/*
* Constructor
*
* @overload new(seq_flags = CV_SEQ_ELTYPE_POINT | CV_SEQ_KIND_GENERIC, storage = nil)
* @param [Fixnum] seq_flags Flags of the created sequence, which are combinations of
* the element types and sequence types.
* - Element type:
* - <tt>CV_SEQ_ELTYPE_POINT</tt>: {CvPoint}
* - <tt>CV_32FC2</tt>: {CvPoint2D32f}
* - <tt>CV_SEQ_ELTYPE_POINT3D</tt>: {CvPoint3D32f}
* - <tt>CV_SEQ_ELTYPE_INDEX</tt>: Fixnum
* - <tt>CV_SEQ_ELTYPE_CODE</tt>: Fixnum (Freeman code)
* - Sequence type:
* - <tt>CV_SEQ_KIND_GENERIC</tt>: Generic sequence
* - <tt>CV_SEQ_KIND_CURVE</tt>: Curve
* @param [CvMemStorage] storage Sequence location
* @return [CvContour] self
* @opencv_func cvCreateSeq
* @example
* seq = CvContour.new(CV_SEQ_ELTYPE_POINT | CV_SEQ_KIND_CURVE)
* seq << CvPoint.new(1, 2)
* seq << 3 #=> TypeError
*/
VALUE
rb_initialize(int argc, VALUE *argv, VALUE self)
{
VALUE seq_flags_value, storage_value;
rb_scan_args(argc, argv, "02", &seq_flags_value, &storage_value);
int seq_flags = 0;
if (NIL_P(seq_flags_value)) {
seq_flags = CV_SEQ_ELTYPE_POINT | CV_SEQ_KIND_GENERIC;
}
else {
Check_Type(seq_flags_value, T_FIXNUM);
seq_flags = FIX2INT(seq_flags_value);
}
storage_value = CHECK_CVMEMSTORAGE(storage_value);
try {
DATA_PTR(self) = (CvContour*)cCvSeq::create_seq(seq_flags, sizeof(CvContour), storage_value);
}
catch (cv::Exception& e) {
raise_cverror(e);
}
return self;
}
CvSeq*
create_seq(int seq_flags, size_t header_size, VALUE storage_value)
{
VALUE klass = Qnil;
int eltype = seq_flags & CV_SEQ_ELTYPE_MASK;
storage_value = CHECK_CVMEMSTORAGE(storage_value);
if (!eltype2class(eltype, &klass)) {
seq_flags = CV_SEQ_ELTYPE_POINT | CV_SEQ_KIND_GENERIC;
}
int mat_type = CV_MAT_TYPE(seq_flags);
size_t elem_size = (size_t)(CV_ELEM_SIZE(mat_type));
CvSeq* seq = NULL;
try {
seq = cvCreateSeq(seq_flags, header_size, elem_size, CVMEMSTORAGE(storage_value));
}
catch (cv::Exception& e) {
raise_cverror(e);
}
register_elem_class(seq, klass);
register_root_object(seq, storage_value);
return seq;
}
/*
* call-seq:
* CvSeq.new(type[,storage])
*
* Return a new CvSeq. <i>type</i> should be following classes.
*
* * CvIndex
* * CvPoint
*/
VALUE
rb_initialize(int argc, VALUE *argv, VALUE self)
{
VALUE klass, storage_value;
rb_scan_args(argc, argv, "11", &klass, &storage_value);
if (!rb_obj_is_kind_of(klass, rb_cClass))
raise_typeerror(klass, rb_cClass);
int type = 0, size = 0;
if (klass == rb_cFixnum) {
type = CV_SEQ_ELTYPE_INDEX;
size = sizeof(int);
}
else if (klass == cCvPoint::rb_class()) {
type = CV_SEQ_ELTYPE_POINT;
size = sizeof(CvPoint);
}
else if (klass == cCvPoint2D32f::rb_class()) {
type = CV_SEQ_ELTYPE_POINT;
size = sizeof(CvPoint2D32f);
}
else if (klass == cCvPoint3D32f::rb_class()) {
type = CV_SEQ_ELTYPE_POINT3D;
size = sizeof(CvPoint3D32f);
}
else
rb_raise(rb_eArgError, "unsupport %s class for sequence-block.", rb_class2name(klass));
CvSeq* seq = NULL;
if (NIL_P(storage_value)) {
storage_value = cCvMemStorage::new_object(0);
}
else {
storage_value = CHECK_CVMEMSTORAGE(storage_value);
}
try {
seq = cvCreateSeq(type, sizeof(CvSeq), size, CVMEMSTORAGE(storage_value));
}
catch (cv::Exception& e) {
raise_cverror(e);
}
DATA_PTR(self) = seq;
register_elem_class(seq, klass);
register_root_object(seq, storage_value);
return self;
}
CvSeq*
create_seq(int seq_flags, size_t header_size, VALUE storage_value)
{
VALUE klass = Qnil;
int eltype = seq_flags & CV_SEQ_ELTYPE_MASK;
storage_value = CHECK_CVMEMSTORAGE(storage_value);
switch (eltype) {
case CV_SEQ_ELTYPE_POINT:
klass = cCvPoint::rb_class();
break;
case CV_32FC2:
klass = cCvPoint2D32f::rb_class();
break;
case CV_SEQ_ELTYPE_POINT3D:
klass = cCvPoint3D32f::rb_class();
break;
case CV_SEQ_ELTYPE_CODE:
case CV_SEQ_ELTYPE_INDEX:
klass = rb_cFixnum;
break;
case CV_SEQ_ELTYPE_PPOINT: // or CV_SEQ_ELTYPE_PTR:
// Not supported
rb_raise(rb_eArgError, "seq_flags %d is not supported.", eltype);
break;
default:
seq_flags = CV_SEQ_ELTYPE_POINT | CV_SEQ_KIND_GENERIC;
klass = cCvPoint::rb_class();
break;
}
int mat_type = CV_MAT_TYPE(seq_flags);
size_t elem_size = (size_t)(CV_ELEM_SIZE(mat_type));
CvSeq* seq = NULL;
try {
seq = cvCreateSeq(seq_flags, header_size, elem_size, CVMEMSTORAGE(storage_value));
}
catch (cv::Exception& e) {
raise_cverror(e);
}
register_elem_class(seq, klass);
register_root_object(seq, storage_value);
return seq;
}
/*
* call-seq:
* detect_objects(image[, options]) -> cvseq(include CvAvgComp object)
* detect_objects(image[, options]){|cmp| ... } -> cvseq(include CvAvgComp object)
*
* Detects objects in the image. This method finds rectangular regions in the
* given image that are likely to contain objects the cascade has been trained
* for and return those regions as a sequence of rectangles.
*
* * <i>option</i> should be Hash include these keys.
* :scale_factor (should be > 1.0)
* The factor by which the search window is scaled between the subsequent scans,
* 1.1 mean increasing window by 10%.
* :storage
* Memory storage to store the resultant sequence of the object candidate rectangles
* :flags
* Mode of operation. Currently the only flag that may be specified is CV_HAAR_DO_CANNY_PRUNING .
* If it is set, the function uses Canny edge detector to reject some image regions that contain
* too few or too much edges and thus can not contain the searched object. The particular threshold
* values are tuned for face detection and in this case the pruning speeds up the processing
* :min_neighbors
* Minimum number (minus 1) of neighbor rectangles that makes up an object.
* All the groups of a smaller number of rectangles than min_neighbors - 1 are rejected.
* If min_neighbors is 0, the function does not any grouping at all and returns all the detected
* candidate rectangles, whitch many be useful if the user wants to apply a customized grouping procedure.
* :min_size
* Minimum window size. By default, it is set to size of samples the classifier has been
* trained on (~20x20 for face detection).
* :max_size
* aximum window size to use. By default, it is set to the size of the image.
*/
VALUE
rb_detect_objects(int argc, VALUE *argv, VALUE self)
{
VALUE image, options;
rb_scan_args(argc, argv, "11", &image, &options);
double scale_factor;
int flags, min_neighbors;
CvSize min_size, max_size;
VALUE storage_val;
if (NIL_P(options)) {
scale_factor = 1.1;
flags = 0;
min_neighbors = 3;
min_size = max_size = cvSize(0, 0);
storage_val = cCvMemStorage::new_object();
}
else {
scale_factor = IF_DBL(LOOKUP_CVMETHOD(options, "scale_factor"), 1.1);
flags = IF_INT(LOOKUP_CVMETHOD(options, "flags"), 0);
min_neighbors = IF_INT(LOOKUP_CVMETHOD(options, "min_neighbors"), 3);
VALUE min_size_val = LOOKUP_CVMETHOD(options, "min_size");
min_size = NIL_P(min_size_val) ? cvSize(0, 0) : VALUE_TO_CVSIZE(min_size_val);
VALUE max_size_val = LOOKUP_CVMETHOD(options, "max_size");
max_size = NIL_P(max_size_val) ? cvSize(0, 0) : VALUE_TO_CVSIZE(max_size_val);
storage_val = CHECK_CVMEMSTORAGE(LOOKUP_CVMETHOD(options, "storage"));
}
VALUE result = Qnil;
try {
IplImage *ipl = IPLIMAGE_WITH_CHECK(image);
CvSeq *seq = cvHaarDetectObjects(ipl, CVHAARCLASSIFIERCASCADE(self), CVMEMSTORAGE(storage_val),
scale_factor, min_neighbors, flags, min_size, max_size);
result = cCvSeq::new_sequence(cCvSeq::rb_class(), seq, cCvAvgComp::rb_class(), storage_val);
if (rb_block_given_p()) {
for(int i = 0; i < seq->total; ++i)
rb_yield(REFER_OBJECT(cCvAvgComp::rb_class(), cvGetSeqElem(seq, i), storage_val));
}
}
catch (cv::Exception& e) {
raise_cverror(e);
}
return result;
}
/*
* call-seq:
* CvSeq.new(<i>type[,storage]</i>)
*
* Return a new CvSeq. <i>type</i> should be following classes.
*
* * CvIndex
* * CvPoint
*/
VALUE
rb_initialize(int argc, VALUE *argv, VALUE self)
{
VALUE klass, storage_value;
CvMemStorage *storage;
if (rb_scan_args(argc, argv, "11", &klass, &storage_value) > 1) {
storage_value = CHECK_CVMEMSTORAGE(storage_value);
storage = CVMEMSTORAGE(storage_value);
}
else
storage = cvCreateMemStorage(0);
if(!rb_obj_is_kind_of(klass, rb_cClass))
rb_raise(rb_eTypeError, "argument 1 (sequence-block class) should be %s.", rb_class2name(rb_cClass));
int type = 0, size = 0;
if (klass == cCvIndex::rb_class()) {
type = CV_SEQ_ELTYPE_INDEX;
size = sizeof(CvIndex);
}
else if (klass == cCvPoint::rb_class()) {
type = CV_SEQ_ELTYPE_POINT;
size = sizeof(CvPoint);
}
else if (klass == cCvPoint2D32f::rb_class()) {
type = CV_SEQ_ELTYPE_POINT;
size = sizeof(CvPoint2D32f);
}
else if (klass == cCvPoint3D32f::rb_class()) {
type = CV_SEQ_ELTYPE_POINT3D;
size = sizeof(CvPoint3D32f);
}
// todo: more various class will be support.
if (!size)
rb_raise(rb_eTypeError, "unsupport %s class for sequence-block.", rb_class2name(klass));
CvSeq* seq = cvCreateSeq(type, sizeof(CvSeq), size, storage);
DATA_PTR(self) = seq;
resist_class_information_of_sequence(seq, klass);
return self;
}
VALUE
rb_initialize(int argc, VALUE *argv, VALUE self)
{
CvMemStorage *storage;
VALUE storage_value;
if (rb_scan_args(argc, argv, "01", &storage_value) > 0) {
storage_value = CHECK_CVMEMSTORAGE(storage_value);
storage = CVMEMSTORAGE(storage_value);
}
else
storage = rb_cvCreateMemStorage(0);
try {
DATA_PTR(self) = (CvChain*)cvCreateSeq(CV_SEQ_ELTYPE_CODE, sizeof(CvChain),
sizeof(char), storage);
}
catch (cv::Exception& e) {
raise_cverror(e);
}
return self;
}
/*
* call-seq:
* detect_objects_with_pruning(image[,scale_factor = 1.1, min_neighbor = 3, min_size = CvSize.new(0,0)]) -> cvseq(include CvAvgComp object)
* detect_objects_with_pruning(image[,scale_factor = 1.1, min_neighbor = 3, min_size = CvSize.new(0,0)]){|cmp| ... } -> cvseq(include CvAvgComp object)
*
* Almost same to #detect_objects (Return detected objects).
*
* Before scanning to image, Canny edge detector to reject some image regions
* that contain too few or too much edges, and thus can not contain the searched object.
*
* note: The particular threshold values are tuned for face detection.
* And in this case the pruning speeds up the processing.
*/
VALUE
rb_detect_objects_with_pruning(int argc, VALUE *argv, VALUE self)
{
VALUE image, storage, scale_factor, min_neighbors, min_size, result;
rb_scan_args(argc, argv, "14", &image, &storage, &scale_factor, &min_neighbors, &min_size);
if (!rb_obj_is_kind_of(image, cCvMat::rb_class()))
rb_raise(rb_eTypeError, "argument 1(target-image) should be %s.", rb_class2name(cCvMat::rb_class()));
double scale = IF_DBL(scale_factor, 1.1);
if (!(scale > 1.0))
rb_raise(rb_eArgError, "argument 2 (scale factor) must > 1.0.");
storage = CHECK_CVMEMSTORAGE(storage);
CvSeq *seq = cvHaarDetectObjects(CVMAT(image), CVHAARCLASSIFIERCASCADE(self), CVMEMSTORAGE(storage),
scale, IF_INT(min_neighbors, 3), CV_HAAR_DO_CANNY_PRUNING, NIL_P(min_size) ? cvSize(0,0) : VALUE_TO_CVSIZE(min_size));
result = cCvSeq::new_sequence(cCvSeq::rb_class(), seq, cCvAvgComp::rb_class(), storage);
if (rb_block_given_p()) {
for(int i = 0; i < seq->total; i++)
rb_yield(REFER_OBJECT(cCvAvgComp::rb_class(), cvGetSeqElem(seq, i), storage));
}
return result;
}
/*
* Constructor
* @overload new(storage = nil)
* @param [CvMemStorage] storage Sequence location
* @return [CvContour] self
* @opencv_func cvCreateSeq
*/
VALUE
rb_initialize(int argc, VALUE *argv, VALUE self)
{
VALUE storage;
rb_scan_args(argc, argv, "01", &storage);
if (NIL_P(storage))
storage = cCvMemStorage::new_object(0);
else
storage = CHECK_CVMEMSTORAGE(storage);
try {
DATA_PTR(self) = (CvContour*)cvCreateSeq(CV_SEQ_ELTYPE_POINT, sizeof(CvContour),
sizeof(CvPoint), CVMEMSTORAGE(storage));
}
catch (cv::Exception& e) {
raise_cverror(e);
}
cCvSeq::register_elem_class(self, cCvPoint::rb_class());
register_root_object(CVSEQ(self), storage);
return self;
}
