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我是一個opencv的新手
要把下面這個程式改成不是一個影片檔的
而是獨兩張圖片
然後比對
但我查了好多資料，還是不會。
所以想請大家幫幫忙
謝謝了
(這是一支別人寫好的demo,from David Stavens )
/* --Sparse Optical Flow Demo Program--
* Written by David Stavens (<!-- e --><a href="mailto:dstavens@robotics.stanford.edu">dstavens@robotics.stanford.edu</a><!-- e -->)
*/
#include <stdio.h>
#include <cv.h>
#include <highgui.h>
#include <math.h>
static const double pi = 3.14159265358979323846;
inline static double square(int a)
{
return a * a;
}
/* This is just an inline that allocates images. I did this to reduce clutter in the
* actual computer vision algorithmic code. Basically it allocates the requested image
* unless that image is already non-NULL. It always leaves a non-NULL image as-is even
* if that image's size, depth, and/or channels are different than the request.
*/
inline static void allocateOnDemand( IplImage **img, CvSize size, int depth, int channels)
{
if ( *img != NULL ) return;
*img = cvCreateImage( size, depth, channels );
if ( *img == NULL )
{
fprintf(stderr, "Error: Couldn't allocate image. Out of memory?\n");
exit(-1);
}
}
int main(void)
{
/* Create an object that decodes the input video stream. */
CvCapture *input_video = cvCaptureFromFile(
"C:\\Documents and Settings\\David Staven\\logo.avi");
if (input_video == NULL)
{
/* Either the video didn't exist OR it uses a codec OpenCV
* doesn't support.
*/
fprintf(stderr, "Error: Can't open video.\n");
return -1;
}
/* This is a hack. If we don't call this first then getting capture
* properties (below) won't work right. This is an OpenCV bug. We
* ignore the return value here. But it's actually a video frame.
*/
cvQueryFrame( input_video );
/* Read the video's frame size out of the AVI. */
CvSize frame_size;
frame_size.height =
(int) cvGetCaptureProperty( input_video, CV_CAP_PROP_FRAME_HEIGHT );
frame_size.width =
(int) cvGetCaptureProperty( input_video, CV_CAP_PROP_FRAME_WIDTH );
/* Determine the number of frames in the AVI. */
long number_of_frames;
/* Go to the end of the AVI (ie: the fraction is "1") */
cvSetCaptureProperty( input_video, CV_CAP_PROP_POS_AVI_RATIO, 1. );
/* Now that we're at the end, read the AVI position in frames */
number_of_frames = (int) cvGetCaptureProperty( input_video, CV_CAP_PROP_POS_FRAMES );
/* Return to the beginning */
cvSetCaptureProperty( input_video, CV_CAP_PROP_POS_FRAMES, 0. );
/* Create three windows called "Frame N", "Frame N+1", and "Optical Flow"
* for visualizing the output. Have those windows automatically change their
* size to match the output.
*/
cvNamedWindow("Optical Flow", CV_WINDOW_AUTOSIZE);
long current_frame = 0;
while(true)
{
static IplImage *frame = NULL, *frame1 = NULL, *frame1_1C = NULL, *frame2_1C =
NULL, *eig_image = NULL, *temp_image = NULL, *pyramid1 = NULL, *pyramid2 = NULL;
/* Go to the frame we want. Important if multiple frames are queried in
* the loop which they of course are for optical flow. Note that the very
* first call to this is actually not needed. (Because the correct position
* is set outsite the for() loop.)
*/
cvSetCaptureProperty( input_video, CV_CAP_PROP_POS_FRAMES, current_frame );
/* Get the next frame of the video.
* IMPORTANT! cvQueryFrame() always returns a pointer to the _same_
* memory location. So successive calls:
* frame1 = cvQueryFrame();
* frame2 = cvQueryFrame();
* frame3 = cvQueryFrame();
* will result in (frame1 == frame2 && frame2 == frame3) being true.
* The solution is to make a copy of the cvQueryFrame() output.
*/
frame = cvQueryFrame( input_video );
if (frame == NULL)
{
/* Why did we get a NULL frame? We shouldn't be at the end. */
fprintf(stderr, "Error: Hmm. The end came sooner than we thought.\n");
return -1;
}
/* Allocate another image if not already allocated.
* Image has ONE challenge of color (ie: monochrome) with 8-bit "color" depth.
* This is the image format OpenCV algorithms actually operate on (mostly).
*/
allocateOnDemand( &frame1_1C, frame_size, IPL_DEPTH_8U, 1 );
/* Convert whatever the AVI image format is into OpenCV's preferred format.
* AND flip the image vertically. Flip is a shameless hack. OpenCV reads
* in AVIs upside-down by default. (No comment  )
*/
cvConvertImage(frame, frame1_1C, CV_CVTIMG_FLIP);
/* We'll make a full color backup of this frame so that we can draw on it.
* (It's not the best idea to draw on the static memory space of cvQueryFrame().)
*/
allocateOnDemand( &frame1, frame_size, IPL_DEPTH_8U, 3 );
cvConvertImage(frame, frame1, CV_CVTIMG_FLIP);
/* Get the second frame of video. Sample principles as the first. */
frame = cvQueryFrame( input_video );
if (frame == NULL)
{
fprintf(stderr, "Error: Hmm. The end came sooner than we thought.\n");
return -1;
}
allocateOnDemand( &frame2_1C, frame_size, IPL_DEPTH_8U, 1 );
cvConvertImage(frame, frame2_1C, CV_CVTIMG_FLIP);
/* Shi and Tomasi Feature Tracking! */
/* Preparation: Allocate the necessary storage. */
allocateOnDemand( &eig_image, frame_size, IPL_DEPTH_32F, 1 );
allocateOnDemand( &temp_image, frame_size, IPL_DEPTH_32F, 1 );
/* Preparation: This array will contain the features found in frame 1. */
CvPoint2D32f frame1_features[400];
/* Preparation: BEFORE the function call this variable is the array size
* (or the maximum number of features to find). AFTER the function call
* this variable is the number of features actually found.
*/
int number_of_features;
/* I'm hardcoding this at 400. But you should make this a #define so that you can
* change the number of features you use for an accuracy/speed tradeoff analysis.
*/
number_of_features = 400;
/* Actually run the Shi and Tomasi algorithm!!
* "frame1_1C" is the input image.
* "eig_image" and "temp_image" are just workspace for the algorithm.
* The first ".01" specifies the minimum quality of the features (based on the
eigenvalues).
* The second ".01" specifies the minimum Euclidean distance between features.
* "NULL" means use the entire input image. You could point to a part of the
image.
* WHEN THE ALGORITHM RETURNS:
* "frame1_features" will contain the feature points.
* "number_of_features" will be set to a value <= 400 indicating the number of
feature points found.
*/
cvGoodFeaturesToTrack(frame1_1C, eig_image, temp_image, frame1_features, &
number_of_features, .01, .01, NULL);
/* Pyramidal Lucas Kanade Optical Flow! */
/* This array will contain the locations of the points from frame 1 in frame 2. */
CvPoint2D32f frame2_features[400];
/* The i-th element of this array will be non-zero if and only if the i-th feature
of
* frame 1 was found in frame 2.
*/
char optical_flow_found_feature[400];
/* The i-th element of this array is the error in the optical flow for the i-th
feature
* of frame1 as found in frame 2. If the i-th feature was not found (see the
array above)
* I think the i-th entry in this array is undefined.
*/
float optical_flow_feature_error[400];
/* This is the window size to use to avoid the aperture problem (see slide
"Optical Flow: Overview"). */
CvSize optical_flow_window = cvSize(3,3);
/* This termination criteria tells the algorithm to stop when it has either done
20 iterations or when
* epsilon is better than .3. You can play with these parameters for speed vs.
accuracy but these values
* work pretty well in many situations.
*/
CvTermCriteria optical_flow_termination_criteria
= cvTermCriteria( CV_TERMCRIT_ITER | CV_TERMCRIT_EPS, 20, .3 );
/* This is some workspace for the algorithm.
* (The algorithm actually carves the image into pyramids of different resolutions
.)
*/
allocateOnDemand( &pyramid1, frame_size, IPL_DEPTH_8U, 1 );
allocateOnDemand( &pyramid2, frame_size, IPL_DEPTH_8U, 1 );
/* Actually run Pyramidal Lucas Kanade Optical Flow!!
* "frame1_1C" is the first frame with the known features.
* "frame2_1C" is the second frame where we want to find the first frame's
features.
* "pyramid1" and "pyramid2" are workspace for the algorithm.
* "frame1_features" are the features from the first frame.
* "frame2_features" is the (outputted) locations of those features in the second
frame.
* "number_of_features" is the number of features in the frame1_features array.
* "optical_flow_window" is the size of the window to use to avoid the aperture
problem.
* "5" is the maximum number of pyramids to use. 0 would be just one level.
* "optical_flow_found_feature" is as described above (non-zero iff feature found
by the flow).
* "optical_flow_feature_error" is as described above (error in the flow for this
feature).
* "optical_flow_termination_criteria" is as described above (how long the
algorithm should look).
* "0" means disable enhancements. (For example, the second aray isn't preinitialized
with guesses.)
*/
cvCalcOpticalFlowPyrLK(frame1_1C, frame2_1C, pyramid1, pyramid2, frame1_features,
frame2_features, number_of_features, optical_flow_window, 5,
optical_flow_found_feature, optical_flow_feature_error,
optical_flow_termination_criteria, 0 );
/* For fun (and debugging ), let's draw the flow field. */
for(int i = 0; i < number_of_features; i++)
{
/* If Pyramidal Lucas Kanade didn't really find the feature, skip it. */
if ( optical_flow_found_feature == 0 ) continue;
int line_thickness; line_thickness = 1;
/* CV_RGB(red, green, blue) is the red, green, and blue components
* of the color you want, each out of 255.
*/
CvScalar line_color; line_color = CV_RGB(255,0,0);
/* Let's make the flow field look nice with arrows. */
/* The arrows will be a bit too short for a nice visualization because of the
high framerate
* (ie: there's not much motion between the frames). So let's lengthen them
by a factor of 3.
*/
CvPoint p,q;
p.x = (int) frame1_features.x;
p.y = (int) frame1_features.y;
q.x = (int) frame2_features.x;
q.y = (int) frame2_features.y;
double angle; angle = atan2( (double) p.y - q.y, (double) p.x - q.x );
double hypotenuse; hypotenuse = sqrt( square(p.y - q.y) + square(p.x - q.x) )
;
/* Here we lengthen the arrow by a factor of three. */
q.x = (int) (p.x - 3 * hypotenuse * cos(angle));
q.y = (int) (p.y - 3 * hypotenuse * sin(angle));
/* Now we draw the main line of the arrow. */
/* "frame1" is the frame to draw on.
* "p" is the point where the line begins.
* "q" is the point where the line stops.
* "CV_AA" means antialiased drawing.
* "0" means no fractional bits in the center cooridinate or radius.
*/
cvLine( frame1, p, q, line_color, line_thickness, CV_AA, 0 );
/* Now draw the tips of the arrow. I do some scaling so that the
* tips look proportional to the main line of the arrow.
*/
p.x = (int) (q.x + 9 * cos(angle + pi / 4));
p.y = (int) (q.y + 9 * sin(angle + pi / 4));
cvLine( frame1, p, q, line_color, line_thickness, CV_AA, 0 );
p.x = (int) (q.x + 9 * cos(angle - pi / 4));
p.y = (int) (q.y + 9 * sin(angle - pi / 4));
cvLine( frame1, p, q, line_color, line_thickness, CV_AA, 0 );
}
/* Now display the image we drew on. Recall that "Optical Flow" is the name of
* the window we created above.
*/
cvShowImage("Optical Flow", frame1);
/* And wait for the user to press a key (so the user has time to look at the
image).
* If the argument is 0 then it waits forever otherwise it waits that number of
milliseconds.
* The return value is the key the user pressed.
*/
int key_pressed;
key_pressed = cvWaitKey(0);
/* If the users pushes "b" or "B" go back one frame.
* Otherwise go forward one frame.
*/
if (key_pressed == 'b' || key_pressed == 'B') current_frame--;
else current_frame++;
/* Don't run past the front/end of the AVI. */
if (current_frame < 0) current_frame = 0;
if (current_frame >= number_of_frames - 1) current_frame = number_of_frames - 2;
}
} |
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发表于 2008-7-30 16:20:59
发表于 2008-7-30 17:04:40
楼主