|
||
List<List<ImageRegion>> clusterRows = ClusterRows(gridItems, (int)(0.025 * this.roi.Height));
|
||
this.currentPage = new Page(new Queue<ImageRegion>(clusterRows.SelectMany(r => r)), clusterRows.Reverse<List<ImageRegion>>().Skip(1)?.FirstOrDefault()?.FirstOrDefault()?.ToRect());
|
||
|
||
//foreach (Rect item in gridItems.Select(r => r.ToRect()))
|
||
//{
|
||
// imageRegion.DrawRect(item, item.GetHashCode().ToString(), new System.Drawing.Pen(System.Drawing.Color.Lime));
|
||
//}
|
||
}
|
||
|
||
this.current = this.currentPage.ImageRegions.Dequeue();
|
||
return true;
|
||
}
|
||
|
||
public ValueTask DisposeAsync()
|
||
{
|
||
return ValueTask.CompletedTask;
|
||
}
|
||
}
|
||
}
|
||
}
|