OBJECT DETECTION Archives

[C#/COMMON/ML.NET/.NET5] ONNX와 YOLOv5를 사용해 이미지 객체 인식하기

■ ONNX와 YOLOv5를 사용해 이미지 객체를 인식하는 방법을 보여준다. [소스 이미지] [결과 이미지] ▶ RectangleExtension.cs


using System.Drawing;

namespace TestProject
{
    /// <summary>
    /// 사각형 확장
    /// </summary>
    public static class RectangleExtension
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Method
        ////////////////////////////////////////////////////////////////////////////////////////// Static
        //////////////////////////////////////////////////////////////////////////////// Public

        #region 영역 구하기 - GetArea(rectangle)

        /// <summary>
        /// 영역 구하기
        /// </summary>
        /// <param name="rectangle">사각형</param>
        /// <returns>영역</returns>
        public static float GetArea(this RectangleF rectangle)
        {
            return rectangle.Width * rectangle.Height;
        }

        #endregion
    }
}

using System.Drawing;

namespace TestProject

{

/// <summary>

/// 사각형 확장

/// </summary>

public static class RectangleExtension

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Method

////////////////////////////////////////////////////////////////////////////////////////// Static

//////////////////////////////////////////////////////////////////////////////// Public

#region 영역 구하기 - GetArea(rectangle)

/// <summary>

/// 영역 구하기

/// </summary>

/// <param name="rectangle">사각형</param>

/// <returns>영역</returns>

public static float GetArea(this RectangleF rectangle)

{

return rectangle.Width * rectangle.Height;

}

#endregion

}

▶ YOLOModel.cs


using System.Collections.Generic;

namespace TestProject
{
    /// <summary>
    /// YOLO 모델
    /// </summary>
    public abstract class YOLOModel
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Property
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 너비 - Width

        /// <summary>
        /// 너비
        /// </summary>
        public abstract int Width { get; set; }

        #endregion
        #region 높이 - Height

        /// <summary>
        /// 높이
        /// </summary>
        public abstract int Height { get; set; }

        #endregion
        #region 깊이 - Depth

        /// <summary>
        /// 깊이
        /// </summary>
        public abstract int Depth { get; set; }

        #endregion
        #region 차원 - Dimension

        /// <summary>
        /// 차원
        /// </summary>
        public abstract int Dimension { get; set; }

        #endregion
        #region 스트라이드 배열 - StrideArray

        /// <summary>
        /// 스트라이드 배열
        /// </summary>
        public abstract float[] StrideArray { get; set; }

        #endregion
        #region 앵커 배열 - AnchorArray

        /// <summary>
        /// 앵커 배열
        /// </summary>
        public abstract float[][][] AnchorArray { get; set; }

        #endregion
        #region 도형 배열 - ShapeArray

        /// <summary>
        /// 도형 배열
        /// </summary>
        public abstract int[] ShapeArray { get; set; }

        #endregion
        #region 신뢰도 - Confidence

        /// <summary>
        /// 신뢰도
        /// </summary>
        public abstract float Confidence { get; set; }

        #endregion
        #region 다중 신뢰도 - MultipleConfidence

        /// <summary>
        /// 다중 신뢰도
        /// </summary>
        public abstract float MultipleConfidence { get; set; }

        #endregion
        #region 오버랩 - Overlap

        /// <summary>
        /// 오버랩
        /// </summary>
        public abstract float Overlap { get; set; }

        #endregion
        #region 출력 배열 - OutputArray

        /// <summary>
        /// 출력 배열
        /// </summary>
        public abstract string[] OutputArray { get; set; }

        #endregion
        #region 레이블 리스트 - LabelList

        /// <summary>
        /// 레이블 리스트
        /// </summary>
        public abstract List<YOLOLabel> LabelList { get; set; }

        #endregion
        #region 탐지 사용 여부 - UseDetect

        /// <summary>
        /// 탐지 사용 여부
        /// </summary>
        public abstract bool UseDetect { get; set; }

        #endregion
    }
}

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using System.Collections.Generic;

namespace TestProject

{

/// <summary>

/// YOLO 모델

/// </summary>

public abstract class YOLOModel

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Property

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 너비 - Width

/// <summary>

/// 너비

/// </summary>

public abstract int Width { get; set; }

#endregion

#region 높이 - Height

/// <summary>

/// 높이

/// </summary>

public abstract int Height { get; set; }

#endregion

#region 깊이 - Depth

/// <summary>

/// 깊이

/// </summary>

public abstract int Depth { get; set; }

#endregion

#region 차원 - Dimension

/// <summary>

/// 차원

/// </summary>

public abstract int Dimension { get; set; }

#endregion

#region 스트라이드 배열 - StrideArray

/// <summary>

/// 스트라이드 배열

/// </summary>

public abstract float[] StrideArray { get; set; }

#endregion

#region 앵커 배열 - AnchorArray

/// <summary>

/// 앵커 배열

/// </summary>

public abstract float[][][] AnchorArray { get; set; }

#endregion

#region 도형 배열 - ShapeArray

/// <summary>

/// 도형 배열

/// </summary>

public abstract int[] ShapeArray { get; set; }

#endregion

#region 신뢰도 - Confidence

/// <summary>

/// 신뢰도

/// </summary>

public abstract float Confidence { get; set; }

#endregion

#region 다중 신뢰도 - MultipleConfidence

/// <summary>

/// 다중 신뢰도

/// </summary>

public abstract float MultipleConfidence { get; set; }

#endregion

#region 오버랩 - Overlap

/// <summary>

/// 오버랩

/// </summary>

public abstract float Overlap { get; set; }

#endregion

#region 출력 배열 - OutputArray

/// <summary>

/// 출력 배열

/// </summary>

public abstract string[] OutputArray { get; set; }

#endregion

#region 레이블 리스트 - LabelList

/// <summary>

/// 레이블 리스트

/// </summary>

public abstract List<YOLOLabel> LabelList { get; set; }

#endregion

#region 탐지 사용 여부 - UseDetect

/// <summary>

/// 탐지 사용 여부

/// </summary>

public abstract bool UseDetect { get; set; }

#endregion

}

▶ YOLOCOCOP5Model.cs


using System.Collections.Generic;

namespace TestProject
{
    /// <summary>
    /// YOLO COCO P5 모델
    /// </summary>
    public class YOLOCOCOP5Model : YOLOModel
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Property
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 너비 - Width

        /// <summary>
        /// 너비
        /// </summary>
        public override int Width { get; set; } = 640;

        #endregion
        #region 높이 - Height

        /// <summary>
        /// 높이
        /// </summary>
        public override int Height { get; set; } = 640;

        #endregion
        #region 깊이 - Depth

        /// <summary>
        /// 깊이
        /// </summary>
        public override int Depth { get; set; } = 3;

        #endregion
        #region 차원 - Dimension

        /// <summary>
        /// 차원
        /// </summary>
        public override int Dimension { get; set; } = 85;

        #endregion
        #region 스트라이드 배열 - StrideArray

        /// <summary>
        /// 스트라이드 배열
        /// </summary>
        public override float[] StrideArray { get; set; } = new float[] { 8, 16, 32 };

        #endregion
        #region 앵커 배열 - AnchorArray

        /// <summary>
        /// 앵커 배열
        /// </summary>
        public override float[][][] AnchorArray { get; set; } = new float[][][]
        {
            new float[][] { new float[] { 010, 13 }, new float[] { 016, 030 }, new float[] { 033, 023 } },
            new float[][] { new float[] { 030, 61 }, new float[] { 062, 045 }, new float[] { 059, 119 } },
            new float[][] { new float[] { 116, 90 }, new float[] { 156, 198 }, new float[] { 373, 326 } }
        };

        #endregion
        #region 도형 배열 - ShapeArray

        /// <summary>
        /// 도형 배열
        /// </summary>
        public override int[] ShapeArray { get; set; } = new int[] { 80, 40, 20 };

        #endregion
        #region 신뢰도 - Confidence

        /// <summary>
        /// 신뢰도
        /// </summary>
        public override float Confidence { get; set; } = 0.20f;

        #endregion
        #region 다중 신뢰도 - MultipleConfidence

        /// <summary>
        /// 다중 신뢰도
        /// </summary>
        public override float MultipleConfidence { get; set; } = 0.25f;

        #endregion
        #region 오버랩 - Overlap

        /// <summary>
        /// 오버랩
        /// </summary>
        public override float Overlap { get; set; } = 0.45f;

        #endregion
        #region 출력 배열 - OutputArray

        /// <summary>
        /// 출력 배열
        /// </summary>
        public override string[] OutputArray { get; set; } = new[] { "output" };

        #endregion
        #region 레이블 리스트 - LabelList

        /// <summary>
        /// 레이블 리스트
        /// </summary>
        public override List<YOLOLabel> LabelList { get; set; } = new List<YOLOLabel>()
        {
            new YOLOLabel { ID = 1,  Name = "person"         },
            new YOLOLabel { ID = 2,  Name = "bicycle"        },
            new YOLOLabel { ID = 3,  Name = "car"            },
            new YOLOLabel { ID = 4,  Name = "motorcycle"     },
            new YOLOLabel { ID = 5,  Name = "airplane"       },
            new YOLOLabel { ID = 6,  Name = "bus"            },
            new YOLOLabel { ID = 7,  Name = "train"          },
            new YOLOLabel { ID = 8,  Name = "truck"          },
            new YOLOLabel { ID = 9,  Name = "boat"           },
            new YOLOLabel { ID = 10, Name = "traffic light"  },
            new YOLOLabel { ID = 11, Name = "fire hydrant"   },
            new YOLOLabel { ID = 12, Name = "stop sign"      },
            new YOLOLabel { ID = 13, Name = "parking meter"  },
            new YOLOLabel { ID = 14, Name = "bench"          },
            new YOLOLabel { ID = 15, Name = "bird"           },
            new YOLOLabel { ID = 16, Name = "cat"            },
            new YOLOLabel { ID = 17, Name = "dog"            },
            new YOLOLabel { ID = 18, Name = "horse"          },
            new YOLOLabel { ID = 19, Name = "sheep"          },
            new YOLOLabel { ID = 20, Name = "cow"            },
            new YOLOLabel { ID = 21, Name = "elephant"       },
            new YOLOLabel { ID = 22, Name = "bear"           },
            new YOLOLabel { ID = 23, Name = "zebra"          },
            new YOLOLabel { ID = 24, Name = "giraffe"        },
            new YOLOLabel { ID = 25, Name = "backpack"       },
            new YOLOLabel { ID = 26, Name = "umbrella"       },
            new YOLOLabel { ID = 27, Name = "handbag"        },
            new YOLOLabel { ID = 28, Name = "tie"            },
            new YOLOLabel { ID = 29, Name = "suitcase"       },
            new YOLOLabel { ID = 30, Name = "frisbee"        },
            new YOLOLabel { ID = 31, Name = "skis"           },
            new YOLOLabel { ID = 32, Name = "snowboard"      },
            new YOLOLabel { ID = 33, Name = "sports ball"    },
            new YOLOLabel { ID = 34, Name = "kite"           },
            new YOLOLabel { ID = 35, Name = "baseball bat"   },
            new YOLOLabel { ID = 36, Name = "baseball glove" },
            new YOLOLabel { ID = 37, Name = "skateboard"     },
            new YOLOLabel { ID = 38, Name = "surfboard"      },
            new YOLOLabel { ID = 39, Name = "tennis racket"  },
            new YOLOLabel { ID = 40, Name = "bottle"         },
            new YOLOLabel { ID = 41, Name = "wine glass"     },
            new YOLOLabel { ID = 42, Name = "cup"            },
            new YOLOLabel { ID = 43, Name = "fork"           },
            new YOLOLabel { ID = 44, Name = "knife"          },
            new YOLOLabel { ID = 45, Name = "spoon"          },
            new YOLOLabel { ID = 46, Name = "bowl"           },
            new YOLOLabel { ID = 47, Name = "banana"         },
            new YOLOLabel { ID = 48, Name = "apple"          },
            new YOLOLabel { ID = 49, Name = "sandwich"       },
            new YOLOLabel { ID = 50, Name = "orange"         },
            new YOLOLabel { ID = 51, Name = "broccoli"       },
            new YOLOLabel { ID = 52, Name = "carrot"         },
            new YOLOLabel { ID = 53, Name = "hot dog"        },
            new YOLOLabel { ID = 54, Name = "pizza"          },
            new YOLOLabel { ID = 55, Name = "donut"          },
            new YOLOLabel { ID = 56, Name = "cake"           },
            new YOLOLabel { ID = 57, Name = "chair"          },
            new YOLOLabel { ID = 58, Name = "couch"          },
            new YOLOLabel { ID = 59, Name = "potted plant"   },
            new YOLOLabel { ID = 60, Name = "bed"            },
            new YOLOLabel { ID = 61, Name = "dining table"   },
            new YOLOLabel { ID = 62, Name = "toilet"         },
            new YOLOLabel { ID = 63, Name = "tv"             },
            new YOLOLabel { ID = 64, Name = "laptop"         },
            new YOLOLabel { ID = 65, Name = "mouse"          },
            new YOLOLabel { ID = 66, Name = "remote"         },
            new YOLOLabel { ID = 67, Name = "keyboard"       },
            new YOLOLabel { ID = 68, Name = "cell phone"     },
            new YOLOLabel { ID = 69, Name = "microwave"      },
            new YOLOLabel { ID = 70, Name = "oven"           },
            new YOLOLabel { ID = 71, Name = "toaster"        },
            new YOLOLabel { ID = 72, Name = "sink"           },
            new YOLOLabel { ID = 73, Name = "refrigerator"   },
            new YOLOLabel { ID = 74, Name = "book"           },
            new YOLOLabel { ID = 75, Name = "clock"          },
            new YOLOLabel { ID = 76, Name = "vase"           },
            new YOLOLabel { ID = 77, Name = "scissors"       },
            new YOLOLabel { ID = 78, Name = "teddy bear"     },
            new YOLOLabel { ID = 79, Name = "hair drier"     },
            new YOLOLabel { ID = 80, Name = "toothbrush"     }
        };

        #endregion
        #region 탐지 사용 여부 - UseDetect

        /// <summary>
        /// 탐지 사용 여부
        /// </summary>
        public override bool UseDetect { get; set; } = true;

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - YOLOCOCOP5Model()

        /// <summary>
        /// 생성자
        /// </summary>
        public YOLOCOCOP5Model()
        {
        }

        #endregion
    }
}

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using System.Collections.Generic;

namespace TestProject

{

/// <summary>

/// YOLO COCO P5 모델

/// </summary>

public class YOLOCOCOP5Model : YOLOModel

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Property

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 너비 - Width

/// <summary>

/// 너비

/// </summary>

public override int Width { get; set; } = 640;

#endregion

#region 높이 - Height

/// <summary>

/// 높이

/// </summary>

public override int Height { get; set; } = 640;

#endregion

#region 깊이 - Depth

/// <summary>

/// 깊이

/// </summary>

public override int Depth { get; set; } = 3;

#endregion

#region 차원 - Dimension

/// <summary>

/// 차원

/// </summary>

public override int Dimension { get; set; } = 85;

#endregion

#region 스트라이드 배열 - StrideArray

/// <summary>

/// 스트라이드 배열

/// </summary>

public override float[] StrideArray { get; set; } = new float[] { 8, 16, 32 };

#endregion

#region 앵커 배열 - AnchorArray

/// <summary>

/// 앵커 배열

/// </summary>

public override float[][][] AnchorArray { get; set; } = new float[][][]

{

new float[][] { new float[] { 010, 13 }, new float[] { 016, 030 }, new float[] { 033, 023 } },

new float[][] { new float[] { 030, 61 }, new float[] { 062, 045 }, new float[] { 059, 119 } },

new float[][] { new float[] { 116, 90 }, new float[] { 156, 198 }, new float[] { 373, 326 } }

};

#endregion

#region 도형 배열 - ShapeArray

/// <summary>

/// 도형 배열

/// </summary>

public override int[] ShapeArray { get; set; } = new int[] { 80, 40, 20 };

#endregion

#region 신뢰도 - Confidence

/// <summary>

/// 신뢰도

/// </summary>

public override float Confidence { get; set; } = 0.20f;

#endregion

#region 다중 신뢰도 - MultipleConfidence

/// <summary>

/// 다중 신뢰도

/// </summary>

public override float MultipleConfidence { get; set; } = 0.25f;

#endregion

#region 오버랩 - Overlap

/// <summary>

/// 오버랩

/// </summary>

public override float Overlap { get; set; } = 0.45f;

#endregion

#region 출력 배열 - OutputArray

/// <summary>

/// 출력 배열

/// </summary>

public override string[] OutputArray { get; set; } = new[] { "output" };

#endregion

#region 레이블 리스트 - LabelList

/// <summary>

/// 레이블 리스트

/// </summary>

public override List<YOLOLabel> LabelList { get; set; } = new List<YOLOLabel>()

{

new YOLOLabel { ID = 1, Name = "person" },

new YOLOLabel { ID = 2, Name = "bicycle" },

new YOLOLabel { ID = 3, Name = "car" },

new YOLOLabel { ID = 4, Name = "motorcycle" },

new YOLOLabel { ID = 5, Name = "airplane" },

new YOLOLabel { ID = 6, Name = "bus" },

new YOLOLabel { ID = 7, Name = "train" },

new YOLOLabel { ID = 8, Name = "truck" },

new YOLOLabel { ID = 9, Name = "boat" },

new YOLOLabel { ID = 10, Name = "traffic light" },

new YOLOLabel { ID = 11, Name = "fire hydrant" },

new YOLOLabel { ID = 12, Name = "stop sign" },

new YOLOLabel { ID = 13, Name = "parking meter" },

new YOLOLabel { ID = 14, Name = "bench" },

new YOLOLabel { ID = 15, Name = "bird" },

new YOLOLabel { ID = 16, Name = "cat" },

new YOLOLabel { ID = 17, Name = "dog" },

new YOLOLabel { ID = 18, Name = "horse" },

new YOLOLabel { ID = 19, Name = "sheep" },

new YOLOLabel { ID = 20, Name = "cow" },

new YOLOLabel { ID = 21, Name = "elephant" },

new YOLOLabel { ID = 22, Name = "bear" },

new YOLOLabel { ID = 23, Name = "zebra" },

new YOLOLabel { ID = 24, Name = "giraffe" },

new YOLOLabel { ID = 25, Name = "backpack" },

new YOLOLabel { ID = 26, Name = "umbrella" },

new YOLOLabel { ID = 27, Name = "handbag" },

new YOLOLabel { ID = 28, Name = "tie" },

new YOLOLabel { ID = 29, Name = "suitcase" },

new YOLOLabel { ID = 30, Name = "frisbee" },

new YOLOLabel { ID = 31, Name = "skis" },

new YOLOLabel { ID = 32, Name = "snowboard" },

new YOLOLabel { ID = 33, Name = "sports ball" },

new YOLOLabel { ID = 34, Name = "kite" },

new YOLOLabel { ID = 35, Name = "baseball bat" },

new YOLOLabel { ID = 36, Name = "baseball glove" },

new YOLOLabel { ID = 37, Name = "skateboard" },

new YOLOLabel { ID = 38, Name = "surfboard" },

new YOLOLabel { ID = 39, Name = "tennis racket" },

new YOLOLabel { ID = 40, Name = "bottle" },

new YOLOLabel { ID = 41, Name = "wine glass" },

new YOLOLabel { ID = 42, Name = "cup" },

new YOLOLabel { ID = 43, Name = "fork" },

new YOLOLabel { ID = 44, Name = "knife" },

new YOLOLabel { ID = 45, Name = "spoon" },

new YOLOLabel { ID = 46, Name = "bowl" },

new YOLOLabel { ID = 47, Name = "banana" },

new YOLOLabel { ID = 48, Name = "apple" },

new YOLOLabel { ID = 49, Name = "sandwich" },

new YOLOLabel { ID = 50, Name = "orange" },

new YOLOLabel { ID = 51, Name = "broccoli" },

new YOLOLabel { ID = 52, Name = "carrot" },

new YOLOLabel { ID = 53, Name = "hot dog" },

new YOLOLabel { ID = 54, Name = "pizza" },

new YOLOLabel { ID = 55, Name = "donut" },

new YOLOLabel { ID = 56, Name = "cake" },

new YOLOLabel { ID = 57, Name = "chair" },

new YOLOLabel { ID = 58, Name = "couch" },

new YOLOLabel { ID = 59, Name = "potted plant" },

new YOLOLabel { ID = 60, Name = "bed" },

new YOLOLabel { ID = 61, Name = "dining table" },

new YOLOLabel { ID = 62, Name = "toilet" },

new YOLOLabel { ID = 63, Name = "tv" },

new YOLOLabel { ID = 64, Name = "laptop" },

new YOLOLabel { ID = 65, Name = "mouse" },

new YOLOLabel { ID = 66, Name = "remote" },

new YOLOLabel { ID = 67, Name = "keyboard" },

new YOLOLabel { ID = 68, Name = "cell phone" },

new YOLOLabel { ID = 69, Name = "microwave" },

new YOLOLabel { ID = 70, Name = "oven" },

new YOLOLabel { ID = 71, Name = "toaster" },

new YOLOLabel { ID = 72, Name = "sink" },

new YOLOLabel { ID = 73, Name = "refrigerator" },

new YOLOLabel { ID = 74, Name = "book" },

new YOLOLabel { ID = 75, Name = "clock" },

new YOLOLabel { ID = 76, Name = "vase" },

new YOLOLabel { ID = 77, Name = "scissors" },

new YOLOLabel { ID = 78, Name = "teddy bear" },

new YOLOLabel { ID = 79, Name = "hair drier" },

new YOLOLabel { ID = 80, Name = "toothbrush" }

};

#endregion

#region 탐지 사용 여부 - UseDetect

/// <summary>

/// 탐지 사용 여부

/// </summary>

public override bool UseDetect { get; set; } = true;

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - YOLOCOCOP5Model()

/// <summary>

/// 생성자

/// </summary>

public YOLOCOCOP5Model()

{

}

#endregion

}

[C#/WINFORM] YOLO 이미지 객체 인식하기

■ YOLO 이미지 객체를 인식하는 방법을 보여준다. [TestProject 프로젝트] ▶ MainForm.cs


using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Drawing;
using System.IO;
using System.Linq;
using System.Threading.Tasks;
using System.Windows.Forms;

using TestCommon;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Field
        ////////////////////////////////////////////////////////////////////////////////////////// Private

        #region Field

        /// <summary>
        /// YOLO 레퍼
        /// </summary>
        private YoloWrapper wrapper;

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            this.processImageButton.Enabled = false;

            this.sourceDataGridView.AutoGenerateColumns = false;
            this.resultDataGridView.AutoGenerateColumns = false;

            IEnumerable<ImageInfo> imageInfoEnumerable = new DirectoryImageReader().Analyze(@".\IMAGE");

            this.sourceDataGridView.DataSource = imageInfoEnumerable.ToList();

            ConfigurationDetector configurationDetector = new ConfigurationDetector();

            YoloConfiguration configuration = configurationDetector.Detect();

            if(configuration == null)
            {
                MessageBox.Show("YOLO 구성 탐지를 실패했습니다.", "INFORMATION", MessageBoxButtons.OK, MessageBoxIcon.Information);

                return;
            }

            this.toolStripStatusLabel1.Text = string.Empty;
            this.toolStripStatusLabel2.Text = string.Empty;

            FormClosing += Form_FormClosing;
            this.sourceDataGridView.SelectionChanged += sourceDataGridView_SelectionChanged;
            this.sourceDataGridView.KeyDown          += sourceDataGridView_KeyDown;
            this.processImageButton.Click            += processImageButton_Click;
            this.resultDataGridView.SelectionChanged += resultDataGridView_SelectionChanged;

            Task.Run(() => Initialize(configuration));
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Method
        ////////////////////////////////////////////////////////////////////////////////////////// Private
        //////////////////////////////////////////////////////////////////////////////// Event

        #region 폼 닫을 경우 처리하기 - Form_FormClosing(sender, e)

        /// <summary>
        /// 폼 닫을 경우 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void Form_FormClosing(object sender, FormClosingEventArgs e)
        {
            this.wrapper.Dispose();
        }

        #endregion
        #region 소스 데이터 그리드 뷰 선택 변경시 처리하기 - sourceDataGridView_SelectionChanged(sender, e)

        /// <summary>
        /// 소스 데이터 그리드 뷰 선택 변경시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void sourceDataGridView_SelectionChanged(object sender, EventArgs e)
        {
            Image previousImage = this.pictureBox.Image;

            ImageInfo imageInfo = GetCurrentImageInfo();

            this.pictureBox.Image = Image.FromFile(imageInfo.FilePath);

            previousImage?.Dispose();

            this.resultDataGridView.DataSource = null;
        }

        #endregion
        #region 소스 데이터 그리드 뷰 키 DOWN 처리하기 - sourceDataGridView_KeyDown(sender, e)

        /// <summary>
        /// 소스 데이터 그리드 뷰 키 DOWN 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void sourceDataGridView_KeyDown(object sender, KeyEventArgs e)
        {
            if(e.KeyCode == Keys.Space)
            {
                Detect();
            }
        }

        #endregion
        #region 이미지 처리 버튼 클릭시 처리하기 - processImageButton_Click(sender, e)

        /// <summary>
        /// 이미지 처리 버튼 클릭시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void processImageButton_Click(object sender, EventArgs e)
        {
            Detect();
        }

        #endregion
        #region 결과 데이터 그리드 뷰 선택 변경시 처리하기 - resultDataGridView_SelectionChanged(sender, e)

        /// <summary>
        /// 결과 데이터 그리드 뷰 선택 변경시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void resultDataGridView_SelectionChanged(object sender, EventArgs e)
        {
            if(!this.resultDataGridView.Focused)
            {
                return;
            }

            List<YoloItem> itemList = this.resultDataGridView.DataSource as List<YoloItem>;

            YoloItem item = this.resultDataGridView.CurrentRow?.DataBoundItem as YoloItem;

            DrawImage(itemList, item);
        }

        #endregion
        #region 폴더 열기 메뉴 항목 클릭시 처리하기 - openFolderMenuItem_Click(sender, e)

        /// <summary>
        /// 폴더 열기 메뉴 항목 클릭시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void openFolderMenuItem_Click(object sender, EventArgs e)
        {
            DialogResult result = this.folderBrowserDialog.ShowDialog();

            if(result != DialogResult.OK)
            {
                return;
            }

            IEnumerable<ImageInfo> imageInfoEnumerable = new DirectoryImageReader().Analyze(this.folderBrowserDialog.SelectedPath);

            this.sourceDataGridView.DataSource = imageInfoEnumerable.ToList();
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////// Function

        #region 초기화 하기 - Initialize(configuration)

        /// <summary>
        /// 초기화 하기
        /// </summary>
        /// <param name="configuration">YOLO 구성</param>
        private void Initialize(YoloConfiguration configuration)
        {
            Stopwatch stopwatch = new Stopwatch();

            stopwatch.Start();

            this.wrapper = new YoloWrapper(configuration.ConfigurationFilePath, configuration.WeightFilePath, configuration.NameFilePath, 0);

            stopwatch.Stop();

            this.statusStrip.Invoke
            (
                new MethodInvoker
                (
                    delegate()
                    {
                        this.toolStripStatusLabel1.Text = string.Format
                        (
                            "초기화 시간 : {0} 밀리초, 탐지 시스템 : {1} ({2})",
                            stopwatch.Elapsed.TotalMilliseconds,
                            this.wrapper.DetectionSystemType,
                            this.wrapper.EnvironmentReport.GraphicDeviceName
                        );
                    }
                )
            );

            this.processImageButton.Invoke(new MethodInvoker(delegate () { this.processImageButton.Enabled = true; }));
        }

        #endregion
        #region 현재 이미지 정보 구하기 - GetCurrentImageInfo()

        /// <summary>
        /// 현재 이미지 정보 구하기
        /// </summary>
        /// <returns>현재 이미지 정보</returns>
        private ImageInfo GetCurrentImageInfo()
        {
            ImageInfo imageInfo = this.sourceDataGridView.CurrentRow?.DataBoundItem as ImageInfo;

            return imageInfo;
        }

        #endregion
        #region 펜 구하기 - GetPen(confidence, width)

        /// <summary>
        /// 펜 구하기
        /// </summary>
        /// <param name="confidence">확신도</param>
        /// <param name="width">너비</param>
        /// <returns>펜</returns>
        private Pen GetPen(double confidence, int width)
        {
            int size = width / 100;

            if(confidence > 0.5)
            {
                return new Pen(Brushes.GreenYellow, size);
            }
            else if(confidence > 0.2 && confidence <= 0.5)
            {
                return new Pen(Brushes.Orange, size);
            }

            return new Pen(Brushes.DarkRed, size);
        }

        #endregion
        #region 이미지 그리기 - DrawImage(itemList, selectedItem)

        /// <summary>
        /// 이미지 그리기
        /// </summary>
        /// <param name="itemList">이미지 리스트</param>
        /// <param name="selectedItem">선택 이미지</param>
        private void DrawImage(List<YoloItem> itemList, YoloItem selectedItem = null)
        {
            ImageInfo imageInfo = GetCurrentImageInfo();

            Image image = Image.FromFile(imageInfo.FilePath);

            using(Graphics graphics = Graphics.FromImage(image))
            {
                foreach(YoloItem item in itemList)
                {
                    int x      = item.X;
                    int y      = item.Y;
                    int width  = item.Width;
                    int height = item.Height;

                    using(SolidBrush overlayBrush = new SolidBrush(Color.FromArgb(150, 255, 255, 102)))
                    {
                        using(Pen pen = GetPen(item.Confidence, image.Width))
                        {
                            if(item.Equals(selectedItem))
                            {
                                graphics.FillRectangle(overlayBrush, x, y, width, height);
                            }

                            graphics.DrawRectangle(pen, x, y, width, height);

                            graphics.Flush();
                        }
                    }
                }
            }

            Image previousImage = this.pictureBox.Image;

            this.pictureBox.Image = image;

            previousImage?.Dispose();
        }

        #endregion
        #region 탐지하기 - Detect()

        /// <summary>
        /// 탐지하기
        /// </summary>
        private void Detect()
        {
            if(this.wrapper == null)
            {
                return;
            }

            bool memoryTransfer = true;

            ImageInfo imageInfo = GetCurrentImageInfo();

            byte[] imageByteArray = File.ReadAllBytes(imageInfo.FilePath);

            Stopwatch stopwatch = new Stopwatch();

            stopwatch.Start();

            List<YoloItem> itemList;

            if(memoryTransfer)
            {
                itemList = this.wrapper.Detect(imageByteArray).ToList();
            }
            else
            {
                itemList = this.wrapper.Detect(imageInfo.FilePath).ToList();
            }

            stopwatch.Stop();

            this.toolStripStatusLabel2.Text = $"이미지 처리 시간 : {stopwatch.Elapsed.TotalMilliseconds:0.00} 밀리초";

            this.resultDataGridView.DataSource = itemList;

            DrawImage(itemList);
        }

        #endregion
    }
}

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using System;

using System.Collections.Generic;

using System.Diagnostics;

using System.Drawing;

using System.IO;

using System.Linq;

using System.Threading.Tasks;

using System.Windows.Forms;

using TestCommon;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Field

////////////////////////////////////////////////////////////////////////////////////////// Private

#region Field

/// <summary>

/// YOLO 레퍼

/// </summary>

private YoloWrapper wrapper;

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

this.processImageButton.Enabled = false;

this.sourceDataGridView.AutoGenerateColumns = false;

this.resultDataGridView.AutoGenerateColumns = false;

IEnumerable<ImageInfo> imageInfoEnumerable = new DirectoryImageReader().Analyze(@".\IMAGE");

this.sourceDataGridView.DataSource = imageInfoEnumerable.ToList();

ConfigurationDetector configurationDetector = new ConfigurationDetector();

YoloConfiguration configuration = configurationDetector.Detect();

if(configuration == null)

{

MessageBox.Show("YOLO 구성 탐지를 실패했습니다.", "INFORMATION", MessageBoxButtons.OK, MessageBoxIcon.Information);

return;

}

this.toolStripStatusLabel1.Text = string.Empty;

this.toolStripStatusLabel2.Text = string.Empty;

FormClosing += Form_FormClosing;

this.sourceDataGridView.SelectionChanged += sourceDataGridView_SelectionChanged;

this.sourceDataGridView.KeyDown += sourceDataGridView_KeyDown;

this.processImageButton.Click += processImageButton_Click;

this.resultDataGridView.SelectionChanged += resultDataGridView_SelectionChanged;

Task.Run(() => Initialize(configuration));

}

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Method

////////////////////////////////////////////////////////////////////////////////////////// Private

//////////////////////////////////////////////////////////////////////////////// Event

#region 폼 닫을 경우 처리하기 - Form_FormClosing(sender, e)

/// <summary>

/// 폼 닫을 경우 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void Form_FormClosing(object sender, FormClosingEventArgs e)

{

this.wrapper.Dispose();

}

#endregion

#region 소스 데이터 그리드 뷰 선택 변경시 처리하기 - sourceDataGridView_SelectionChanged(sender, e)

/// <summary>

/// 소스 데이터 그리드 뷰 선택 변경시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void sourceDataGridView_SelectionChanged(object sender, EventArgs e)

{

Image previousImage = this.pictureBox.Image;

ImageInfo imageInfo = GetCurrentImageInfo();

this.pictureBox.Image = Image.FromFile(imageInfo.FilePath);

previousImage?.Dispose();

this.resultDataGridView.DataSource = null;

}

#endregion

#region 소스 데이터 그리드 뷰 키 DOWN 처리하기 - sourceDataGridView_KeyDown(sender, e)

/// <summary>

/// 소스 데이터 그리드 뷰 키 DOWN 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void sourceDataGridView_KeyDown(object sender, KeyEventArgs e)

{

if(e.KeyCode == Keys.Space)

{

Detect();

}

#endregion

#region 이미지 처리 버튼 클릭시 처리하기 - processImageButton_Click(sender, e)

/// <summary>

/// 이미지 처리 버튼 클릭시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void processImageButton_Click(object sender, EventArgs e)

{

Detect();

}

#endregion

#region 결과 데이터 그리드 뷰 선택 변경시 처리하기 - resultDataGridView_SelectionChanged(sender, e)

/// <summary>

/// 결과 데이터 그리드 뷰 선택 변경시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void resultDataGridView_SelectionChanged(object sender, EventArgs e)

{

if(!this.resultDataGridView.Focused)

{

return;

}

List<YoloItem> itemList = this.resultDataGridView.DataSource as List<YoloItem>;

YoloItem item = this.resultDataGridView.CurrentRow?.DataBoundItem as YoloItem;

DrawImage(itemList, item);

}

#endregion

#region 폴더 열기 메뉴 항목 클릭시 처리하기 - openFolderMenuItem_Click(sender, e)

/// <summary>

/// 폴더 열기 메뉴 항목 클릭시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void openFolderMenuItem_Click(object sender, EventArgs e)

{

DialogResult result = this.folderBrowserDialog.ShowDialog();

if(result != DialogResult.OK)

{

return;

}

IEnumerable<ImageInfo> imageInfoEnumerable = new DirectoryImageReader().Analyze(this.folderBrowserDialog.SelectedPath);

this.sourceDataGridView.DataSource = imageInfoEnumerable.ToList();

}

#endregion

//////////////////////////////////////////////////////////////////////////////// Function

#region 초기화 하기 - Initialize(configuration)

/// <summary>

/// 초기화 하기

/// </summary>

/// <param name="configuration">YOLO 구성</param>

private void Initialize(YoloConfiguration configuration)

{

Stopwatch stopwatch = new Stopwatch();

stopwatch.Start();

this.wrapper = new YoloWrapper(configuration.ConfigurationFilePath, configuration.WeightFilePath, configuration.NameFilePath, 0);

stopwatch.Stop();

this.statusStrip.Invoke

(

new MethodInvoker

(

delegate()

{

this.toolStripStatusLabel1.Text = string.Format

(

"초기화 시간 : {0} 밀리초, 탐지 시스템 : {1} ({2})",

stopwatch.Elapsed.TotalMilliseconds,

this.wrapper.DetectionSystemType,

this.wrapper.EnvironmentReport.GraphicDeviceName

);

}

)

);

this.processImageButton.Invoke(new MethodInvoker(delegate () { this.processImageButton.Enabled = true; }));

}

#endregion

#region 현재 이미지 정보 구하기 - GetCurrentImageInfo()

/// <summary>

/// 현재 이미지 정보 구하기

/// </summary>

/// <returns>현재 이미지 정보</returns>

private ImageInfo GetCurrentImageInfo()

{

ImageInfo imageInfo = this.sourceDataGridView.CurrentRow?.DataBoundItem as ImageInfo;

return imageInfo;

}

#endregion

#region 펜 구하기 - GetPen(confidence, width)

/// <summary>

/// 펜 구하기

/// </summary>

/// <param name="confidence">확신도</param>

/// <param name="width">너비</param>

/// <returns>펜</returns>

private Pen GetPen(double confidence, int width)

{

int size = width / 100;

if(confidence > 0.5)

{

return new Pen(Brushes.GreenYellow, size);

}

else if(confidence > 0.2 && confidence <= 0.5)

{

return new Pen(Brushes.Orange, size);

}

return new Pen(Brushes.DarkRed, size);

}

#endregion

#region 이미지 그리기 - DrawImage(itemList, selectedItem)

/// <summary>

/// 이미지 그리기

/// </summary>

/// <param name="itemList">이미지 리스트</param>

/// <param name="selectedItem">선택 이미지</param>

private void DrawImage(List<YoloItem> itemList, YoloItem selectedItem = null)

{

ImageInfo imageInfo = GetCurrentImageInfo();

Image image = Image.FromFile(imageInfo.FilePath);

using(Graphics graphics = Graphics.FromImage(image))

{

foreach(YoloItem item in itemList)

{

int x = item.X;

int y = item.Y;

int width = item.Width;

int height = item.Height;

using(SolidBrush overlayBrush = new SolidBrush(Color.FromArgb(150, 255, 255, 102)))

{

using(Pen pen = GetPen(item.Confidence, image.Width))

{

if(item.Equals(selectedItem))

{

graphics.FillRectangle(overlayBrush, x, y, width, height);

}

graphics.DrawRectangle(pen, x, y, width, height);

graphics.Flush();

}

Image previousImage = this.pictureBox.Image;

this.pictureBox.Image = image;

previousImage?.Dispose();

}

#endregion

#region 탐지하기 - Detect()

/// <summary>

/// 탐지하기

/// </summary>

private void Detect()

{

if(this.wrapper == null)

{

return;

}

bool memoryTransfer = true;

ImageInfo imageInfo = GetCurrentImageInfo();

byte[] imageByteArray = File.ReadAllBytes(imageInfo.FilePath);

Stopwatch stopwatch = new Stopwatch();

stopwatch.Start();

List<YoloItem> itemList;

if(memoryTransfer)

{

itemList = this.wrapper.Detect(imageByteArray).ToList();

}

else

{

itemList = this.wrapper.Detect(imageInfo.FilePath).ToList();

}

stopwatch.Stop();

this.toolStripStatusLabel2.Text = $"이미지 처리 시간 : {stopwatch.Elapsed.TotalMilliseconds:0.00} 밀리초";

this.resultDataGridView.DataSource = itemList;

DrawImage(itemList);

}

#endregion

}

TestSolution.zip YOLOv3.zip

[C#/WINFORM] 텐서플로우를 사용해 물체 인식하기

■ 텐서플로우를 사용해 물체를 인식하는 방법을 보여준다. ▶ MainForm.cs


using System;
using System.Drawing;
using System.Drawing.Imaging;
using System.IO;
using System.Windows.Forms;

using AForge.Video;
using AForge.Video.DirectShow;

using TensorFlow;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Field
        ////////////////////////////////////////////////////////////////////////////////////////// Private

        #region Field

        /// <summary>
        /// 디스플레이 레이블 그래픽스
        /// </summary>
        private Graphics displayLabelGraphics = null;

        /// <summary>
        /// 필터 정보 컬렉션
        /// </summary>
        private FilterInfoCollection filterInfoCollection = null;

        /// <summary>
        /// 비디오 캡처 장치
        /// </summary>
        private VideoCaptureDevice videoCaptureDevice = null;


        /// <summary>
        /// 모델 배열
        /// </summary>
        private byte[] modelArray = null;

        /// <summary>
        /// 레이블 배열
        /// </summary>
        private string[] labelArray = null;


        /// <summary>
        /// 텐서플로우 그래프
        /// </summary>
        private TFGraph graph = null;

        /// <summary>
        /// 텐서플로우 세션
        /// </summary>
        private TFSession session = null;

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region MainForm

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            #region 이벤트를 설정한다.

            Load                   += Form_Load;
            FormClosing            += Form_FormClosing;
            this.startButton.Click += startButton_Click;

            #endregion
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Method
        ////////////////////////////////////////////////////////////////////////////////////////// Private
        //////////////////////////////////////////////////////////////////////////////// Event

        #region 폼 로드시 처리하기 - Form_Load(sender, e)

        /// <summary>
        /// 폼 로드시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void Form_Load(object sender, EventArgs e)
        {
            this.displayLabelGraphics = this.displayLabel.CreateGraphics();

            #region 카메라 장치 콤보 박스를 설정한다.

            this.filterInfoCollection = new FilterInfoCollection(FilterCategory.VideoInputDevice);

            for(int i = 0; i < this.filterInfoCollection.Count; i++)
            {
                this.cameraDeviceComboBox.Items.Add(this.filterInfoCollection[i].Name);
            }

            if(this.cameraDeviceComboBox.Items.Count > 0)
            {
                this.cameraDeviceComboBox.SelectedIndex = 0;
            }

            #endregion
            #region 시작 버튼을 설정한다.

            this.startButton.Enabled = (this.cameraDeviceComboBox.Items.Count > 0);

            #endregion

            #region 모델 배열을 설정한다.

            this.modelArray = File.ReadAllBytes("DATA\\frozen_process_no_filter_tiny.pb");

            #endregion
            #region 레이블 배열을 설정한다.

            this.labelArray = File.ReadAllLines("DATA\\yolo_labels.txt");

            #endregion
            #region 텐서플로우 그래프를 설정한다.

            this.graph = new TFGraph();

            this.graph.Import(this.modelArray, "");

            #endregion
            #region 텐서플로우 세션을 설정한다.

            this.session = new TFSession(graph);

            #endregion

            Bitmap bitmap = new Bitmap(100, 100, PixelFormat.Format24bppRgb);

            Predict(bitmap);
        }

        #endregion
        #region 폼 닫을 경우 처리하기 - Form_FormClosing(sender, e)

        /// <summary>
        /// 폼 닫을 경우 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void Form_FormClosing(object sender, FormClosingEventArgs e)
        {
            StopCameraCaoture();
        }

        #endregion
        #region 시작 버튼 클릭시 처리하기 - startButton_Click(sender, e)

        /// <summary>
        /// 시작 버튼 클릭시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void startButton_Click(object sender, EventArgs e)
        {
            if(this.startButton.Text == "시작")
            {
                this.startButton.Text = "중지";

                StartCameraCapture();
            }
            else
            {
                StopCameraCaoture();

                this.startButton.Text = "시작";
            }
        }

        #endregion
        #region 비디오 캡처 장치 신규 프레임 처리하기 - videoCaptureDevice_NewFrame(sender, e)

        /// <summary>
        /// 비디오 캡처 장치 신규 프레임 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void videoCaptureDevice_NewFrame(object sender, NewFrameEventArgs e)
        {
            Bitmap bitmap = e.Frame;

            TFTensor[] outputTensorArray = Predict(bitmap);

            float[,] rectangleArray   = (float[,])outputTensorArray[0].GetValue();
            float[]  probabilityArray = (float[] )outputTensorArray[1].GetValue();
            long[]   labelIndexArray  = (long[]  )outputTensorArray[2].GetValue();

            using(Graphics graphics = Graphics.FromImage(bitmap))
            {
                for(int i = 0; i < probabilityArray.Length; i++)
                {
                    if(probabilityArray[i] > 0.2)
                    {
                        int rectangleLeft   = (int)(rectangleArray[i, 0] * (float)bitmap.Width );
                        int rectangleTop    = (int)(rectangleArray[i, 1] * (float)bitmap.Height);
                        int rectangleWidth  = (int)(rectangleArray[i, 2] * (float)bitmap.Width );
                        int rectangleHeight = (int)(rectangleArray[i, 3] * (float)bitmap.Height);

                        graphics.DrawRectangle
                        (
                            new Pen(Color.Red, 2),
                            rectangleLeft - rectangleWidth  / 2,
                            rectangleTop  - rectangleHeight / 2,
                            rectangleWidth,
                            rectangleHeight
                        );

                        string label = this.labelArray[labelIndexArray[i]] + " " + probabilityArray[i].ToString();

                        graphics.DrawString
                        (
                            label,
                            Font,
                            Brushes.Red,
                            rectangleLeft - rectangleWidth  / 2,
                            rectangleTop  - rectangleHeight / 2
                        );
                    }
                }
            }

            this.displayLabelGraphics.DrawImage(bitmap, 0, 0, this.displayLabel.Width, this.displayLabel.Height);
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////// Function

        #region 카메라 캡처 시작하기 - StartCameraCapture()

        /// <summary>
        /// 카메라 캡처 시작하기
        /// </summary>
        private void StartCameraCapture()
        {
            if(this.videoCaptureDevice == null || !this.videoCaptureDevice.IsRunning)
            {
                FilterInfo filterInfo = this.filterInfoCollection[this.cameraDeviceComboBox.SelectedIndex];

                this.videoCaptureDevice = new VideoCaptureDevice(filterInfo.MonikerString);

                this.videoCaptureDevice.NewFrame += videoCaptureDevice_NewFrame;

                this.videoCaptureDevice.Start();
            }
        }

        #endregion
        #region 카메라 캡처 중단하기 - StopCameraCaoture()

        /// <summary>
        /// 카메라 캡처 중단하기
        /// </summary>
        private void StopCameraCaoture()
        {
            if(this.videoCaptureDevice != null && this.videoCaptureDevice.IsRunning)
            {
                this.videoCaptureDevice.NewFrame -= videoCaptureDevice_NewFrame;

                this.videoCaptureDevice.SignalToStop();

                this.videoCaptureDevice.WaitForStop();

                this.videoCaptureDevice = null;
            }
        }

        #endregion

        #region 텐서 구하기 - GetTensor(sourceArray)

        /// <summary>
        /// 텐서 구하기
        /// </summary>
        /// <param name="sourceArray">소스 배열</param>
        /// <returns>텐서</returns>
        private TFTensor GetTensor(byte[] sourceArray)
        {
            TFGraph  graph  = new TFGraph();
            TFOutput input  = graph.Placeholder(TFDataType.String);
            TFOutput output = graph.Cast(graph.DecodeJpeg(contents : input, channels : 3), DstT : TFDataType.Float);
            TFTensor tensor = TFTensor.CreateString(sourceArray);

            using(TFSession session = new TFSession(graph))
            {
                TFTensor[] normalizedTensorArray = session.Run
                (
                    inputs      : new[] { input  },
                    outputs     : new[] { output },
                    inputValues : new[] { tensor }
                );

                return normalizedTensorArray[0];
            }
        }

        #endregion
        #region 예측하기 - Predict(bitmap)

        /// <summary>
        /// 예측하기
        /// </summary>
        /// <param name="bitmap">비트맵</param>
        /// <returns>결과 텐서 배열</returns>
        private TFTensor[] Predict(Bitmap bitmap)
        {
            MemoryStream memoryStream = new MemoryStream();

            bitmap.Save(memoryStream, ImageFormat.Jpeg);

            TFTensor tensor = GetTensor(memoryStream.GetBuffer());

            TFSession.Runner runner = this.session.GetRunner();

            runner.AddInput(this.graph["input"][0], tensor).Fetch("boxes", "classes_prob", "classes_arg");

            TFTensor[] outputTensorArray = runner.Run();

            return outputTensorArray;
        }

        #endregion
    }
}

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using System;

using System.Drawing;

using System.Drawing.Imaging;

using System.IO;

using System.Windows.Forms;

using AForge.Video;

using AForge.Video.DirectShow;

using TensorFlow;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Field

////////////////////////////////////////////////////////////////////////////////////////// Private

#region Field

/// <summary>

/// 디스플레이 레이블 그래픽스

/// </summary>

private Graphics displayLabelGraphics = null;

/// <summary>

/// 필터 정보 컬렉션

/// </summary>

private FilterInfoCollection filterInfoCollection = null;

/// <summary>

/// 비디오 캡처 장치

/// </summary>

private VideoCaptureDevice videoCaptureDevice = null;

/// <summary>

/// 모델 배열

/// </summary>

private byte[] modelArray = null;

/// <summary>

/// 레이블 배열

/// </summary>

private string[] labelArray = null;

/// <summary>

/// 텐서플로우 그래프

/// </summary>

private TFGraph graph = null;

/// <summary>

/// 텐서플로우 세션

/// </summary>

private TFSession session = null;

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region MainForm

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

#region 이벤트를 설정한다.

Load += Form_Load;

FormClosing += Form_FormClosing;

this.startButton.Click += startButton_Click;

#endregion

}

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Method

////////////////////////////////////////////////////////////////////////////////////////// Private

//////////////////////////////////////////////////////////////////////////////// Event

#region 폼 로드시 처리하기 - Form_Load(sender, e)

/// <summary>

/// 폼 로드시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void Form_Load(object sender, EventArgs e)

{

this.displayLabelGraphics = this.displayLabel.CreateGraphics();

#region 카메라 장치 콤보 박스를 설정한다.

this.filterInfoCollection = new FilterInfoCollection(FilterCategory.VideoInputDevice);

for(int i = 0; i < this.filterInfoCollection.Count; i++)

{

this.cameraDeviceComboBox.Items.Add(this.filterInfoCollection[i].Name);

}

if(this.cameraDeviceComboBox.Items.Count > 0)

{

this.cameraDeviceComboBox.SelectedIndex = 0;

}

#endregion

#region 시작 버튼을 설정한다.

this.startButton.Enabled = (this.cameraDeviceComboBox.Items.Count > 0);

#endregion

#region 모델 배열을 설정한다.

this.modelArray = File.ReadAllBytes("DATA\\frozen_process_no_filter_tiny.pb");

#endregion

#region 레이블 배열을 설정한다.

this.labelArray = File.ReadAllLines("DATA\\yolo_labels.txt");

#endregion

#region 텐서플로우 그래프를 설정한다.

this.graph = new TFGraph();

this.graph.Import(this.modelArray, "");

#endregion

#region 텐서플로우 세션을 설정한다.

this.session = new TFSession(graph);

#endregion

Bitmap bitmap = new Bitmap(100, 100, PixelFormat.Format24bppRgb);

Predict(bitmap);

}

#endregion

#region 폼 닫을 경우 처리하기 - Form_FormClosing(sender, e)

/// <summary>

/// 폼 닫을 경우 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void Form_FormClosing(object sender, FormClosingEventArgs e)

{

StopCameraCaoture();

}

#endregion

#region 시작 버튼 클릭시 처리하기 - startButton_Click(sender, e)

/// <summary>

/// 시작 버튼 클릭시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void startButton_Click(object sender, EventArgs e)

{

if(this.startButton.Text == "시작")

{

this.startButton.Text = "중지";

StartCameraCapture();

}

else

{

StopCameraCaoture();

this.startButton.Text = "시작";

}

#endregion

#region 비디오 캡처 장치 신규 프레임 처리하기 - videoCaptureDevice_NewFrame(sender, e)

/// <summary>

/// 비디오 캡처 장치 신규 프레임 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void videoCaptureDevice_NewFrame(object sender, NewFrameEventArgs e)

{

Bitmap bitmap = e.Frame;

TFTensor[] outputTensorArray = Predict(bitmap);

float[,] rectangleArray = (float[,])outputTensorArray[0].GetValue();

float[] probabilityArray = (float[] )outputTensorArray[1].GetValue();

long[] labelIndexArray = (long[] )outputTensorArray[2].GetValue();

using(Graphics graphics = Graphics.FromImage(bitmap))

{

for(int i = 0; i < probabilityArray.Length; i++)

{

if(probabilityArray[i] > 0.2)

{

int rectangleLeft = (int)(rectangleArray[i, 0] * (float)bitmap.Width );

int rectangleTop = (int)(rectangleArray[i, 1] * (float)bitmap.Height);

int rectangleWidth = (int)(rectangleArray[i, 2] * (float)bitmap.Width );

int rectangleHeight = (int)(rectangleArray[i, 3] * (float)bitmap.Height);

graphics.DrawRectangle

(

new Pen(Color.Red, 2),

rectangleLeft - rectangleWidth / 2,

rectangleTop - rectangleHeight / 2,

rectangleWidth,

rectangleHeight

);

string label = this.labelArray[labelIndexArray[i]] + " " + probabilityArray[i].ToString();

graphics.DrawString

(

label,

Font,

Brushes.Red,

rectangleLeft - rectangleWidth / 2,

rectangleTop - rectangleHeight / 2

);

}

this.displayLabelGraphics.DrawImage(bitmap, 0, 0, this.displayLabel.Width, this.displayLabel.Height);

}

#endregion

//////////////////////////////////////////////////////////////////////////////// Function

#region 카메라 캡처 시작하기 - StartCameraCapture()

/// <summary>

/// 카메라 캡처 시작하기

/// </summary>

private void StartCameraCapture()

{

if(this.videoCaptureDevice == null || !this.videoCaptureDevice.IsRunning)

{

FilterInfo filterInfo = this.filterInfoCollection[this.cameraDeviceComboBox.SelectedIndex];

this.videoCaptureDevice = new VideoCaptureDevice(filterInfo.MonikerString);

this.videoCaptureDevice.NewFrame += videoCaptureDevice_NewFrame;

this.videoCaptureDevice.Start();

}

#endregion

#region 카메라 캡처 중단하기 - StopCameraCaoture()

/// <summary>

/// 카메라 캡처 중단하기

/// </summary>

private void StopCameraCaoture()

{

if(this.videoCaptureDevice != null && this.videoCaptureDevice.IsRunning)

{

this.videoCaptureDevice.NewFrame -= videoCaptureDevice_NewFrame;

this.videoCaptureDevice.SignalToStop();

this.videoCaptureDevice.WaitForStop();

this.videoCaptureDevice = null;

}

#endregion

#region 텐서 구하기 - GetTensor(sourceArray)

/// <summary>

/// 텐서 구하기

/// </summary>

/// <param name="sourceArray">소스 배열</param>

/// <returns>텐서</returns>

private TFTensor GetTensor(byte[] sourceArray)

{

TFGraph graph = new TFGraph();

TFOutput input = graph.Placeholder(TFDataType.String);

TFOutput output = graph.Cast(graph.DecodeJpeg(contents : input, channels : 3), DstT : TFDataType.Float);

TFTensor tensor = TFTensor.CreateString(sourceArray);

using(TFSession session = new TFSession(graph))

{

TFTensor[] normalizedTensorArray = session.Run

(

inputs : new[] { input },

outputs : new[] { output },

inputValues : new[] { tensor }

);

return normalizedTensorArray[0];

}

#endregion

#region 예측하기 - Predict(bitmap)

/// <summary>

/// 예측하기

/// </summary>

/// <param name="bitmap">비트맵</param>

/// <returns>결과 텐서 배열</returns>

private TFTensor[] Predict(Bitmap bitmap)

{

MemoryStream memoryStream = new MemoryStream();

bitmap.Save(memoryStream, ImageFormat.Jpeg);

TFTensor tensor = GetTensor(memoryStream.GetBuffer());

TFSession.Runner runner = this.session.GetRunner();

runner.AddInput(this.graph["input"][0], tensor).Fetch("boxes", "classes_prob", "classes_arg");

TFTensor[] outputTensorArray = runner.Run();

return outputTensorArray;

}

#endregion

}

TestProject.zip

[C#/WINFORM] 텐서플로우를 사용해 물체 인식하기

■ 텐서플로우를 사용해 물체를 인식하는 방법을 보여준다. ▶ MainForm.cs


using System;
using System.Drawing;
using System.Drawing.Imaging;
using System.IO;
using System.Windows.Forms;

using AForge.Video.DirectShow;

using TensorFlow;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Field
        ////////////////////////////////////////////////////////////////////////////////////////// Private

        #region Field

        /// <summary>
        /// 타이머
        /// </summary>
        private Timer timer = null;

        /// <summary>
        /// 필터 정보 컬렉션
        /// </summary>
        private FilterInfoCollection filterInfoCollection = null;


        /// <summary>
        /// 모델 배열
        /// </summary>
        private byte[] modelArray;

        /// <summary>
        /// 레이블 배열
        /// </summary>
        private string[] labelArray = null;

        /// <summary>
        /// 텐서플로우 세션
        /// </summary>
        private TFSession session = null;

        /// <summary>
        /// 텐서플로우 그래프
        /// </summary>
        private TFGraph graph = null;

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            #region 타이머를 설정한다.

            this.timer = new Timer();

            this.timer.Interval = 1000;

            #endregion
            #region 이벤트를 설정한다.

            Load += Form_Load;
            FormClosing            += Form_FormClosing;
            this.startButton.Click += startButton_Click;
            this.timer.Tick        += timer_Tick;

            #endregion
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Method
        ////////////////////////////////////////////////////////////////////////////////////////// Private
        //////////////////////////////////////////////////////////////////////////////// Event

        #region 폼 로드시 처리하기 - Form_Load(sender, e)

        /// <summary>
        /// 폼 로드시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void Form_Load(object sender, EventArgs e)
        {
            #region 카메라 장치 콤보 박스를 설정한다.

            this.filterInfoCollection = new FilterInfoCollection(FilterCategory.VideoInputDevice);

            for(int i = 0; i < this.filterInfoCollection.Count; i++)
            {
                this.cameraDeviceComboBox.Items.Add(this.filterInfoCollection[i].Name);
            }

            if(this.cameraDeviceComboBox.Items.Count > 0)
            {
                this.cameraDeviceComboBox.SelectedIndex = 0;
            }

            #endregion
            #region 시작 버튼을 설정한다.

            this.startButton.Enabled = (this.cameraDeviceComboBox.Items.Count > 0);

            #endregion

            #region 모델 배열을 설정한다.

            this.modelArray = File.ReadAllBytes("DATA\\tensorflow_inception_graph.pb");

            #endregion
            #region 레이블 배열을 설정한다.

            this.labelArray = File.ReadAllLines("DATA\\imagenet_comp_graph_label_strings.txt");

            #endregion


            this.graph   = new TFGraph();
            this.session = new TFSession(graph);

            this.graph.Import(this.modelArray, "");
        }

        #endregion
        #region 폼 닫을 경우 처리하기 - Form_FormClosing(sender, e)

        /// <summary>
        /// 폼 닫을 경우 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void Form_FormClosing(object sender, FormClosingEventArgs e)
        {
            this.timer.Stop();

            StopCameraCaoture();
        }

        #endregion
        #region 시작 버튼 클릭시 처리하기 - startButton_Click(sender, e)

        /// <summary>
        /// 시작 버튼 클릭시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void startButton_Click(object sender, EventArgs e)
        {
            if(this.startButton.Text == "시작")
            {
                this.startButton.Text = "중지";

                StartCameraCapture();

                this.timer.Start();
            }
            else
            {
                this.timer.Stop();

                StopCameraCaoture();

                this.startButton.Text = "시작";
            }
        }

        #endregion
        #region 타이머 틱 처리하기 - timer_Tick(sender, e)

        /// <summary>
        /// 타이머 틱 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void timer_Tick(object sender, EventArgs e)
        {
            Bitmap bitmap = this.videoSourcePlayer.GetCurrentVideoFrame();

            if(bitmap == null)
            {
                return;
            }

            MemoryStream memoryStream = new MemoryStream();

            bitmap.Save(memoryStream, ImageFormat.Jpeg);

            TFTensor tensor = GetTensor(memoryStream.GetBuffer());

            TFSession.Runner runner = this.session.GetRunner();

            runner.AddInput(graph["input"][0], tensor).Fetch(graph["output"][0]);

            TFTensor[] outputTensorArray = runner.Run();

            TFTensor outputTensor = outputTensorArray[0];

            long[] shapeArray = outputTensor.Shape;

            if(outputTensor.NumDims != 2 || shapeArray[0] != 1)
            {
                string shapeString = string.Empty;

                foreach(long shape in shapeArray)
                {
                    shapeString += $"{shape} ";
                }

                shapeString = shapeString.Trim();

                Console.WriteLine($"에러 : [1 N] 차원 텐서의 생성을 기대했는데(여기서 N은 라벨의 개수), [{shapeString}] 차원 텐서를 생성했습니다.");

                Environment.Exit(1);
            }

            bool  jagged    = true;
            int   bestIndex = 0;
            float best      = 0;

            if(jagged)
            {
                float[] probabilityArray = ((float[][])outputTensor.GetValue(jagged : true))[0];

                for(int i = 0; i < probabilityArray.Length; i++)
                {
                    if(probabilityArray[i] > best)
                    {
                        bestIndex = i;

                        best = probabilityArray[i];
                    }
                }
            }
            else
            {
                float[,] valueArray = (float[,])outputTensor.GetValue(jagged : false);

                for(int i = 0; i < valueArray.GetLength(1); i++)
                {
                    if(valueArray[0, i] > best)
                    {
                        bestIndex = i;

                        best = valueArray[0, i];
                    }
                }
            }

            this.informationLabel.Text = $"판정 : [{bestIndex}] {best * 100.0}% {this.labelArray[bestIndex]}";

            Console.WriteLine($"판정 : [{bestIndex}] {best * 100.0}% {this.labelArray[bestIndex]}");
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////// Function

        #region 카메라 캡처 시작하기 - StartCameraCapture()

        /// <summary>
        /// 카메라 캡처 시작하기
        /// </summary>
        private void StartCameraCapture()
        {
            FilterInfo filterInfo;

            filterInfo = this.filterInfoCollection[this.cameraDeviceComboBox.SelectedIndex];

            VideoCaptureDevice videoCaptureDevice = new VideoCaptureDevice(filterInfo.MonikerString);

            this.videoSourcePlayer.VideoSource = videoCaptureDevice;

            this.videoSourcePlayer.AutoSizeControl = true;

            this.videoSourcePlayer.Start();
        }

        #endregion
        #region 카메라 캡처 중단하기 - StopCameraCaoture()

        /// <summary>
        /// 카메라 캡처 중단하기
        /// </summary>
        private void StopCameraCaoture()
        {
            this.videoSourcePlayer.SignalToStop();

            this.videoSourcePlayer.WaitForStop();
        }

        #endregion

        #region 값 설정하기 - SetValue(graph, input, output)

        /// <summary>
        /// 값 설정하기
        /// </summary>
        /// <param name="graph">그래프</param>
        /// <param name="input">입력</param>
        /// <param name="output">출력</param>
        private void SetValue(out TFGraph graph, out TFOutput input, out TFOutput output)
        {
            const int   IMAGE_WIDTH  = 224;
            const int   IMAGE_HEIGHT = 224;
            const float MEAN         = 117;
            const float SCALE        = 1;

            graph = new TFGraph();
            input = graph.Placeholder(TFDataType.String);

            output = graph.Div
            (
                x : graph.Sub
                (
                    x : graph.ResizeBilinear
                    (
                        images : graph.ExpandDims
                        (
                            input : graph.Cast
                            (
                                graph.DecodeJpeg(contents : input, channels : 3),
                                DstT : TFDataType.Float
                            ),
                            dim : graph.Const(0, "make_batch")
                        ),
                        size : graph.Const(new int[] { IMAGE_WIDTH, IMAGE_HEIGHT }, "size")),
                    y : graph.Const(MEAN, "mean")
                ),
                y : graph.Const(SCALE, "scale")
            );
        }

        #endregion
        #region 텐서 구하기 - GetTensor(sourceArray)

        /// <summary>
        /// 텐서 구하기
        /// </summary>
        /// <param name="sourceArray">소스 배열</param>
        /// <returns>텐서</returns>
        private TFTensor GetTensor(byte[] sourceArray)
        {
            TFTensor tensor = TFTensor.CreateString(sourceArray);
            TFGraph  graph;
            TFOutput input;
            TFOutput output;

            SetValue(out graph, out input, out output);

            using(TFSession session = new TFSession(graph))
            {
                TFTensor[] normalizedTensorArray = session.Run
                (
                    inputs      : new[] { input  },
                    inputValues : new[] { tensor },
                    outputs     : new[] { output }
                );

                return normalizedTensorArray[0];
            }
        }

        #endregion
    }
}

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using System;

using System.Drawing;

using System.Drawing.Imaging;

using System.IO;

using System.Windows.Forms;

using AForge.Video.DirectShow;

using TensorFlow;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Field

////////////////////////////////////////////////////////////////////////////////////////// Private

#region Field

/// <summary>

/// 타이머

/// </summary>

private Timer timer = null;

/// <summary>

/// 필터 정보 컬렉션

/// </summary>

private FilterInfoCollection filterInfoCollection = null;

/// <summary>

/// 모델 배열

/// </summary>

private byte[] modelArray;

/// <summary>

/// 레이블 배열

/// </summary>

private string[] labelArray = null;

/// <summary>

/// 텐서플로우 세션

/// </summary>

private TFSession session = null;

/// <summary>

/// 텐서플로우 그래프

/// </summary>

private TFGraph graph = null;

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

#region 타이머를 설정한다.

this.timer = new Timer();

this.timer.Interval = 1000;

#endregion

#region 이벤트를 설정한다.

Load += Form_Load;

FormClosing += Form_FormClosing;

this.startButton.Click += startButton_Click;

this.timer.Tick += timer_Tick;

#endregion

}

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Method

////////////////////////////////////////////////////////////////////////////////////////// Private

//////////////////////////////////////////////////////////////////////////////// Event

#region 폼 로드시 처리하기 - Form_Load(sender, e)

/// <summary>

/// 폼 로드시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void Form_Load(object sender, EventArgs e)

{

#region 카메라 장치 콤보 박스를 설정한다.

this.filterInfoCollection = new FilterInfoCollection(FilterCategory.VideoInputDevice);

for(int i = 0; i < this.filterInfoCollection.Count; i++)

{

this.cameraDeviceComboBox.Items.Add(this.filterInfoCollection[i].Name);

}

if(this.cameraDeviceComboBox.Items.Count > 0)

{

this.cameraDeviceComboBox.SelectedIndex = 0;

}

#endregion

#region 시작 버튼을 설정한다.

this.startButton.Enabled = (this.cameraDeviceComboBox.Items.Count > 0);

#endregion

#region 모델 배열을 설정한다.

this.modelArray = File.ReadAllBytes("DATA\\tensorflow_inception_graph.pb");

#endregion

#region 레이블 배열을 설정한다.

this.labelArray = File.ReadAllLines("DATA\\imagenet_comp_graph_label_strings.txt");

#endregion

this.graph = new TFGraph();

this.session = new TFSession(graph);

this.graph.Import(this.modelArray, "");

}

#endregion

#region 폼 닫을 경우 처리하기 - Form_FormClosing(sender, e)

/// <summary>

/// 폼 닫을 경우 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void Form_FormClosing(object sender, FormClosingEventArgs e)

{

this.timer.Stop();

StopCameraCaoture();

}

#endregion

#region 시작 버튼 클릭시 처리하기 - startButton_Click(sender, e)

/// <summary>

/// 시작 버튼 클릭시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void startButton_Click(object sender, EventArgs e)

{

if(this.startButton.Text == "시작")

{

this.startButton.Text = "중지";

StartCameraCapture();

this.timer.Start();

}

else

{

this.timer.Stop();

StopCameraCaoture();

this.startButton.Text = "시작";

}

#endregion

#region 타이머 틱 처리하기 - timer_Tick(sender, e)

/// <summary>

/// 타이머 틱 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void timer_Tick(object sender, EventArgs e)

{

Bitmap bitmap = this.videoSourcePlayer.GetCurrentVideoFrame();

if(bitmap == null)

{

return;

}

MemoryStream memoryStream = new MemoryStream();

bitmap.Save(memoryStream, ImageFormat.Jpeg);

TFTensor tensor = GetTensor(memoryStream.GetBuffer());

TFSession.Runner runner = this.session.GetRunner();

runner.AddInput(graph["input"][0], tensor).Fetch(graph["output"][0]);

TFTensor[] outputTensorArray = runner.Run();

TFTensor outputTensor = outputTensorArray[0];

long[] shapeArray = outputTensor.Shape;

if(outputTensor.NumDims != 2 || shapeArray[0] != 1)

{

string shapeString = string.Empty;

foreach(long shape in shapeArray)

{

shapeString += $"{shape} ";

}

shapeString = shapeString.Trim();

Console.WriteLine($"에러 : [1 N] 차원 텐서의 생성을 기대했는데(여기서 N은 라벨의 개수), [{shapeString}] 차원 텐서를 생성했습니다.");

Environment.Exit(1);

}

bool jagged = true;

int bestIndex = 0;

float best = 0;

if(jagged)

{

float[] probabilityArray = ((float[][])outputTensor.GetValue(jagged : true))[0];

for(int i = 0; i < probabilityArray.Length; i++)

{

if(probabilityArray[i] > best)

{

bestIndex = i;

best = probabilityArray[i];

}

else

{

float[,] valueArray = (float[,])outputTensor.GetValue(jagged : false);

for(int i = 0; i < valueArray.GetLength(1); i++)

{

if(valueArray[0, i] > best)

{

bestIndex = i;

best = valueArray[0, i];

}

this.informationLabel.Text = $"판정 : [{bestIndex}] {best * 100.0}% {this.labelArray[bestIndex]}";

Console.WriteLine($"판정 : [{bestIndex}] {best * 100.0}% {this.labelArray[bestIndex]}");

}

#endregion

//////////////////////////////////////////////////////////////////////////////// Function

#region 카메라 캡처 시작하기 - StartCameraCapture()

/// <summary>

/// 카메라 캡처 시작하기

/// </summary>

private void StartCameraCapture()

{

FilterInfo filterInfo;

filterInfo = this.filterInfoCollection[this.cameraDeviceComboBox.SelectedIndex];

VideoCaptureDevice videoCaptureDevice = new VideoCaptureDevice(filterInfo.MonikerString);

this.videoSourcePlayer.VideoSource = videoCaptureDevice;

this.videoSourcePlayer.AutoSizeControl = true;

this.videoSourcePlayer.Start();

}

#endregion

#region 카메라 캡처 중단하기 - StopCameraCaoture()

/// <summary>

/// 카메라 캡처 중단하기

/// </summary>

private void StopCameraCaoture()

{

this.videoSourcePlayer.SignalToStop();

this.videoSourcePlayer.WaitForStop();

}

#endregion

#region 값 설정하기 - SetValue(graph, input, output)

/// <summary>

/// 값 설정하기

/// </summary>

/// <param name="graph">그래프</param>

/// <param name="input">입력</param>

/// <param name="output">출력</param>

private void SetValue(out TFGraph graph, out TFOutput input, out TFOutput output)

{

const int IMAGE_WIDTH = 224;

const int IMAGE_HEIGHT = 224;

const float MEAN = 117;

const float SCALE = 1;

graph = new TFGraph();

input = graph.Placeholder(TFDataType.String);

output = graph.Div

(

x : graph.Sub

(

x : graph.ResizeBilinear

(

images : graph.ExpandDims

(

input : graph.Cast

(

graph.DecodeJpeg(contents : input, channels : 3),

DstT : TFDataType.Float

dim : graph.Const(0, "make_batch")

size : graph.Const(new int[] { IMAGE_WIDTH, IMAGE_HEIGHT }, "size")),

y : graph.Const(MEAN, "mean")

y : graph.Const(SCALE, "scale")

);

}

#endregion

#region 텐서 구하기 - GetTensor(sourceArray)

/// <summary>

/// 텐서 구하기

/// </summary>

/// <param name="sourceArray">소스 배열</param>

/// <returns>텐서</returns>

private TFTensor GetTensor(byte[] sourceArray)

{

TFTensor tensor = TFTensor.CreateString(sourceArray);

TFGraph graph;

TFOutput input;

TFOutput output;

SetValue(out graph, out input, out output);

using(TFSession session = new TFSession(graph))

{

TFTensor[] normalizedTensorArray = session.Run

(

inputs : new[] { input },

inputValues : new[] { tensor },

outputs : new[] { output }

);

return normalizedTensorArray[0];

}

#endregion

}

※ 닷넷 프레임워크 4.7.1 버전을 사용해야 한다. ※ 프로젝트 속성의 빌드 탭에서

[C#/WINFORM/EMGUCV] STOP 표지판 인식하기

■ STOP 표지판을 인식하는 방법을 보여준다. ▶ StopSignDetector.cs


using System;
using System.Collections.Generic;
using System.Drawing;

using Emgu.CV;
using Emgu.CV.CvEnum;
using Emgu.CV.Features2D;
using Emgu.CV.Structure;
using Emgu.Util;

namespace TestProject
{
    /// <summary>
    /// STOP 표지판 검출기
    /// </summary>
    public class StopSignDetector : DisposableObject
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Field
        ////////////////////////////////////////////////////////////////////////////////////////// Private

        #region Field

        /// <summary>
        /// 추적기
        /// </summary>
        private Features2DTracker<float> tracker;

        /// <summary>
        /// 검출기
        /// </summary>
        private SURFDetector detector;

        /// <summary>
        /// 팔각형 저장소
        /// </summary>
        private MemStorage octagonStorage;

        /// <summary>
        /// 팔각형 윤곽선
        /// </summary>
        private Contour<Point> octagonContour;

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - StopSignDetector(modelImage)

        /// <summary>
        /// 생성자
        /// </summary>
        /// <param name="modelImage">모델 이미지</param>
        public StopSignDetector(Image<Bgr, Byte> modelImage)
        {
            this.detector = new SURFDetector(500, false);

            using(Image<Gray, Byte> maskImage = GetRedPixelMaskImage(modelImage))
            {
                ImageFeature<float>[] imageFeatureArray = this.detector.DetectFeatures(maskImage, null);

                if(imageFeatureArray.Length == 0)
                {
                    throw new Exception("No image feature has been found in the stop sign model");
                }

                this.tracker = new Features2DTracker<float>(imageFeatureArray);
            }

            this.octagonStorage = new MemStorage();

            this.octagonContour = new Contour<Point>(this.octagonStorage);

            this.octagonContour.PushMulti
            (
                new Point[]
                {
                    new Point(1, 0),
                    new Point(2, 0),
                    new Point(3, 1),
                    new Point(3, 2),
                    new Point(2, 3),
                    new Point(1, 3),
                    new Point(0, 2),
                    new Point(0, 1)
                },
                BACK_OR_FRONT.FRONT
            );
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Method
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region STOP 표지판 검출하기 - DetectStopSign(sourceImage, imageList, rectangleList)

        /// <summary>
        /// STOP 표지판 검출하기
        /// </summary>
        /// <param name="sourceImage">소스 이미지</param>
        /// <param name="imageList">이미지 리스트</param>
        /// <param name="rectangleList">사각형 리스트</param>
        public void DetectStopSign(Image<Bgr, byte> sourceImage, List<Image<Gray, Byte>> imageList, List<Rectangle> rectangleList)
        {
            Image<Bgr, Byte> smoothImage = sourceImage.SmoothGaussian(5, 5, 1.5, 1.5);

            Image<Gray, Byte> maskImage = GetRedPixelMaskImage(smoothImage);

            maskImage._Dilate(1);

            maskImage._Erode(1);

            using(Image<Gray, Byte> cannyImage = maskImage.Canny(100, 50))
            {
                using(MemStorage storage = new MemStorage())
                {
                    Contour<Point> pointContour = cannyImage.FindContours
                    (
                        CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE,
                        RETR_TYPE.CV_RETR_TREE,
                        storage
                    );

                    FindStopSign(sourceImage, imageList, rectangleList, pointContour);
                }
            }
        }

        #endregion

        ////////////////////////////////////////////////////////////////////////////////////////// Protected

        #region 객체 리소스 해제하기 - DisposeObject()

        /// <summary>
        /// 객체 리소스 해제하기
        /// </summary>
        protected override void DisposeObject()
        {
            this.tracker.Dispose();

            this.octagonStorage.Dispose();
        }

        #endregion

        ////////////////////////////////////////////////////////////////////////////////////////// Private

        #region 빨간색 픽셀 마스크 이미지 구하기 - GetRedPixelMaskImage(sourceImage)

        /// <summary>
        /// 빨간색 픽셀 마스크 이미지 구하기
        /// </summary>
        /// <param name="sourceImage">소스 이미지</param>
        /// <returns>빨간색 픽셀 마스크 이미지</returns>
        private Image<Gray, Byte> GetRedPixelMaskImage(Image<Bgr, byte> sourceImage)
        {
            using(Image<Hsv, Byte> hsvImage = sourceImage.Convert<Hsv, Byte>())
            {
                Image<Gray, Byte>[] channelImageArray = hsvImage.Split();

                try
                {
                    CvInvoke.cvInRangeS
                    (
                        channelImageArray[0],
                        new MCvScalar(20),
                        new MCvScalar(160),
                        channelImageArray[0]
                    );

                    channelImageArray[0]._Not();

                    channelImageArray[1]._ThresholdBinary(new Gray(10), new Gray(255.0));

                    CvInvoke.cvAnd(channelImageArray[0], channelImageArray[1], channelImageArray[0], IntPtr.Zero);
                }
                finally
                {
                    channelImageArray[1].Dispose();
                    channelImageArray[2].Dispose();
                }

                return channelImageArray[0];
            }
        }

        #endregion
        #region STOP 표지판 찾기 - FindStopSign(sourceImage, imageList, rectangleList, pointContour)

        /// <summary>
        /// STOP 표지판 찾기
        /// </summary>
        /// <param name="sourceImage">소스 이미지</param>
        /// <param name="imageList">이미지 리스트</param>
        /// <param name="rectangleList">사각형 리스트</param>
        /// <param name="pointContour">포인트 윤곽선</param>
        private void FindStopSign(Image<Bgr, byte> sourceImage, List<Image<Gray, Byte>> imageList, List<Rectangle> rectangleList, Contour<Point> pointContour)
        {
            for(; pointContour != null; pointContour = pointContour.HNext)
            {
                pointContour.ApproxPoly(pointContour.Perimeter * 0.02, 0, pointContour.Storage);

                if(pointContour.Area > 200)
                {
                    double ratio = CvInvoke.cvMatchShapes
                    (
                        this.octagonContour,
                        pointContour,
                        CONTOURS_MATCH_TYPE.CV_CONTOURS_MATCH_I3,
                        0
                    );

                    if(ratio > 0.1)
                    {
                        Contour<Point> childPointContour = pointContour.VNext;

                        if(childPointContour != null)
                        {
                            FindStopSign(sourceImage, imageList, rectangleList, childPointContour);
                        }

                        continue;
                    }

                    Rectangle rectangle = pointContour.BoundingRectangle;

                    Image<Gray, Byte> candidateImage;

                    using(Image<Bgr, Byte> temporaryImage = sourceImage.Copy(rectangle))
                    {
                        candidateImage = temporaryImage.Convert<Gray, byte>();
                    }

                    using(Image<Gray, Byte> maskImage = new Image<Gray, byte>(rectangle.Size))
                    {
                        maskImage.Draw
                        (
                            pointContour,
                            new Gray(255),
                            new Gray(255),
                            0,
                            -1,
                            new Point(-rectangle.X, -rectangle.Y)
                        );

                        double mean = CvInvoke.cvAvg(candidateImage, maskImage).v0;

                        candidateImage._ThresholdBinary(new Gray(mean), new Gray(255.0));

                        candidateImage._Not();

                        maskImage._Not();

                        candidateImage.SetValue(0, maskImage);
                    }

                    ImageFeature<float>[] imageFeatureArray = this.detector.DetectFeatures(candidateImage, null);

                    int minimumMatchCount = 10;

                    if(imageFeatureArray != null && imageFeatureArray.Length >= minimumMatchCount)
                    {
                        Features2DTracker<float>.MatchedImageFeature[] matchedImageFeatureArray = this.tracker.MatchFeature(imageFeatureArray, 2);

                        int goodMatchCount = 0;

                        foreach(Features2DTracker<float>.MatchedImageFeature matchedImageFeature in matchedImageFeatureArray)
                        {
                            if(matchedImageFeature.SimilarFeatures[0].Distance < 0.5)
                            {
                                goodMatchCount++;
                            }
                        }

                        if(goodMatchCount >= minimumMatchCount)
                        {
                            rectangleList.Add(rectangle);

                            imageList.Add(candidateImage);
                        }
                    }
                }
            }
        }

        #endregion
    }
}

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using System;

using System.Collections.Generic;

using System.Drawing;

using Emgu.CV;

using Emgu.CV.CvEnum;

using Emgu.CV.Features2D;

using Emgu.CV.Structure;

using Emgu.Util;

namespace TestProject

{

/// <summary>

/// STOP 표지판 검출기

/// </summary>

public class StopSignDetector : DisposableObject

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Field

////////////////////////////////////////////////////////////////////////////////////////// Private

#region Field

/// <summary>

/// 추적기

/// </summary>

private Features2DTracker<float> tracker;

/// <summary>

/// 검출기

/// </summary>

private SURFDetector detector;

/// <summary>

/// 팔각형 저장소

/// </summary>

private MemStorage octagonStorage;

/// <summary>

/// 팔각형 윤곽선

/// </summary>

private Contour<Point> octagonContour;

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - StopSignDetector(modelImage)

/// <summary>

/// 생성자

/// </summary>

/// <param name="modelImage">모델 이미지</param>

public StopSignDetector(Image<Bgr, Byte> modelImage)

{

this.detector = new SURFDetector(500, false);

using(Image<Gray, Byte> maskImage = GetRedPixelMaskImage(modelImage))

{

ImageFeature<float>[] imageFeatureArray = this.detector.DetectFeatures(maskImage, null);

if(imageFeatureArray.Length == 0)

{

throw new Exception("No image feature has been found in the stop sign model");

}

this.tracker = new Features2DTracker<float>(imageFeatureArray);

}

this.octagonStorage = new MemStorage();

this.octagonContour = new Contour<Point>(this.octagonStorage);

this.octagonContour.PushMulti

(

new Point[]

{

new Point(1, 0),

new Point(2, 0),

new Point(3, 1),

new Point(3, 2),

new Point(2, 3),

new Point(1, 3),

new Point(0, 2),

new Point(0, 1)

BACK_OR_FRONT.FRONT

);

}

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Method

////////////////////////////////////////////////////////////////////////////////////////// Public

#region STOP 표지판 검출하기 - DetectStopSign(sourceImage, imageList, rectangleList)

/// <summary>

/// STOP 표지판 검출하기

/// </summary>

/// <param name="sourceImage">소스 이미지</param>

/// <param name="imageList">이미지 리스트</param>

/// <param name="rectangleList">사각형 리스트</param>

public void DetectStopSign(Image<Bgr, byte> sourceImage, List<Image<Gray, Byte>> imageList, List<Rectangle> rectangleList)

{

Image<Bgr, Byte> smoothImage = sourceImage.SmoothGaussian(5, 5, 1.5, 1.5);

Image<Gray, Byte> maskImage = GetRedPixelMaskImage(smoothImage);

maskImage._Dilate(1);

maskImage._Erode(1);

using(Image<Gray, Byte> cannyImage = maskImage.Canny(100, 50))

{

using(MemStorage storage = new MemStorage())

{

Contour<Point> pointContour = cannyImage.FindContours

(

CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE,

RETR_TYPE.CV_RETR_TREE,

storage

);

FindStopSign(sourceImage, imageList, rectangleList, pointContour);

}

#endregion

////////////////////////////////////////////////////////////////////////////////////////// Protected

#region 객체 리소스 해제하기 - DisposeObject()

/// <summary>

/// 객체 리소스 해제하기

/// </summary>

protected override void DisposeObject()

{

this.tracker.Dispose();

this.octagonStorage.Dispose();

}

#endregion

////////////////////////////////////////////////////////////////////////////////////////// Private

#region 빨간색 픽셀 마스크 이미지 구하기 - GetRedPixelMaskImage(sourceImage)

/// <summary>

/// 빨간색 픽셀 마스크 이미지 구하기

/// </summary>

/// <param name="sourceImage">소스 이미지</param>

/// <returns>빨간색 픽셀 마스크 이미지</returns>

private Image<Gray, Byte> GetRedPixelMaskImage(Image<Bgr, byte> sourceImage)

{

using(Image<Hsv, Byte> hsvImage = sourceImage.Convert<Hsv, Byte>())

{

Image<Gray, Byte>[] channelImageArray = hsvImage.Split();

try

{

CvInvoke.cvInRangeS

(

channelImageArray[0],

new MCvScalar(20),

new MCvScalar(160),

channelImageArray[0]

);

channelImageArray[0]._Not();

channelImageArray[1]._ThresholdBinary(new Gray(10), new Gray(255.0));

CvInvoke.cvAnd(channelImageArray[0], channelImageArray[1], channelImageArray[0], IntPtr.Zero);

}

finally

{

channelImageArray[1].Dispose();

channelImageArray[2].Dispose();

}

return channelImageArray[0];

}

#endregion

#region STOP 표지판 찾기 - FindStopSign(sourceImage, imageList, rectangleList, pointContour)

/// <summary>

/// STOP 표지판 찾기

/// </summary>

/// <param name="sourceImage">소스 이미지</param>

/// <param name="imageList">이미지 리스트</param>

/// <param name="rectangleList">사각형 리스트</param>

/// <param name="pointContour">포인트 윤곽선</param>

private void FindStopSign(Image<Bgr, byte> sourceImage, List<Image<Gray, Byte>> imageList, List<Rectangle> rectangleList, Contour<Point> pointContour)

{

for(; pointContour != null; pointContour = pointContour.HNext)

{

pointContour.ApproxPoly(pointContour.Perimeter * 0.02, 0, pointContour.Storage);

if(pointContour.Area > 200)

{

double ratio = CvInvoke.cvMatchShapes

(

this.octagonContour,

pointContour,

CONTOURS_MATCH_TYPE.CV_CONTOURS_MATCH_I3,

);

if(ratio > 0.1)

{

Contour<Point> childPointContour = pointContour.VNext;

if(childPointContour != null)

{

FindStopSign(sourceImage, imageList, rectangleList, childPointContour);

}

continue;

}

Rectangle rectangle = pointContour.BoundingRectangle;

Image<Gray, Byte> candidateImage;

using(Image<Bgr, Byte> temporaryImage = sourceImage.Copy(rectangle))

{

candidateImage = temporaryImage.Convert<Gray, byte>();

}

using(Image<Gray, Byte> maskImage = new Image<Gray, byte>(rectangle.Size))

{

maskImage.Draw

(

pointContour,

new Gray(255),

-1,

new Point(-rectangle.X, -rectangle.Y)

);

double mean = CvInvoke.cvAvg(candidateImage, maskImage).v0;

candidateImage._ThresholdBinary(new Gray(mean), new Gray(255.0));

candidateImage._Not();

maskImage._Not();

candidateImage.SetValue(0, maskImage);

}

ImageFeature<float>[] imageFeatureArray = this.detector.DetectFeatures(candidateImage, null);

int minimumMatchCount = 10;

if(imageFeatureArray != null && imageFeatureArray.Length >= minimumMatchCount)

{

Features2DTracker<float>.MatchedImageFeature[] matchedImageFeatureArray = this.tracker.MatchFeature(imageFeatureArray, 2);

int goodMatchCount = 0;

foreach(Features2DTracker<float>.MatchedImageFeature matchedImageFeature in matchedImageFeatureArray)

{

if(matchedImageFeature.SimilarFeatures[0].Distance < 0.5)

{

goodMatchCount++;

}

if(goodMatchCount >= minimumMatchCount)

{

rectangleList.Add(rectangle);

imageList.Add(candidateImage);

}

#endregion

}

▶ MainForm.cs


using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Drawing;
using System.Windows.Forms;

using Emgu.CV;
using Emgu.CV.Structure;
using Emgu.CV.UI;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Field
        ////////////////////////////////////////////////////////////////////////////////////////// Private

        #region Field

        /// <summary>
        /// 검출기
        /// </summary>
        private StopSignDetector detector;

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            using(Image<Bgr, Byte> modelImage = new Image<Bgr, Byte>("stop-sign-model.png"))
            {
                using (Image<Bgr, Byte> image = new Image<Bgr, byte>("stop-sign.jpg"))
                {
                    this.detector = new StopSignDetector(modelImage);

                    ProcessImage(image);
                }
            }
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Method
        ////////////////////////////////////////////////////////////////////////////////////////// Private
        //////////////////////////////////////////////////////////////////////////////// Event

        #region 이미지 로드 버튼 클릭시 처리하기 - loadImageButton_Click(sender, e)

        /// <summary>
        /// 이미지 로드 버튼 클릭시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void loadImageButton_Click(object sender, EventArgs e)
        {
            DialogResult result = openFileDialog.ShowDialog();

            if(result == DialogResult.OK)
            {
                Image<Bgr, Byte> image;

                try
                {
                    image = new Image<Bgr, byte>(openFileDialog.FileName);
                }
                catch
                {
                    MessageBox.Show("지원하는 파일 포맷이 아닙니다.");

                    return;
                }

                ProcessImage(image);
            }
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////// Function

        #region 레이블 및 이미지 추가하기 - AddLabelAndImage(startPoint, text, image)

        /// <summary>
        /// 레이블 및 이미지 추가하기
        /// </summary>
        /// <param name="startPoint">시작 위치</param>
        /// <param name="text">텍스트</param>
        /// <param name="image">이미지</param>
        private void AddLabelAndImage(ref Point startPoint, string text, IImage image)
        {
            Label label = new Label();

            this.resultPanel.Controls.Add(label);

            label.Width    = 100;
            label.Height   = 30;
            label.Location = startPoint;
            label.Text     = text;

            startPoint.Y += label.Height;

            ImageBox imageBox = new ImageBox();

            this.resultPanel.Controls.Add(imageBox);

            imageBox.ClientSize = image.Size;
            imageBox.Location   = startPoint;
            imageBox.Image      = image;

            startPoint.Y += imageBox.Height + 10;
        }

        #endregion
        #region 이미지 처리하기 - ProcessImage(image)

        /// <summary>
        /// 이미지 처리하기
        /// </summary>
        /// <param name="image">이미지</param>
        private void ProcessImage(Image<Bgr, byte> image)
        {
            Stopwatch stopwatch = Stopwatch.StartNew();

            List<Image<Gray, Byte>> imageList     = new List<Image<Gray, byte>>();
            List<Rectangle>         rectangleList = new List<Rectangle>();

            this.detector.DetectStopSign(image, imageList, rectangleList);

            stopwatch.Stop();

            this.messageLabel.Text = String.Format("STOP 표지판 검출 시간 : {0} 밀리초", stopwatch.Elapsed.TotalMilliseconds);

            this.resultPanel.Controls.Clear();

            Point startPoint = new Point(10, 10);

            for(int i = 0; i < imageList.Count; i++)
            {
                Rectangle rectangle = rectangleList[i];

                AddLabelAndImage
                (
                    ref startPoint,
                    string.Format
                    (
                        "STOP 표지판 [{0}, {1}]",
                        rectangle.Location.Y + rectangle.Width  / 2,
                        rectangle.Location.Y + rectangle.Height / 2
                    ),
                    imageList[i]
                );

                image.Draw(rectangle, new Bgr(Color.Aquamarine), 2);
            }

            this.imageBox.Image = image;
        }

        #endregion
    }
}

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using System;

using System.Collections.Generic;

using System.Diagnostics;

using System.Drawing;

using System.Windows.Forms;

using Emgu.CV;

using Emgu.CV.Structure;

using Emgu.CV.UI;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Field

////////////////////////////////////////////////////////////////////////////////////////// Private

#region Field

/// <summary>

/// 검출기

/// </summary>

private StopSignDetector detector;

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

using(Image<Bgr, Byte> modelImage = new Image<Bgr, Byte>("stop-sign-model.png"))

{

using (Image<Bgr, Byte> image = new Image<Bgr, byte>("stop-sign.jpg"))

{

this.detector = new StopSignDetector(modelImage);

ProcessImage(image);

}

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Method

////////////////////////////////////////////////////////////////////////////////////////// Private

//////////////////////////////////////////////////////////////////////////////// Event

#region 이미지 로드 버튼 클릭시 처리하기 - loadImageButton_Click(sender, e)

/// <summary>

/// 이미지 로드 버튼 클릭시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void loadImageButton_Click(object sender, EventArgs e)

{

DialogResult result = openFileDialog.ShowDialog();

if(result == DialogResult.OK)

{

Image<Bgr, Byte> image;

try

{

image = new Image<Bgr, byte>(openFileDialog.FileName);

}

catch

{

MessageBox.Show("지원하는 파일 포맷이 아닙니다.");

return;

}

ProcessImage(image);

}

#endregion

//////////////////////////////////////////////////////////////////////////////// Function

#region 레이블 및 이미지 추가하기 - AddLabelAndImage(startPoint, text, image)

/// <summary>

/// 레이블 및 이미지 추가하기

/// </summary>

/// <param name="startPoint">시작 위치</param>

/// <param name="text">텍스트</param>

/// <param name="image">이미지</param>

private void AddLabelAndImage(ref Point startPoint, string text, IImage image)

{

Label label = new Label();

this.resultPanel.Controls.Add(label);

label.Width = 100;

label.Height = 30;

label.Location = startPoint;

label.Text = text;

startPoint.Y += label.Height;

ImageBox imageBox = new ImageBox();

this.resultPanel.Controls.Add(imageBox);

imageBox.ClientSize = image.Size;

imageBox.Location = startPoint;

imageBox.Image = image;

startPoint.Y += imageBox.Height + 10;

}

#endregion

#region 이미지 처리하기 - ProcessImage(image)

/// <summary>

/// 이미지 처리하기

/// </summary>

/// <param name="image">이미지</param>

private void ProcessImage(Image<Bgr, byte> image)

{

Stopwatch stopwatch = Stopwatch.StartNew();

List<Image<Gray, Byte>> imageList = new List<Image<Gray, byte>>();

List<Rectangle> rectangleList = new List<Rectangle>();

this.detector.DetectStopSign(image, imageList, rectangleList);

stopwatch.Stop();

this.messageLabel.Text = String.Format("STOP 표지판 검출 시간 : {0} 밀리초", stopwatch.Elapsed.TotalMilliseconds);

this.resultPanel.Controls.Clear();

Point startPoint = new Point(10, 10);

for(int i = 0; i < imageList.Count; i++)

{

Rectangle rectangle = rectangleList[i];

AddLabelAndImage

(

ref startPoint,

string.Format

(

"STOP 표지판 [{0}, {1}]",

rectangle.Location.Y + rectangle.Width / 2,

rectangle.Location.Y + rectangle.Height / 2

imageList[i]

);

image.Draw(rectangle, new Bgr(Color.Aquamarine), 2);

}

this.imageBox.Image = image;

}

#endregion

}

TestProject.zip

[C#/WINFORM/EMGUCV] 자동차 번호판 인식하기

■ 자동차 번호판을 인식하는 방법을 보여준다. ▶ LicensePlateDetector.cs


using System;
using System.Collections.Generic;
using System.Drawing;
using System.Text;

using Emgu.CV;
using Emgu.CV.CvEnum;
using Emgu.CV.OCR;
using Emgu.CV.Structure;
using Emgu.Util;

namespace TestProject
{
    /// <summary>
    /// 자동차 번호판 검출기
    /// </summary>
    public class LicensePlateDetector : DisposableObject
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Field
        ////////////////////////////////////////////////////////////////////////////////////////// Private

        #region Field

        /// <summary>
        /// OCR
        /// </summary>
        private Tesseract ocr;

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - LicensePlateDetector(dataPath)

        /// <summary>
        /// 생성자
        /// </summary>
        /// <param name="dataPath">데이터 경로</param>
        public LicensePlateDetector(string dataPath)
        {
            this.ocr = new Tesseract(dataPath, "eng", Tesseract.OcrEngineMode.OEM_TESSERACT_CUBE_COMBINED);

            this.ocr.SetVariable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ-1234567890");
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Method
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 자동차 번호판 검출하기 - DetectLicensePlate(sourceImage, licensePlateImageList, filteredLicensePlateImageList, detectedLicensePlateRectangleList)

        /// <summary>
        /// 자동차 번호판 검출하기
        /// </summary>
        /// <param name="sourceImage">소스 이미지</param>
        /// <param name="licensePlateImageList">자동차 번호판 이미지 리스트</param>
        /// <param name="filteredLicensePlateImageList">필터 자동차 번호판 이미지 리스트</param>
        /// <param name="detectedLicensePlateRectangleList">검출 자동차 번호판 사각형 리스트</param>
        /// <returns>자동차 번호 리스트</returns>
        public List<string> DetectLicensePlate
        (
            Image<Bgr, byte> sourceImage,
            List<Image<Gray, Byte>> licensePlateImageList,
            List<Image<Gray, Byte>> filteredLicensePlateImageList,
            List<MCvBox2D> detectedLicensePlateRectangleList)
        {
            List<string> licenseList = new List<String>();

            using(Image<Gray, byte> grayscaleImage = sourceImage.Convert<Gray, Byte>())
            {
                using(Image<Gray, Byte> cannyImage = new Image<Gray, byte>(grayscaleImage.Size))
                {
                    using(MemStorage storage = new MemStorage())
                    {
                        CvInvoke.cvCanny(grayscaleImage, cannyImage, 100, 50, 3);

                        Contour<Point> pointContour = cannyImage.FindContours
                        (
                            CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE,
                            RETR_TYPE.CV_RETR_TREE,
                            storage
                        );

                        FindLicensePlate
                        (
                            pointContour,
                            grayscaleImage,
                            cannyImage,
                            licensePlateImageList,
                            filteredLicensePlateImageList,
                            detectedLicensePlateRectangleList,
                            licenseList
                        );
                    }
                }
            }

            return licenseList;
        }

        #endregion

        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 흰색 픽셀 마스크 구하기 - GetWhitePixelMask(image)

        /// <summary>
        /// 흰색 픽셀 마스크 구하기
        /// </summary>
        /// <param name="image">이미지</param>
        /// <returns>흰색 픽셀 마스크</returns>
        /// <remarks>
        /// 흰색 픽셀은 채도가 40보다 작거나 200보다 큰 경우에 해당한다.
        /// </remarks>
        private static Image<Gray, Byte> GetWhitePixelMask(Image<Bgr, byte> image)
        {
            using(Image<Hsv, Byte> hsvImage = image.Convert<Hsv, Byte>())
            {
                Image<Gray, Byte>[] grayscaleImageArray = hsvImage.Split();

                try
                {
                    grayscaleImageArray[1]._ThresholdBinaryInv(new Gray(40), new Gray(255));

                    grayscaleImageArray[2]._ThresholdBinary(new Gray(200), new Gray(255));

                    CvInvoke.cvAnd(grayscaleImageArray[1], grayscaleImageArray[2], grayscaleImageArray[0], IntPtr.Zero);
                }
                finally
                {
                    grayscaleImageArray[1].Dispose();
                    grayscaleImageArray[2].Dispose();
                }

                return grayscaleImageArray[0];
            }
        }

        #endregion
        #region 자식 카운트 구하기 - GetChildCount(contour)

        /// <summary>
        /// 자식 카운트 구하기
        /// </summary>
        /// <param name="contour">윤곽</param>
        /// <returns>자식 카운트</returns>
        private static int GetChildCount(Contour<Point> contour)
        {
            Contour<Point> childContour = contour.VNext;

            if(childContour == null)
            {
                return 0;
            }

            int count = 0;

            while(childContour != null)
            {
                count++;

                childContour = childContour.HNext;
            }

            return count;
        }

        #endregion
        #region 자동차 번호판 찾기 - FindLicensePlate(pointContour, grayscaleImage, cannyImage, licensePlateImageList, filteredLicensePlateImageList,
            detectedLicensePlateRectangleList, licenseList)

        /// <summary>
        /// 자동차 번호판 찾기
        /// </summary>
        /// <param name="pointContour">포인트 윤곽</param>
        /// <param name="grayscaleImage">회색조 이미지</param>
        /// <param name="cannyImage">캐니 이미지</param>
        /// <param name="licensePlateImageList">자동차 번호판 이미지 리스트</param>
        /// <param name="filteredLicensePlateImageList">필터 자동차 번호판 이미지 리스트</param>
        /// <param name="detectedLicensePlateRectangleList">검출 자동차 번호판 사각형 리스트</param>
        /// <param name="licenseList">자동차 번호 리스트</param>
        private void FindLicensePlate
        (
            Contour<Point> pointContour,
            Image<Gray, Byte> grayscaleImage,
            Image<Gray, Byte> cannyImage,
            List<Image<Gray, Byte>> licensePlateImageList,
            List<Image<Gray, Byte>> filteredLicensePlateImageList,
            List<MCvBox2D> detectedLicensePlateRectangleList,
            List<String> licenseList
        )
        {
            for(; pointContour != null; pointContour = pointContour.HNext)
            {
                int childCount = GetChildCount(pointContour);

                if(childCount == 0)
                {
                    continue;
                }

                if(pointContour.Area > 400)
                {
                    if(childCount < 3)
                    {
                        // 윤곽선에 자식 윤곽선이 3개 보다 작은 경우는 자동차 번호판이 아니디.
                        // (자동차 번호판에 문자가 3자 이상 있다고 가정한다)
                        // 그러나 윤곽선의 자식 윤곽선을 검색해 그 중 하나가 자동차 번호판인지 확인해야 한다.
                        FindLicensePlate
                        (
                            pointContour.VNext,
                            grayscaleImage,
                            cannyImage,
                            licensePlateImageList,
                            filteredLicensePlateImageList,
                            detectedLicensePlateRectangleList,
                            licenseList
                        );

                        continue;
                    }

                    MCvBox2D rectangle = pointContour.GetMinAreaRect();

                    if(rectangle.angle < -45.0)
                    {
                        float temporaryWidth = rectangle.size.Width;

                        rectangle.size.Width  = rectangle.size.Height;
                        rectangle.size.Height = temporaryWidth;

                        rectangle.angle += 90.0f;
                    }
                    else if(rectangle.angle > 45.0)
                    {
                        float temporaryWidth = rectangle.size.Width;

                        rectangle.size.Width  = rectangle.size.Height;
                        rectangle.size.Height = temporaryWidth;

                        rectangle.angle -= 90.0f;
                    }

                    double ratio = (double)rectangle.size.Width / rectangle.size.Height;

                    if(!(3.0 < ratio && ratio < 10.0))
                    {
                        Contour<Point> childContour = pointContour.VNext;

                        if(childContour != null)
                        {
                            FindLicensePlate
                            (
                                childContour,
                                grayscaleImage,
                                cannyImage,
                                licensePlateImageList,
                                filteredLicensePlateImageList,
                                detectedLicensePlateRectangleList,
                                licenseList
                            );
                        }

                        continue;
                    }

                    using(Image<Gray, Byte> temporaryImage1 = grayscaleImage.Copy(rectangle))
                    {
                        using(Image<Gray, Byte> temporaryImage2 = temporaryImage1.Resize(240, 180, INTER.CV_INTER_CUBIC, true))
                        {
                            int edgePixelSize = 2;

                            temporaryImage2.ROI = new Rectangle
                            (
                                new Point(edgePixelSize, edgePixelSize),
                                temporaryImage2.Size - new Size(2 * edgePixelSize, 2 * edgePixelSize)
                            );

                            Image<Gray, Byte> plateImage = temporaryImage2.Copy();

                            Image<Gray, Byte> filteredPlateImage = FilterLicensePlateImage(plateImage);

                            Tesseract.Charactor[] charactorArray;

                            StringBuilder stringBuilder = new StringBuilder();

                            using(Image<Gray, Byte> temporaryImage3 = filteredPlateImage.Clone())
                            {
                                this.ocr.Recognize(temporaryImage3);

                                charactorArray = this.ocr.GetCharactors();

                                if(charactorArray.Length == 0)
                                {
                                    continue;
                                }

                                for(int i = 0; i < charactorArray.Length; i++)
                                {
                                    stringBuilder.Append(charactorArray[i].Text);
                                }
                            }

                            licenseList.Add(stringBuilder.ToString());

                            licensePlateImageList.Add(plateImage);

                            filteredLicensePlateImageList.Add(filteredPlateImage);

                            detectedLicensePlateRectangleList.Add(rectangle);
                        }
                    }
                }
            }
        }

        #endregion
        #region 자동차 번호판 이미지 필터하기 - FilterLicensePlateImage(sourceImage)

        /// <summary>
        /// 자동차 번호판 이미지 필터하기
        /// </summary>
        /// <param name="sourceImage">소스 이미지</param>
        /// <returns>필터 이미지</returns>
        private static Image<Gray, Byte> FilterLicensePlateImage(Image<Gray, Byte> sourceImage)
        {
            Image<Gray, Byte> threshImage = sourceImage.ThresholdBinaryInv(new Gray(120), new Gray(255));

            using(Image<Gray, Byte> maskImage = new Image<Gray, byte>(sourceImage.Size))
            {
                using(Image<Gray, Byte> cannyImage = sourceImage.Canny(100, 50))
                {
                    using(MemStorage storage = new MemStorage())
                    {
                        maskImage.SetValue(255.0);

                        for(Contour<Point> pointContour = cannyImage.FindContours(CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE, RETR_TYPE.CV_RETR_EXTERNAL, storage);
                            pointContour != null; pointContour = pointContour.HNext)
                        {
                            Rectangle rectangle = pointContour.BoundingRectangle;

                            if(rectangle.Height > (sourceImage.Height >> 1))
                            {
                                rectangle.X -= 1;
                                rectangle.Y -= 1;

                                rectangle.Width  += 2;
                                rectangle.Height += 2;

                                rectangle.Intersect(sourceImage.ROI);

                                maskImage.Draw(rectangle, new Gray(0.0), -1);
                            }
                        }

                        threshImage.SetValue(0, maskImage);
                    }
                }
            }

            threshImage._Erode(1);
            threshImage._Dilate(1);

            return threshImage;
        }

        #endregion
        #region 객체 리소스 해제하기 - DisposeObject()

        /// <summary>
        /// 객체 리소스 해제하기
        /// </summary>
        protected override void DisposeObject()
        {
            this.ocr.Dispose();
        }

        #endregion
    }
}

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using System;

using System.Collections.Generic;

using System.Drawing;

using System.Text;

using Emgu.CV;

using Emgu.CV.CvEnum;

using Emgu.CV.OCR;

using Emgu.CV.Structure;

using Emgu.Util;

namespace TestProject

{

/// <summary>

/// 자동차 번호판 검출기

/// </summary>

public class LicensePlateDetector : DisposableObject

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Field

////////////////////////////////////////////////////////////////////////////////////////// Private

#region Field

/// <summary>

/// OCR

/// </summary>

private Tesseract ocr;

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - LicensePlateDetector(dataPath)

/// <summary>

/// 생성자

/// </summary>

/// <param name="dataPath">데이터 경로</param>

public LicensePlateDetector(string dataPath)

{

this.ocr = new Tesseract(dataPath, "eng", Tesseract.OcrEngineMode.OEM_TESSERACT_CUBE_COMBINED);

this.ocr.SetVariable("tessedit_char_whitelist", "ABCDEFGHIJKLMNOPQRSTUVWXYZ-1234567890");

}

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Method

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 자동차 번호판 검출하기 - DetectLicensePlate(sourceImage, licensePlateImageList, filteredLicensePlateImageList, detectedLicensePlateRectangleList)

/// <summary>

/// 자동차 번호판 검출하기

/// </summary>

/// <param name="sourceImage">소스 이미지</param>

/// <param name="licensePlateImageList">자동차 번호판 이미지 리스트</param>

/// <param name="filteredLicensePlateImageList">필터 자동차 번호판 이미지 리스트</param>

/// <param name="detectedLicensePlateRectangleList">검출 자동차 번호판 사각형 리스트</param>

/// <returns>자동차 번호 리스트</returns>

public List<string> DetectLicensePlate

(

Image<Bgr, byte> sourceImage,

List<Image<Gray, Byte>> licensePlateImageList,

List<Image<Gray, Byte>> filteredLicensePlateImageList,

List<MCvBox2D> detectedLicensePlateRectangleList)

{

List<string> licenseList = new List<String>();

using(Image<Gray, byte> grayscaleImage = sourceImage.Convert<Gray, Byte>())

{

using(Image<Gray, Byte> cannyImage = new Image<Gray, byte>(grayscaleImage.Size))

{

using(MemStorage storage = new MemStorage())

{

CvInvoke.cvCanny(grayscaleImage, cannyImage, 100, 50, 3);

Contour<Point> pointContour = cannyImage.FindContours

(

CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE,

RETR_TYPE.CV_RETR_TREE,

storage

);

FindLicensePlate

(

pointContour,

grayscaleImage,

cannyImage,

licensePlateImageList,

filteredLicensePlateImageList,

detectedLicensePlateRectangleList,

licenseList

);

}

return licenseList;

}

#endregion

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 흰색 픽셀 마스크 구하기 - GetWhitePixelMask(image)

/// <summary>

/// 흰색 픽셀 마스크 구하기

/// </summary>

/// <param name="image">이미지</param>

/// <returns>흰색 픽셀 마스크</returns>

/// <remarks>

/// 흰색 픽셀은 채도가 40보다 작거나 200보다 큰 경우에 해당한다.

/// </remarks>

private static Image<Gray, Byte> GetWhitePixelMask(Image<Bgr, byte> image)

{

using(Image<Hsv, Byte> hsvImage = image.Convert<Hsv, Byte>())

{

Image<Gray, Byte>[] grayscaleImageArray = hsvImage.Split();

try

{

grayscaleImageArray[1]._ThresholdBinaryInv(new Gray(40), new Gray(255));

grayscaleImageArray[2]._ThresholdBinary(new Gray(200), new Gray(255));

CvInvoke.cvAnd(grayscaleImageArray[1], grayscaleImageArray[2], grayscaleImageArray[0], IntPtr.Zero);

}

finally

{

grayscaleImageArray[1].Dispose();

grayscaleImageArray[2].Dispose();

}

return grayscaleImageArray[0];

}

#endregion

#region 자식 카운트 구하기 - GetChildCount(contour)

/// <summary>

/// 자식 카운트 구하기

/// </summary>

/// <param name="contour">윤곽</param>

/// <returns>자식 카운트</returns>

private static int GetChildCount(Contour<Point> contour)

{

Contour<Point> childContour = contour.VNext;

if(childContour == null)

{

return 0;

}

int count = 0;

while(childContour != null)

{

count++;

childContour = childContour.HNext;

}

return count;

}

#endregion

#region 자동차 번호판 찾기 - FindLicensePlate(pointContour, grayscaleImage, cannyImage, licensePlateImageList, filteredLicensePlateImageList,

detectedLicensePlateRectangleList, licenseList)

/// <summary>

/// 자동차 번호판 찾기

/// </summary>

/// <param name="pointContour">포인트 윤곽</param>

/// <param name="grayscaleImage">회색조 이미지</param>

/// <param name="cannyImage">캐니 이미지</param>

/// <param name="licensePlateImageList">자동차 번호판 이미지 리스트</param>

/// <param name="filteredLicensePlateImageList">필터 자동차 번호판 이미지 리스트</param>

/// <param name="detectedLicensePlateRectangleList">검출 자동차 번호판 사각형 리스트</param>

/// <param name="licenseList">자동차 번호 리스트</param>

private void FindLicensePlate

(

Contour<Point> pointContour,

Image<Gray, Byte> grayscaleImage,

Image<Gray, Byte> cannyImage,

List<Image<Gray, Byte>> licensePlateImageList,

List<Image<Gray, Byte>> filteredLicensePlateImageList,

List<MCvBox2D> detectedLicensePlateRectangleList,

List<String> licenseList

)

{

for(; pointContour != null; pointContour = pointContour.HNext)

{

int childCount = GetChildCount(pointContour);

if(childCount == 0)

{

continue;

}

if(pointContour.Area > 400)

{

if(childCount < 3)

{

// 윤곽선에 자식 윤곽선이 3개 보다 작은 경우는 자동차 번호판이 아니디.

// (자동차 번호판에 문자가 3자 이상 있다고 가정한다)

// 그러나 윤곽선의 자식 윤곽선을 검색해 그 중 하나가 자동차 번호판인지 확인해야 한다.

FindLicensePlate

(

pointContour.VNext,

grayscaleImage,

cannyImage,

licensePlateImageList,

filteredLicensePlateImageList,

detectedLicensePlateRectangleList,

licenseList

);

continue;

}

MCvBox2D rectangle = pointContour.GetMinAreaRect();

if(rectangle.angle < -45.0)

{

float temporaryWidth = rectangle.size.Width;

rectangle.size.Width = rectangle.size.Height;

rectangle.size.Height = temporaryWidth;

rectangle.angle += 90.0f;

}

else if(rectangle.angle > 45.0)

{

float temporaryWidth = rectangle.size.Width;

rectangle.size.Width = rectangle.size.Height;

rectangle.size.Height = temporaryWidth;

rectangle.angle -= 90.0f;

}

double ratio = (double)rectangle.size.Width / rectangle.size.Height;

if(!(3.0 < ratio && ratio < 10.0))

{

Contour<Point> childContour = pointContour.VNext;

if(childContour != null)

{

FindLicensePlate

(

childContour,

grayscaleImage,

cannyImage,

licensePlateImageList,

filteredLicensePlateImageList,

detectedLicensePlateRectangleList,

licenseList

);

}

continue;

}

using(Image<Gray, Byte> temporaryImage1 = grayscaleImage.Copy(rectangle))

{

using(Image<Gray, Byte> temporaryImage2 = temporaryImage1.Resize(240, 180, INTER.CV_INTER_CUBIC, true))

{

int edgePixelSize = 2;

temporaryImage2.ROI = new Rectangle

(

new Point(edgePixelSize, edgePixelSize),

temporaryImage2.Size - new Size(2 * edgePixelSize, 2 * edgePixelSize)

);

Image<Gray, Byte> plateImage = temporaryImage2.Copy();

Image<Gray, Byte> filteredPlateImage = FilterLicensePlateImage(plateImage);

Tesseract.Charactor[] charactorArray;

StringBuilder stringBuilder = new StringBuilder();

using(Image<Gray, Byte> temporaryImage3 = filteredPlateImage.Clone())

{

this.ocr.Recognize(temporaryImage3);

charactorArray = this.ocr.GetCharactors();

if(charactorArray.Length == 0)

{

continue;

}

for(int i = 0; i < charactorArray.Length; i++)

{

stringBuilder.Append(charactorArray[i].Text);

}

licenseList.Add(stringBuilder.ToString());

licensePlateImageList.Add(plateImage);

filteredLicensePlateImageList.Add(filteredPlateImage);

detectedLicensePlateRectangleList.Add(rectangle);

}

#endregion

#region 자동차 번호판 이미지 필터하기 - FilterLicensePlateImage(sourceImage)

/// <summary>

/// 자동차 번호판 이미지 필터하기

/// </summary>

/// <param name="sourceImage">소스 이미지</param>

/// <returns>필터 이미지</returns>

private static Image<Gray, Byte> FilterLicensePlateImage(Image<Gray, Byte> sourceImage)

{

Image<Gray, Byte> threshImage = sourceImage.ThresholdBinaryInv(new Gray(120), new Gray(255));

using(Image<Gray, Byte> maskImage = new Image<Gray, byte>(sourceImage.Size))

{

using(Image<Gray, Byte> cannyImage = sourceImage.Canny(100, 50))

{

using(MemStorage storage = new MemStorage())

{

maskImage.SetValue(255.0);

for(Contour<Point> pointContour = cannyImage.FindContours(CHAIN_APPROX_METHOD.CV_CHAIN_APPROX_SIMPLE, RETR_TYPE.CV_RETR_EXTERNAL, storage);

pointContour != null; pointContour = pointContour.HNext)

{

Rectangle rectangle = pointContour.BoundingRectangle;

if(rectangle.Height > (sourceImage.Height >> 1))

{

rectangle.X -= 1;

rectangle.Y -= 1;

rectangle.Width += 2;

rectangle.Height += 2;

rectangle.Intersect(sourceImage.ROI);

maskImage.Draw(rectangle, new Gray(0.0), -1);

}

threshImage.SetValue(0, maskImage);

}

threshImage._Erode(1);

threshImage._Dilate(1);

return threshImage;

}

#endregion

#region 객체 리소스 해제하기 - DisposeObject()

/// <summary>

/// 객체 리소스 해제하기

/// </summary>

protected override void DisposeObject()

{

this.ocr.Dispose();

}

#endregion

}

▶ MainForm.cs


using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Drawing;
using System.Windows.Forms;

using Emgu.CV;
using Emgu.CV.Structure;
using Emgu.CV.UI;

namespace TestProject
{
    /// <summary>
    /// 메인 폼
    /// </summary>
    public partial class MainForm : Form
    {
        //////////////////////////////////////////////////////////////////////////////////////////////////// Field
        ////////////////////////////////////////////////////////////////////////////////////////// Private

        #region Field

        /// <summary>
        /// 번호판 검출기
        /// </summary>
        private LicensePlateDetector licensePlateDetector;

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Constructor
        ////////////////////////////////////////////////////////////////////////////////////////// Public

        #region 생성자 - MainForm()

        /// <summary>
        /// 생성자
        /// </summary>
        public MainForm()
        {
            InitializeComponent();

            this.filePathButton.Click += filePathButton_Click;

            this.licensePlateDetector = new LicensePlateDetector("");

            ProcessImage(new Image<Bgr, byte>("LicensePlate.jpg"));
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////////////////////////// Method
        ////////////////////////////////////////////////////////////////////////////////////////// Private
        //////////////////////////////////////////////////////////////////////////////// Event

        #region 파일 경로 버튼 클릭시 처리하기 - filePathButton_Click(sender, e)

        /// <summary>
        /// 파일 경로 버튼 클릭시 처리하기
        /// </summary>
        /// <param name="sender">이벤트 발생자</param>
        /// <param name="e">이벤트 인자</param>
        private void filePathButton_Click(object sender, EventArgs e)
        {
            DialogResult result = this.openFileDialog.ShowDialog();

            if(result == DialogResult.OK)
            {
                Image<Bgr, Byte> image;

                try
                {
                    image = new Image<Bgr, byte>(this.openFileDialog.FileName);
                }
                catch
                {
                    MessageBox.Show(string.Format("무효한 파일 : {0}", this.openFileDialog.FileName));

                    return;
                }

                ProcessImage(image);
            }
        }

        #endregion

        //////////////////////////////////////////////////////////////////////////////// Function

        #region 레이블/이미지 추가하기 - AddLabelAndImage(startPoint, labelText, image)

        /// <summary>
        /// 레이블/이미지 추가하기
        /// </summary>
        /// <param name="startPoint">시작 위치</param>
        /// <param name="labelText">레이블 텍스트</param>
        /// <param name="image">이미지</param>
        private void AddLabelAndImage(ref Point startPoint, string labelText, IImage image)
        {
            Label label = new Label();

            this.resultPanel.Controls.Add(label);

            label.Width    = 200;
            label.Height   = 30;
            label.Location = startPoint;
            label.Text     = labelText;

            startPoint.Y += label.Height;

            ImageBox imageBox = new ImageBox();

            this.resultPanel.Controls.Add(imageBox);

            imageBox.ClientSize = image.Size;
            imageBox.Location   = startPoint;
            imageBox.Image      = image;

            startPoint.Y += imageBox.Height + 10;
        }

        #endregion
        #region 이미지 처리하기 - ProcessImage(image)

        /// <summary>
        /// 이미지 처리하기
        /// </summary>
        /// <param name="image">이미지</param>
        private void ProcessImage(Image<Bgr, byte> image)
        {
            Stopwatch stopwatch = Stopwatch.StartNew();

            List<Image<Gray, Byte>> licensePlateImageList = new List<Image<Gray, byte>>();

            List<Image<Gray, Byte>> filteredLicensePlateImageList = new List<Image<Gray, byte>>();

            List<MCvBox2D> licenseRectangleList = new List<MCvBox2D>();

            List<string> licensePlateArray = this.licensePlateDetector.DetectLicensePlate
            (
                image,
                licensePlateImageList,
                filteredLicensePlateImageList,
                licenseRectangleList
            );

            stopwatch.Stop();

            this.messageLabel.Text = string.Format("자동차 번호판 인식 시간 : {0} 밀리초", stopwatch.Elapsed.TotalMilliseconds);

            this.resultPanel.Controls.Clear();

            Point startPoint = new Point(10, 10);

            for(int i = 0; i < licensePlateArray.Count; i++)
            {
                AddLabelAndImage
                (
                    ref startPoint,
                    string.Format("자동차 번호 : {0}", licensePlateArray[i]),
                    licensePlateImageList[i].ConcateVertical(filteredLicensePlateImageList[i])
                );

                image.Draw(licenseRectangleList[i], new Bgr(Color.Red), 2);
            }

            this.imageBox.Image = image;
        }

        #endregion
    }
}

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using System;

using System.Collections.Generic;

using System.Diagnostics;

using System.Drawing;

using System.Windows.Forms;

using Emgu.CV;

using Emgu.CV.Structure;

using Emgu.CV.UI;

namespace TestProject

{

/// <summary>

/// 메인 폼

/// </summary>

public partial class MainForm : Form

{

//////////////////////////////////////////////////////////////////////////////////////////////////// Field

////////////////////////////////////////////////////////////////////////////////////////// Private

#region Field

/// <summary>

/// 번호판 검출기

/// </summary>

private LicensePlateDetector licensePlateDetector;

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Constructor

////////////////////////////////////////////////////////////////////////////////////////// Public

#region 생성자 - MainForm()

/// <summary>

/// 생성자

/// </summary>

public MainForm()

{

InitializeComponent();

this.filePathButton.Click += filePathButton_Click;

this.licensePlateDetector = new LicensePlateDetector("");

ProcessImage(new Image<Bgr, byte>("LicensePlate.jpg"));

}

#endregion

//////////////////////////////////////////////////////////////////////////////////////////////////// Method

////////////////////////////////////////////////////////////////////////////////////////// Private

//////////////////////////////////////////////////////////////////////////////// Event

#region 파일 경로 버튼 클릭시 처리하기 - filePathButton_Click(sender, e)

/// <summary>

/// 파일 경로 버튼 클릭시 처리하기

/// </summary>

/// <param name="sender">이벤트 발생자</param>

/// <param name="e">이벤트 인자</param>

private void filePathButton_Click(object sender, EventArgs e)

{

DialogResult result = this.openFileDialog.ShowDialog();

if(result == DialogResult.OK)

{

Image<Bgr, Byte> image;

try

{

image = new Image<Bgr, byte>(this.openFileDialog.FileName);

}

catch

{

MessageBox.Show(string.Format("무효한 파일 : {0}", this.openFileDialog.FileName));

return;

}

ProcessImage(image);

}

#endregion

//////////////////////////////////////////////////////////////////////////////// Function

#region 레이블/이미지 추가하기 - AddLabelAndImage(startPoint, labelText, image)

/// <summary>

/// 레이블/이미지 추가하기

/// </summary>

/// <param name="startPoint">시작 위치</param>

/// <param name="labelText">레이블 텍스트</param>

/// <param name="image">이미지</param>

private void AddLabelAndImage(ref Point startPoint, string labelText, IImage image)

{

Label label = new Label();

this.resultPanel.Controls.Add(label);

label.Width = 200;

label.Height = 30;

label.Location = startPoint;

label.Text = labelText;

startPoint.Y += label.Height;

ImageBox imageBox = new ImageBox();

this.resultPanel.Controls.Add(imageBox);

imageBox.ClientSize = image.Size;

imageBox.Location = startPoint;

imageBox.Image = image;

startPoint.Y += imageBox.Height + 10;

}

#endregion

#region 이미지 처리하기 - ProcessImage(image)

/// <summary>

/// 이미지 처리하기

/// </summary>

/// <param name="image">이미지</param>

private void ProcessImage(Image<Bgr, byte> image)

{

Stopwatch stopwatch = Stopwatch.StartNew();

List<Image<Gray, Byte>> licensePlateImageList = new List<Image<Gray, byte>>();

List<Image<Gray, Byte>> filteredLicensePlateImageList = new List<Image<Gray, byte>>();

List<MCvBox2D> licenseRectangleList = new List<MCvBox2D>();

List<string> licensePlateArray = this.licensePlateDetector.DetectLicensePlate

(

image,

licensePlateImageList,

filteredLicensePlateImageList,

licenseRectangleList

);

stopwatch.Stop();

this.messageLabel.Text = string.Format("자동차 번호판 인식 시간 : {0} 밀리초", stopwatch.Elapsed.TotalMilliseconds);

this.resultPanel.Controls.Clear();

Point startPoint = new Point(10, 10);

for(int i = 0; i < licensePlateArray.Count; i++)

{

AddLabelAndImage

(

ref startPoint,

string.Format("자동차 번호 : {0}", licensePlateArray[i]),

licensePlateImageList[i].ConcateVertical(filteredLicensePlateImageList[i])

);

image.Draw(licenseRectangleList[i], new Bgr(Color.Red), 2);

}

this.imageBox.Image = image;

}

#endregion

}

TestProject.zip