简介:
本文就opencv中的几个常用函数:imread、cvLoadImage、waitKey、imshow,进行简单的源码分析,并对新、老版本进行比较。
实验平台:
xp + vs2010 + opencv2.4.10
案列:
用Opencv读取并显示图片,一般来说有①、②两种方法,下面就①②进行源码分析。
#include <iostream>
#include <opencv2/highgui/highgui.hpp>
using namespace cv;
using namespace std;
int main()
{
//①老版
IplImage *pic = cvLoadImage("lena.jpg", 1);
cvShowImage("load", pic);
cvWaitKey(0);
//②新版
Mat img = imread("lena.jpg");
imshow("read", img);
waitKey(0);
return 0;
}
源码分析:
1、图像的读取
cvLoadImage、imread
方法①中的cvLoadImage:
cvLoadImage函数原型如下,其中参数filename为待读取的图片名(可含路径),iscolor是读取方式,它是一个枚举参数(默认是读取的是彩色):
CVAPI(IplImage*) cvLoadImage( const char* filename, int iscolor CV_DEFAULT(CV_LOAD_IMAGE_COLOR));
枚举如下:enum
{
/* 8bit, color or not 8位*/
CV_LOAD_IMAGE_UNCHANGED =-1,
/* 8bit, gray 8位灰度*/
CV_LOAD_IMAGE_GRAYSCALE =0,
/* ?, color 彩色*/
CV_LOAD_IMAGE_COLOR =1,
/* any depth, ? 任意深度*/
CV_LOAD_IMAGE_ANYDEPTH =2,
/* ?, any color 任意颜色*/
CV_LOAD_IMAGE_ANYCOLOR =4
};
进一步查看cvLoadImage源码(如下),发现实际上是调用的imread_函数,imread_中有个参数是LOAD_IMAGE,这是因为图片是IplImage的(若是Mat类的,则应是LOAD_MAT,下面会提到)。
CV_IMPL IplImage*
cvLoadImage( const char* filename, int iscolor )
{
return (IplImage*)cv::imread_(filename, iscolor, cv::LOAD_IMAGE );
}
方法②中的imread:
imread函数原型如下,filename是文件名,flags默认为1,其含义同上iscolor枚举。
CV_EXPORTS_W Mat imread( const string& filename, int flags=1 );
进一步查看imread源码,发现实际上调用的还是imread_函数,现在这里的参数就是LOAD_MAT了。Mat imread( const string& filename, int flags )
{
Mat img;//定义一个Mat类,用于装载图片
imread_( filename, flags, LOAD_MAT, &img );//读图像
return img;
}
显然,不论是cvLoadImage还是imread,都是调用的imread_函数。那么我们就由此及彼,由表及里,去粗取精,去伪存真的去剖析其源码。
imread_函数源码(在源文件loadsave.cpp中):static void*
imread_( const string& filename, int flags, int hdrtype, Mat* mat=0 )
{
IplImage* image = 0;//定义一个IplImage结构体
CvMat *matrix = 0;//定义一个CvMat结构体
Mat temp, *data = &temp;//data中保存的是temp的地址,temp是一个Mat类容器
ImageDecoder decoder = findDecoder(filename);//①译码器
if( decoder.empty() )
return 0;
decoder->setSource(filename);
if( !decoder->readHeader() )//②读取信息头
return 0;
CvSize size;
size.width = decoder->width();
size.height = decoder->height();
int type = decoder->type();
if( flags != -1 )//③
{
if( (flags & CV_LOAD_IMAGE_ANYDEPTH) == 0 )
type = CV_MAKETYPE(CV_8U, CV_MAT_CN(type));
if( (flags & CV_LOAD_IMAGE_COLOR) != 0 ||
((flags & CV_LOAD_IMAGE_ANYCOLOR) != 0 && CV_MAT_CN(type) > 1) )
type = CV_MAKETYPE(CV_MAT_DEPTH(type), 3);//彩色
else
type = CV_MAKETYPE(CV_MAT_DEPTH(type), 1);//灰度
}
if( hdrtype == LOAD_CVMAT || hdrtype == LOAD_MAT )//④
{
if( hdrtype == LOAD_CVMAT )
{
matrix = cvCreateMat( size.height, size.width, type );
temp = cvarrToMat(matrix);//temp与matrix同址
}
else
{
mat->create( size.height, size.width, type );
data = mat;//data与mat同址
}
}
else
{
image = cvCreateImage( size, cvIplDepth(type), CV_MAT_CN(type) );
temp = cvarrToMat(image);//temp与image同址
}
if( !decoder->readData( *data ))//⑤
{
cvReleaseImage( &image );
cvReleaseMat( &matrix );
if( mat )
mat->release();
return 0;
}
//根据指针及同址关系,可知matrix、image、mat数据(若存在)与data数据一致
return hdrtype == LOAD_CVMAT ? (void*)matrix :
hdrtype == LOAD_IMAGE ? (void*)image : (void*)mat;
}
在imread_中,有几个地方值得注意①②③④⑤,下面一一分析:
①findDecoder(),这是一个很重要的重载函数,它的目的是:解析图片信息,并确定应该使用的译码器(.jpg格式使用Jpeg译码器),其内部源码如下:
static ImageCodecInitializer codecs;
static ImageDecoder findDecoder( const string& filename )
{
size_t i, maxlen = 0;
for( i = 0; i < codecs.decoders.size(); i++ )
{
size_t len = codecs.decoders[i]->signatureLength();
maxlen = std::max(maxlen, len);
}
FILE* f= fopen( filename.c_str(), "rb" );//读取二进制文件
if( !f )
return ImageDecoder();
string signature(maxlen, ' ');
maxlen = fread( &signature[0], 1, maxlen, f );
fclose(f);
signature = signature.substr(0, maxlen);
for( i = 0; i < codecs.decoders.size(); i++ )
{
if( codecs.decoders[i]->checkSignature(signature) )
return codecs.decoders[i]->newDecoder();
}
return ImageDecoder();
}
译码器的定义如下:
struct ImageCodecInitializer
{
ImageCodecInitializer()
{
decoders.push_back( new BmpDecoder );//Bmp译码器
encoders.push_back( new BmpEncoder );//Bmp编码器
#ifdef HAVE_JPEG
decoders.push_back( new JpegDecoder );//Jpeg
encoders.push_back( new JpegEncoder );
#endif
decoders.push_back( new SunRasterDecoder );
encoders.push_back( new SunRasterEncoder );
decoders.push_back( new PxMDecoder );PxM
encoders.push_back( new PxMEncoder );
#ifdef HAVE_TIFF
decoders.push_back( new TiffDecoder );//Tiff
#endif
encoders.push_back( new TiffEncoder );
#ifdef HAVE_PNG
decoders.push_back( new PngDecoder );//Png
encoders.push_back( new PngEncoder );
#endif
#ifdef HAVE_JASPER
decoders.push_back( new Jpeg2KDecoder );
encoders.push_back( new Jpeg2KEncoder );
#endif
#ifdef HAVE_OPENEXR
decoders.push_back( new ExrDecoder );
encoders.push_back( new ExrEncoder );
#endif
// because it is a generic image I/O API, supporting many formats,
// it should be last in the list.
#ifdef HAVE_IMAGEIO
decoders.push_back( new ImageIODecoder );
encoders.push_back( new ImageIOEncoder );
#endif
}
vector<ImageDecoder> decoders;
vector<ImageEncoder> encoders;
};
②decoder->readHeader(),它是属于decoder类方法,它的作用是:根据上述译码器类型(即Jpeg译码器),对图片进行解压,并读取图片信息头。其源码如下:
bool JpegDecoder::readHeader()//Jpeg格式译码器
{
bool result = false;
close();
JpegState* state = new JpegState;
m_state = state;
state->cinfo.err = jpeg_std_error(&state->jerr.pub);
state->jerr.pub.error_exit = error_exit;
if( setjmp( state->jerr.setjmp_buffer ) == 0 )
{
jpeg_create_decompress( &state->cinfo );
if( !m_buf.empty() )
{
jpeg_buffer_src(&state->cinfo, &state->source);
state->source.pub.next_input_byte = m_buf.data;
state->source.pub.bytes_in_buffer = m_buf.cols*m_buf.rows*m_buf.elemSize();
}
else
{
m_f = fopen( m_filename.c_str(), "rb" );
if( m_f )
jpeg_stdio_src( &state->cinfo, m_f );
}
if (state->cinfo.src != 0)
{
jpeg_read_header( &state->cinfo, TRUE );
m_width = state->cinfo.image_width;//宽
m_height = state->cinfo.image_height;//高
m_type = state->cinfo.num_components > 1 ? CV_8UC3 : CV_8UC1;
result = true;
}
}
if( !result )
close();
return result;
}
③flags是用于判断读取图片的方式。④hdrtype的值不是LOAD_CVMAT就是LOAD_MAT或者LOAD_IMAGE,因为IplImage、cvMat都是由cvArr派生出来的,所以hdrtype不论是LOAD_CVMAT还是LOAD_IMAGE,最终都会cvarrToMat()转换成为Mat类型。
⑤decoder->readData(),它属于decoder类方法,是用来解析图片数据的,它将解析出的数据存放于传入的参数中,其源码如下。在源码的一些函数中,用到Jpeg解压并涉及到了DCT变换的代码,到了底层是汇编代码,在memcpy.asm中(此处我们只看目的,不究过程):
bool JpegDecoder::readData( Mat& img )
{
bool result = false;
int step = (int)img.step;
bool color = img.channels() > 1;
if( m_state && m_width && m_height )
{
jpeg_decompress_struct* cinfo = &((JpegState*)m_state)->cinfo;
JpegErrorMgr* jerr = &((JpegState*)m_state)->jerr;
JSAMPARRAY buffer = 0;
if( setjmp( jerr->setjmp_buffer ) == 0 )
{
/* check if this is a mjpeg image format */
if ( cinfo->ac_huff_tbl_ptrs[0] == NULL &&
cinfo->ac_huff_tbl_ptrs[1] == NULL &&
cinfo->dc_huff_tbl_ptrs[0] == NULL &&
cinfo->dc_huff_tbl_ptrs[1] == NULL )
{
/* yes, this is a mjpeg image format, so load the correct
huffman table */
my_jpeg_load_dht( cinfo,
my_jpeg_odml_dht,
cinfo->ac_huff_tbl_ptrs,
cinfo->dc_huff_tbl_ptrs );
}
if( color )
{
if( cinfo->num_components != 4 )
{
cinfo->out_color_space = JCS_RGB;
cinfo->out_color_components = 3;
}
else
{
cinfo->out_color_space = JCS_CMYK;
cinfo->out_color_components = 4;
}
}
else
{
if( cinfo->num_components != 4 )
{
cinfo->out_color_space = JCS_GRAYSCALE;
cinfo->out_color_components = 1;
}
else
{
cinfo->out_color_space = JCS_CMYK;
cinfo->out_color_components = 4;
}
}
jpeg_start_decompress( cinfo );
buffer = (*cinfo->mem->alloc_sarray)((j_common_ptr)cinfo,
JPOOL_IMAGE, m_width*4, 1 );
uchar* data = img.data;
for( ; m_height--; data += step )
{
jpeg_read_scanlines( cinfo, buffer, 1 );
if( color )
{
if( cinfo->out_color_components == 3 )
icvCvt_RGB2BGR_8u_C3R( buffer[0], 0, data, 0, cvSize(m_width,1) );
else
icvCvt_CMYK2BGR_8u_C4C3R( buffer[0], 0, data, 0, cvSize(m_width,1) );
}
else
{
if( cinfo->out_color_components == 1 )
memcpy( data, buffer[0], m_width );
else
icvCvt_CMYK2Gray_8u_C4C1R( buffer[0], 0, data, 0, cvSize(m_width,1) );
}
}
result = true;
jpeg_finish_decompress( cinfo );
}
}
close();
return result;
}
imread_经过5个关键步骤,将读取到的图片信息头,以及图片数据以Mat类型返回(若是cvLoadImage则会被强制转换成IplImage类型)。
总结下来,方法①②,读取图像的过程都是:输入filename—>解析图片—>确定译码器—>译码函数进行信息、数据的读取—>存放于Mat容器—>返回。
2、图像的显示:
cvShowImage、imshow
方法①中的cvShowImage:
其函数原型如下,其中参数name是窗体名,image是图片。
CVAPI(void) cvShowImage( const char* name, const CvArr* image );
方法②中的imshow:
其寒素原型如下,参数意义同上。
CV_EXPORTS_W void imshow(const string& winname, InputArray mat);
进入到imshow源码中,可以看到注释出,调用的依然是cvShowImage函数(高版本的opencv是支持opengl的,所以调试时直接到第一个注释调用cvShowImage)。void cv::imshow( const string& winname, InputArray _img )
{
const Size size = _img.size();
#ifndef HAVE_OPENGL
CV_Assert(size.width>0 && size.height>0);
{
Mat img = _img.getMat();
CvMat c_img = img;
cvShowImage(winname.c_str(), &c_img);//
}
#else
const double useGl = getWindowProperty(winname, WND_PROP_OPENGL);
CV_Assert(size.width>0 && size.height>0);
if (useGl <= 0)
{
Mat img = _img.getMat();
CvMat c_img = img;
cvShowImage(winname.c_str(), &c_img);//
}
else
{
const double autoSize = getWindowProperty(winname, WND_PROP_AUTOSIZE);
if (autoSize > 0)
{
resizeWindow(winname, size.width, size.height);
}
setOpenGlContext(winname);
if (_img.kind() == _InputArray::OPENGL_TEXTURE)
{
cv::ogl::Texture2D& tex = wndTexs[winname];
tex = _img.getOGlTexture2D();
tex.setAutoRelease(false);
setOpenGlDrawCallback(winname, glDrawTextureCallback, &tex);
}
else
{
cv::ogl::Texture2D& tex = ownWndTexs[winname];
if (_img.kind() == _InputArray::GPU_MAT)
{
cv::ogl::Buffer& buf = ownWndBufs[winname];
buf.copyFrom(_img);
buf.setAutoRelease(false);
tex.copyFrom(buf);
tex.setAutoRelease(false);
}
else
{
tex.copyFrom(_img);
}
tex.setAutoRelease(false);
setOpenGlDrawCallback(winname, glDrawTextureCallback, &tex);
}
updateWindow(winname);
}
#endif
}
显然,接下来应该查看cvShowImage源码,但是,好多东西都没看懂
CV_IMPL void
cvShowImage( const char* name, const CvArr* arr )
{
CV_FUNCNAME( "cvShowImage" );
__BEGIN__;
CvWindow* window;
SIZE size = { 0, 0 };
int channels = 0;
void* dst_ptr = 0;
const int channels0 = 3;
int origin = 0;
CvMat stub, dst, *image;
bool changed_size = false; // philipg
if( !name )//必须要有窗体名字,否则报错!
CV_ERROR( CV_StsNullPtr, "NULL name" );
window = icvFindWindowByName(name);//通过名字查找窗体句柄
if(!window)//如果没有找到,则自动创建一个同名窗体,这就是为什么在显示图片之前可以不用cvNamedWindow创建窗体的原因。
{
cvNamedWindow(name, CV_WINDOW_AUTOSIZE);
window = icvFindWindowByName(name);
}
if( !window || !arr )
EXIT; // keep silence here.
if( CV_IS_IMAGE_HDR( arr ))
origin = ((IplImage*)arr)->origin;
CV_CALL( image = cvGetMat( arr, &stub ));
#ifdef HAVE_OPENGL
if (window->useGl)
{
cv::Mat im(image);
cv::imshow(name, im);
return;
}
#endif
if (window->image)//窗体图像为空
// if there is something wrong with these system calls, we cannot display image...
if (icvGetBitmapData( window, &size, &channels, &dst_ptr ))
return;
if( size.cx != image->width || size.cy != image->height || channels != channels0 )//如果图片的大小与窗体大小不一致
{
changed_size = true;//将更改窗体标志设置为ture
uchar buffer[sizeof(BITMAPINFO) + 255*sizeof(RGBQUAD)];
BITMAPINFO* binfo = (BITMAPINFO*)buffer;
DeleteObject( SelectObject( window->dc, window->image ));
window->image = 0;
size.cx = image->width;//更改属性
size.cy = image->height;
channels = channels0;
FillBitmapInfo( binfo, size.cx, size.cy, channels*8, 1 );//该函数内有设置调色板的信息
window->image = SelectObject( window->dc, CreateDIBSection(window->dc, binfo,
DIB_RGB_COLORS, &dst_ptr, 0, 0));
}
cvInitMatHeader( &dst, size.cy, size.cx, CV_8UC3,//初始化Mat信息头
dst_ptr, (size.cx * channels + 3) & -4 );
cvConvertImage( image, &dst, origin == 0 ? CV_CVTIMG_FLIP : 0 );
// ony resize window if needed
if (changed_size)//若窗体大小改变,则更新窗体
icvUpdateWindowPos(window);
InvalidateRect(window->hwnd, 0, 0);
// philipg: this is not needed and just slows things down
// UpdateWindow(window->hwnd);
__END__;
}
3、等待函数
cvWaitKey、waitKey(时间单位:ms)
方法①中的cvWaitKey:
cvWaitKey函数原型如下,默认参数为0:
/* wait for key event infinitely (delay<=0) or for "delay" milliseconds */
CVAPI(int) cvWaitKey(int delay CV_DEFAULT(0));
方法②中的waitKey:
waitKey函数原型如下,默认参数为0:
CV_EXPORTS_W int waitKey(int delay = 0);
waitKey()源码如下:
int cv::waitKey(int delay)
{
return cvWaitKey(delay);
}
那么将重心转移到cvWaitKey来看,其源码如下,它用到了windows编程中的事件及消息机制,不太懂:CV_IMPL int
cvWaitKey( int delay )
{
int time0 = GetTickCount();
for(;;)//死循环
{
CvWindow* window;
MSG message;
int is_processed = 0;
if( (delay > 0 && abs((int)(GetTickCount() - time0)) >= delay) || hg_windows == 0 )
return -1;
if( delay <= 0 )
GetMessage(&message, 0, 0, 0);
else if( PeekMessage(&message, 0, 0, 0, PM_REMOVE) == FALSE )
{
Sleep(1);//延时1ms
continue;
}
for( window = hg_windows; window != 0 && is_processed == 0; window = window->next )
{
if( window->hwnd == message.hwnd || window->frame == message.hwnd )
{
is_processed = 1;
switch(message.message)
{
case WM_DESTROY:
case WM_CHAR:
DispatchMessage(&message);//推送消息事件
return (int)message.wParam;//返回触发按键的ASIIC码
case WM_SYSKEYDOWN:
if( message.wParam == VK_F10 )
{
is_processed = 1;
return (int)(message.wParam << 16);
}
break;
case WM_KEYDOWN:
TranslateMessage(&message);//破译消息
if( (message.wParam >= VK_F1 && message.wParam <= VK_F24) ||
message.wParam == VK_HOME || message.wParam == VK_END ||
message.wParam == VK_UP || message.wParam == VK_DOWN ||
message.wParam == VK_LEFT || message.wParam == VK_RIGHT ||
message.wParam == VK_INSERT || message.wParam == VK_DELETE ||
message.wParam == VK_PRIOR || message.wParam == VK_NEXT )
{
DispatchMessage(&message);
is_processed = 1;
return (int)(message.wParam << 16);
}
default:
DispatchMessage(&message);
is_processed = 1;
break;
}
}
}
if( !is_processed )
{
TranslateMessage(&message);
DispatchMessage(&message);
}
}
}