mirror of
https://github.com/Laex/Delphi-OpenCV.git
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256 lines
12 KiB
ObjectPascal
256 lines
12 KiB
ObjectPascal
(*
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*****************************************************************
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Delphi-OpenCV
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Copyright (C) 2013 Project Delphi-OpenCV
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****************************************************************
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Contributor:
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Laentir Valetov
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email:laex@bk.ru
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****************************************************************
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You may retrieve the latest version of this file at the GitHub,
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located at git://github.com/Laex/Delphi-OpenCV.git
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****************************************************************
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The contents of this file are used with permission, subject to
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the Mozilla Public License Version 1.1 (the "License"); you may
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not use this file except in compliance with the License. You may
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obtain a copy of the License at
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http://www.mozilla.org/MPL/MPL-1_1Final.html
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Software distributed under the License is distributed on an
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"AS IS" basis, WITHOUT WARRANTY OF ANY KIND, either express or
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implied. See the License for the specific language governing
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rights and limitations under the License.
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*******************************************************************
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*)
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unit ocv.cls.objdetect;
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{$I OpenCV.inc}
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interface
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Uses
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Winapi.Windows,
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ocv.cls.types,
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ocv.core.types_c,
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ocv.cls.core;
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Type
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ICascadeClassifier = interface(IOCVCommon)
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['{700C3DEC-F156-4014-9676-5BD9ECC3B01B}']
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function empty(): cbool;
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function load(const FileName: String): cbool;
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// function Read(const node: IFileNode): cbool;
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procedure detectMultiScale(Image: IMat; var objects: TArray<TCvRect>; scaleFactor: double { = 1.1 };
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minNeighbors: integer { = 3 }; flags: integer { = 0 }; minSize: ISize { = Size() };
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maxSize: ISize { = Size() } ); overload;
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procedure detectMultiScale(Image: IMat; Var objects: TVectorRect; var numDetections: TVectorInt;
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scaleFactor: double { = 1.1 }; minNeighbors: integer { = 3 }; flags: integer { = 0 }; minSize: ISize { = Size() };
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maxSize: ISize { = Size() } ); overload;
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procedure detectMultiScale(Image: IMat; Var objects: TVectorRect; var rejectLevels: TVectorInt;
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Var levelWeights: TVectorDouble; scaleFactor: double { = 1.1 }; minNeighbors: integer { = 3 };
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flags: integer { = 0 }; minSize: ISize { = Size() }; maxSize: ISize { = Size() };
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outputRejectLevels: cbool = false); overload;
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function isOldFormatCascade(): cbool;
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function getOriginalWindowSize(): ISize;
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function getFeatureType(): integer;
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function setImage(Image: IMat): cbool;
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// function convert(const oldcascade: String; const newcascade: String): cbool;
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end;
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TCascadeClassifier = class(TOCVCommon, ICascadeClassifier)
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private
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public
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constructor Create; overload;
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(* * @brief Loads a classifier from a file.
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@param filename Name of the file from which the classifier is loaded.
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*)
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constructor Create(const FileName: String); overload;
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destructor Destroy; override;
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(* * @brief Checks whether the classifier has been loaded.
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*)
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function empty(): cbool;
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(* * @brief Loads a classifier from a file.
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@param filename Name of the file from which the classifier is loaded. The file may contain an old
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HAAR classifier trained by the haartraining application or a new cascade classifier trained by the
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traincascade application.
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*)
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function load(const FileName: String): cbool;
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(* * @brief Reads a classifier from a FileStorage node.
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@note The file may contain a new cascade classifier (trained traincascade application) only.
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*)
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// function Read(const node: IFileNode): cbool;
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(* * @brief Detects objects of different sizes in the input image. The detected objects are returned as a list
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of rectangles.
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@param image Matrix of the type CV_8U containing an image where objects are detected.
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@param objects Vector of rectangles where each rectangle contains the detected object, the
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rectangles may be partially outside the original image.
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@param scaleFactor Parameter specifying how much the image size is reduced at each image scale.
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@param minNeighbors Parameter specifying how many neighbors each candidate rectangle should have
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to retain it.
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@param flags Parameter with the same meaning for an old cascade as in the function
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cvHaarDetectObjects. It is not used for a new cascade.
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@param minSize Minimum possible object size. Objects smaller than that are ignored.
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@param maxSize Maximum possible object size. Objects larger than that are ignored.
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The function is parallelized with the TBB library.
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@note
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- (Python) A face detection example using cascade classifiers can be found at
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opencv_source_code/samples/python2/facedetect.py
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*)
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procedure detectMultiScale(Image: IMat; var objects: TArray<TCvRect>; scaleFactor: double { = 1.1 };
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minNeighbors: integer { = 3 }; flags: integer { = 0 }; minSize: ISize { = Size() };
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maxSize: ISize { = Size() } ); overload;
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(* * @overload
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@param image Matrix of the type CV_8U containing an image where objects are detected.
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@param objects Vector of rectangles where each rectangle contains the detected object, the
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rectangles may be partially outside the original image.
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@param numDetections Vector of detection numbers for the corresponding objects. An object's number
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of detections is the number of neighboring positively classified rectangles that were joined
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together to form the object.
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@param scaleFactor Parameter specifying how much the image size is reduced at each image scale.
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@param minNeighbors Parameter specifying how many neighbors each candidate rectangle should have
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to retain it.
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@param flags Parameter with the same meaning for an old cascade as in the function
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cvHaarDetectObjects. It is not used for a new cascade.
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@param minSize Minimum possible object size. Objects smaller than that are ignored.
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@param maxSize Maximum possible object size. Objects larger than that are ignored.
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*)
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procedure detectMultiScale(Image: IMat; Var objects: TVectorRect; var numDetections: TVectorInt;
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scaleFactor: double { = 1.1 }; minNeighbors: integer { = 3 }; flags: integer { = 0 }; minSize: ISize { = Size() };
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maxSize: ISize { = Size() } ); overload;
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(* * @overload
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if `outputRejectLevels` is `true` returns `rejectLevels` and `levelWeights`
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*)
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procedure detectMultiScale(Image: IMat; Var objects: TVectorRect; var rejectLevels: TVectorInt;
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Var levelWeights: TVectorDouble; scaleFactor: double { = 1.1 }; minNeighbors: integer { = 3 };
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flags: integer { = 0 }; minSize: ISize { = Size() }; maxSize: ISize { = Size() };
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outputRejectLevels: cbool = false); overload;
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function isOldFormatCascade(): cbool;
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function getOriginalWindowSize(): ISize;
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function getFeatureType(): integer;
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function setImage(Image: IMat): cbool;
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// function convert(const oldcascade: String; const newcascade: String): cbool;
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end;
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implementation
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Uses
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ocv.core_c, ocv.utils, ocv.lib, SysUtils;
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// ------------------------------ CascadeClassifier ------------------------------
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function _CreateCascadeClassifier: TOpenCVClass; stdcall; external opencv_classes_lib name '_CreateCascadeClassifier@0';
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procedure _DestroyCascadeClassifier(const CascadeClassifier: TOpenCVClass); stdcall;
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external opencv_classes_lib name '_DestroyCascadeClassifier@4';
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function _get_CascadeClassifier_empty(CascadeClassifier: TOpenCVClass): cbool; stdcall;
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external opencv_classes_lib name '_get_CascadeClassifier_empty@4';
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function _get_CascadeClassifier_load(CascadeClassifier: TOpenCVClass; FileName: PAnsiChar): cbool; stdcall;
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external opencv_classes_lib name '_get_CascadeClassifier_load@8';
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function _CascadeClassifier_isOldFormatCascade(CascadeClassifier: TOpenCVClass): cbool; stdcall;
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external opencv_classes_lib name '_CascadeClassifier_isOldFormatCascade@4';
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function _CascadeClassifier_getOriginalWindowSize(CascadeClassifier: TOpenCVClass): TOpenCVClass; stdcall;
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external opencv_classes_lib name '_CascadeClassifier_getOriginalWindowSize@4';
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function _CascadeClassifier_getFeatureType(CascadeClassifier: TOpenCVClass): integer; stdcall;
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external opencv_classes_lib name '_CascadeClassifier_getFeatureType@4';
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function _CascadeClassifier_setImage(CascadeClassifier: TOpenCVClass; m: TOpenCVClass): cbool; stdcall;
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external opencv_classes_lib name '_CascadeClassifier_setImage@8';
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// function _CascadeClassifier_convert(CascadeClassifier: TOpenCVClass; oldcascade, newcascade: PAnsiChar): cbool; stdcall;
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// external opencv_classes_lib name '_CascadeClassifier_convert@12';
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procedure _CascadeClassifier_detectMultiScale(CascadeClassifier: TOpenCVClass;
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Image: TOpenCVClass; Var rects: TOpenCVClass; var rectCount: NativeUInt; scaleFactor: double;
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minNeighbors: integer; flags: integer; minSize: TOpenCVClass; maxSize: TOpenCVClass); stdcall;
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external opencv_classes_lib name '_CascadeClassifier_detectMultiScale@40';
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procedure _CascadeClassifier_copyAndDestroyRects(rects: TOpenCVClass; objects: Pointer); stdcall;
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external opencv_classes_lib name '_CascadeClassifier_copyAndDestroyRects@8';
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{ ------------------------------ TCascadeClassifier ------------------------------ }
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// function TCascadeClassifier.convert(const oldcascade, newcascade: String): cbool;
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// begin
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// Result := _CascadeClassifier_convert(FData, oldcascade.AsPAnsiChar, newcascade.AsPAnsiChar);
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// end;
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constructor TCascadeClassifier.Create;
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begin
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inherited Create(_CreateCascadeClassifier);
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end;
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constructor TCascadeClassifier.Create(const FileName: String);
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begin
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inherited Create(_CreateCascadeClassifier);
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load(FileName);
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end;
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destructor TCascadeClassifier.Destroy;
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begin
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if Assigned(FData) then
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_DestroyCascadeClassifier(FData);
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inherited;
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end;
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procedure TCascadeClassifier.detectMultiScale(Image: IMat; var objects: TVectorRect; var numDetections: TVectorInt;
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scaleFactor: double; minNeighbors, flags: integer; minSize, maxSize: ISize);
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begin
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raise Exception.Create('Not implemented');
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end;
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procedure TCascadeClassifier.detectMultiScale(Image: IMat; var objects: TVectorRect; var rejectLevels: TVectorInt;
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var levelWeights: TVectorDouble; scaleFactor: double; minNeighbors, flags: integer; minSize, maxSize: ISize;
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outputRejectLevels: cbool);
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begin
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raise Exception.Create('Not implemented');
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end;
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procedure TCascadeClassifier.detectMultiScale(Image: IMat; var objects: TArray<TCvRect>; scaleFactor: double;
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minNeighbors, flags: integer; minSize, maxSize: ISize);
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var rects: TOpenCVClass; rectCount: NativeUInt;
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begin
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if Not Assigned(FData) then raise Exception.Create('TCascadeClassifier.detectMultiScale: FData is null');
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_CascadeClassifier_detectMultiScale(FData, Image._InternalData, rects, rectCount,
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scaleFactor, minNeighbors, flags, minSize._InternalData, maxSize._InternalData);
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SetLength(objects, rectCount);
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_CascadeClassifier_copyAndDestroyRects(rects, objects);
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end;
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function TCascadeClassifier.empty: cbool;
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begin
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Result := _get_CascadeClassifier_empty(FData);
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end;
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function TCascadeClassifier.getFeatureType: integer;
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begin
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Result := _CascadeClassifier_getFeatureType(FData);
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end;
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function TCascadeClassifier.getOriginalWindowSize: ISize;
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begin
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Result := TSize.Create(_CascadeClassifier_getOriginalWindowSize(FData));
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end;
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function TCascadeClassifier.isOldFormatCascade: cbool;
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begin
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Result := _CascadeClassifier_isOldFormatCascade(FData);
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end;
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function TCascadeClassifier.load(const FileName: String): cbool;
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begin
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Result := _get_CascadeClassifier_load(FData, c_str(FileName));
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end;
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function TCascadeClassifier.setImage(Image: IMat): cbool;
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begin
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Result := _CascadeClassifier_setImage(FData, Image._InternalData);
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end;
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end.
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