using System;
using System.Collections.Generic;
using System.Threading;
using HalconDotNet;
using TeamAAS.FlowEditor.Execution;
using TeamAAS.FlowEditor.Models;
using TeamAAS.FlowEditor.Plugins;
using Plugins.Halcon.Models;
using Plugins.Halcon;

namespace Plugins.Halcon
{
    // ─────────────────────────────────────────────────────────────────────
    // HALCON 检测识别分类算子（新增）。
    // ─────────────────────────────────────────────────────────────────────

    /// <summary>H边缘提取：Sobel 梯度 + 阈值，输出边缘区域（可配合形状筛选取感兴趣边缘）。</summary>
    [Serializable]
    [Plugin("H边缘提取", PluginCategory.Halocn模块, typeof(HalconEdgeModel), "VectorLine",
        NodeShape = NodeCategory.Normal, IsSubFlowNode = true, VisionCategory = VisionPlugin.检测识别,
        Description = "Sobel 边缘提取：梯度幅值 + 灰度阈值 → 边缘区域；高级编辑可加载图像调试")]
    public class HalconEdgePlugin : BasePlugin<HalconEdgeModel>
    {
        public override List<OutputField> DeclareOutputs() => new List<OutputField>
        {
            new OutputField("边缘区域", typeof(object)),
            new OutputField("结果", typeof(bool)),
        };

        public override NodeRunStatus PluginRun(CancellationToken token, out Dictionary<string, object> results)
        {
            var res = new Dictionary<string, object>();
            results = res;
            NodeRunStatus Fail(string m) { res["Error"] = m; res["结果"] = false; Log(1, $"边缘提取失败: {m}", TeamAAS.LogLevel.Error); return NodeRunStatus.Failed; }
            bool owned = false;
            HObject image = null;
            HObject edgeAmp = null;
            try
            {
                var src = GetResolve(Model.ImageSource);
                if (src == null) return Fail("未获取到输入图像（请绑定「输入图像」，例如 &{输入.图像}）");
                owned = !(src is HObject);
                image = HalconRuntime.ToHObject(src);

                Log(3, $"边缘提取：Sobel[{Model.FilterType}] 孔径={Model.ApertureSize}，阈值[{Model.MinGray},{Model.MaxGray}]");
                HOperatorSet.SobelAmp(image, out edgeAmp, Model.FilterType, Model.ApertureSize);
                var edges = HalconRuntime.Threshold(edgeAmp, Model.MinGray, Model.MaxGray);
                res["边缘区域"] = edges;
                res["结果"] = true;
                HalconEditorPreview.Show(Model, src, edges, "green");   // 底图 + 边缘叠加
                Log(2, $"边缘提取完成：区域对象数={HalconRuntime.CountObj(edges)}");
                return NodeRunStatus.Success;
            }
            catch (Exception ex) { return Fail(ex.Message); }
            finally
            {
                if (edgeAmp != null) { try { edgeAmp.Dispose(); } catch { } }
                if (owned) HalconRuntime.Dispose(image);
            }
        }
    }
}

namespace Plugins.Halcon.Models
{
    using PropertyGridLib.Attributes;
    using PropertyGridLib.Controls;
    using System.ComponentModel;
    using TeamAAS.FlowEditor.Plugins;
    using TeamAAS.FlowEngine.FormulaData;

    /// <summary>边缘提取模型。</summary>
    [Serializable]
    public class HalconEdgeModel : HalconOperatorModelBase
    {
        [Category("I.输入")]
        [DisplayName("1.输入图像")]
        [Description("上游图像（GenImage/HObject）。子流程内通常绑定 &{输入.图像}")]
        [FormulaEditor(typeof(PluginDataProvider))]
        public FormulaBound<object> ImageSource { get; set; } = new FormulaBound<object>();

        [Category("II.参数")]
        [DisplayName("1.滤波类型")]
        [Description("Sobel 算子组合方式：sum_abs(常用)/sum_sqrt/sum_col/sum_row")]
        public string FilterType { get; set; } = "sum_abs";

        [Category("II.参数")]
        [DisplayName("2.孔径尺寸")]
        [Description("Sobel 滤波核尺寸（奇数）：3/5/7，越大抗噪越强、定位越粗")]
        public int ApertureSize { get; set; } = 3;

        [Category("II.参数")]
        [DisplayName("3.最小梯度")]
        [Description("梯度阈值下限（含），低于此梯度不视为边缘")]
        public int MinGray { get; set; } = 30;

        [Category("II.参数")]
        [DisplayName("4.最大梯度")]
        [Description("梯度阈值上限（含）")]
        public int MaxGray { get; set; } = 255;
    }
}