mirror of
https://github.com/ruby-opencv/ruby-opencv
synced 2023-03-27 23:22:12 -04:00
add minimal functions of EigenFaces
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parent
2ffd26a887
commit
336e9c4ad2
7 changed files with 250 additions and 4 deletions
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@ -109,6 +109,8 @@ ext/opencv/cvutils.cpp
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ext/opencv/cvutils.h
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ext/opencv/cvvideowriter.cpp
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ext/opencv/cvvideowriter.h
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ext/opencv/eigenfaces.cpp
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ext/opencv/eigenfaces.h
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ext/opencv/gui.cpp
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ext/opencv/gui.h
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ext/opencv/iplconvkernel.cpp
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@ -216,6 +218,7 @@ test/test_cvsurfpoint.rb
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test/test_cvtermcriteria.rb
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test/test_cvtwopoints.rb
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test/test_cvvideowriter.rb
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test/test_eigenfaces.rb
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test/test_iplconvkernel.rb
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test/test_iplimage.rb
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test/test_mouseevent.rb
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143
ext/opencv/eigenfaces.cpp
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143
ext/opencv/eigenfaces.cpp
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@ -0,0 +1,143 @@
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/************************************************************
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eigenfaces.cpp -
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$Author: ser1zw $
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Copyright (C) 2013 ser1zw
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************************************************************/
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#include <stdio.h>
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#include "eigenfaces.h"
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/*
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* Document-class: OpenCV::EigenFaces
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*
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*/
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__NAMESPACE_BEGIN_OPENCV
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__NAMESPACE_BEGIN_EIGENFACES
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VALUE rb_klass;
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std::map<long, cv::Ptr<cv::FaceRecognizer> > ptr_guard_map;
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VALUE
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rb_class()
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{
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return rb_klass;
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}
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void
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release_facerecognizer(void *ptr) {
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long key = (long)ptr;
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ptr_guard_map[key].release();
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ptr_guard_map.erase(key);
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}
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VALUE
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rb_allocate(VALUE klass)
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{
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return Data_Wrap_Struct(klass, 0, release_facerecognizer, NULL);
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}
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/*
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* call-seq:
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* EigenFaces.new(num_components=0, threshold=DBL_MAX)
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*/
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VALUE
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rb_initialize(int argc, VALUE argv[], VALUE self)
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{
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VALUE num_components_val, threshold_val;
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rb_scan_args(argc, argv, "02", &num_components_val, &threshold_val);
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int num_components = NIL_P(num_components_val) ? 0 : NUM2INT(num_components_val);
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double threshold = NIL_P(threshold_val) ? DBL_MAX : NUM2DBL(threshold_val);
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free(DATA_PTR(self));
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cv::Ptr<cv::FaceRecognizer> ptr = cv::createEigenFaceRecognizer(num_components, threshold);
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DATA_PTR(self) = ptr;
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long key = (long)(DATA_PTR(self));
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ptr_guard_map[key] = ptr; // To avoid cv::Ptr's GC
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return self;
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}
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/*
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* call-seq:
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* train(src, labels)
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*
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* Trains a FaceRecognizer with given data and associated labels.
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*/
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VALUE
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rb_train(VALUE self, VALUE src, VALUE labels)
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{
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Check_Type(src, T_ARRAY);
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Check_Type(labels, T_ARRAY);
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VALUE *src_ptr = RARRAY_PTR(src);
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int src_size = RARRAY_LEN(src);
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std::vector<cv::Mat> images;
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for (int i = 0; i < src_size; i++) {
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images.push_back(cv::Mat(CVMAT_WITH_CHECK(src_ptr[i])));
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}
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VALUE *labels_ptr = RARRAY_PTR(labels);
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int labels_size = RARRAY_LEN(labels);
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std::vector<int> local_labels;
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for (int i = 0; i < labels_size; i++) {
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local_labels.push_back(NUM2INT(labels_ptr[i]));
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}
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cv::FaceRecognizer *self_ptr = FACERECOGNIZER(self);
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try {
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self_ptr->train(images, local_labels);
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}
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catch (cv::Exception& e) {
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raise_cverror(e);
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}
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return Qnil;
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}
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/*
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* call-seq:
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* predict(src)
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*
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* Predicts a label and associated confidence (e.g. distance) for a given input image.
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*/
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VALUE
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rb_predict(VALUE self, VALUE src)
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{
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cv::Mat mat = cv::Mat(CVMAT_WITH_CHECK(src));
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cv::FaceRecognizer *self_ptr = FACERECOGNIZER(self);
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int label;
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try {
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label = self_ptr->predict(mat);
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}
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catch (cv::Exception& e) {
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raise_cverror(e);
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}
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return INT2NUM(label);
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}
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void
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define_ruby_class()
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{
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if (rb_klass)
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return;
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/*
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* opencv = rb_define_module("OpenCV");
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*
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* note: this comment is used by rdoc.
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*/
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VALUE opencv = rb_module_opencv();
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rb_klass = rb_define_class_under(opencv, "EigenFaces", rb_cObject);
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rb_define_alloc_func(rb_klass, rb_allocate);
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rb_define_private_method(rb_klass, "initialize", RUBY_METHOD_FUNC(rb_initialize), -1);
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rb_define_method(rb_klass, "train", RUBY_METHOD_FUNC(rb_train), 2);
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rb_define_method(rb_klass, "predict", RUBY_METHOD_FUNC(rb_predict), 1);
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}
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__NAMESPACE_END_EIGENFACES
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__NAMESPACE_END_OPENCV
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42
ext/opencv/eigenfaces.h
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42
ext/opencv/eigenfaces.h
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@ -0,0 +1,42 @@
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/************************************************************
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eigenfacerecognizer.h
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$Author: ser1zw $
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Copyright (C) 2013 ser1zw
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************************************************************/
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#ifndef RUBY_OPENCV_EIGENFACES_H
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#define RUBY_OPENCV_EIGENFACES_H
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#include "opencv.h"
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#define __NAMESPACE_BEGIN_EIGENFACES namespace cEigenFaces {
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#define __NAMESPACE_END_EIGENFACES }
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__NAMESPACE_BEGIN_OPENCV
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__NAMESPACE_BEGIN_EIGENFACES
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VALUE rb_class();
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void define_ruby_class();
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VALUE rb_allocate(VALUE klass);
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VALUE rb_initialize(int argc, VALUE argv[], VALUE self);
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VALUE rb_train(VALUE self, VALUE src, VALUE labels);
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__NAMESPACE_END_EIGENFACES
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inline cv::FaceRecognizer*
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FACERECOGNIZER(VALUE object)
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{
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cv::FaceRecognizer *ptr;
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Data_Get_Struct(object, cv::FaceRecognizer, ptr);
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return ptr;
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}
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__NAMESPACE_END_OPENCV
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#endif // RUBY_OPENCV_EIGENFACES_H
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@ -706,6 +706,9 @@ extern "C" {
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mOpenCV::cCvConnectedComp::define_ruby_class();
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mOpenCV::cCvAvgComp::define_ruby_class();
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mOpenCV::cCvHaarClassifierCascade::define_ruby_class();
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mOpenCV::cEigenFaces::define_ruby_class();
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mOpenCV::mGUI::define_ruby_module();
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mOpenCV::mGUI::cWindow::define_ruby_class();
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mOpenCV::mGUI::cTrackbar::define_ruby_class();
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@ -130,6 +130,8 @@ extern "C" {
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#include "cvfeaturetree.h"
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#include "eigenfaces.h"
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// GUI
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#include "gui.h"
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#include "window.h"
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File diff suppressed because one or more lines are too long
53
test/test_eigenfaces.rb
Executable file
53
test/test_eigenfaces.rb
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#!/usr/bin/env ruby
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# -*- mode: ruby; coding: utf-8-unix -*-
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require 'test/unit'
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require 'opencv'
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require File.expand_path(File.dirname(__FILE__)) + '/helper'
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include OpenCV
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# Tests for OpenCV::EigenFaces
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class TestEigenFaces < OpenCVTestCase
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def setup
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@eigenfaces = EigenFaces.new
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end
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def test_initialize
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[EigenFaces.new, EigenFaces.new(1), EigenFaces.new(1, 99999)].each { |ef|
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assert_equal(EigenFaces, ef.class)
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}
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assert_raise(TypeError) {
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EigenFaces.new(DUMMY_OBJ)
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}
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assert_raise(TypeError) {
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EigenFaces.new(1, DUMMY_OBJ)
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}
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end
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def test_train
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img = CvMat.load(FILENAME_LENA256x256, CV_LOAD_IMAGE_GRAYSCALE)
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assert_nil(@eigenfaces.train([img], [1]))
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assert_raise(TypeError) {
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@eigenfaces.train(DUMMY_OBJ, [1])
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}
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assert_raise(TypeError) {
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@eigenfaces.train([img], DUMMY_OBJ)
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}
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end
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def test_predict
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img = CvMat.load(FILENAME_LENA256x256, CV_LOAD_IMAGE_GRAYSCALE)
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label = 1
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@eigenfaces.train([img], [label])
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assert_equal(label, @eigenfaces.predict(img))
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assert_raise(TypeError) {
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@eigenfaces.predict(DUMMY_OBJ)
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}
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end
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end
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