如何使用 OpenCV 从垫子裁剪任意形状？
How to crop an arbitrary shape from mat using OpenCV?
我正在使用 CvVideoCamera 的输出到 UIImageView，然后计算轮廓并将最大轮廓绘制到覆盖的 UIImageView 上。我正在使用矩形 ROI（感兴趣区域）来裁剪图像，以便计算出的轮廓完全在裁剪区域内。现在我怎样才能对可以在 iPad?
上用手势绘制的任何形状做同样的事情
使用 OpenCV 3.1
@interface FCCameraViewController() <CvVideoCameraDelegate>
@property (nonatomic, strong) FCVideoCamera *camera;
@property (nonatomic, assign) UIImageOrientation imageOrientation;
@end
@implementation FCCameraViewController
- (void)setStarted:(BOOL)started {
_started = started;
if (started) {
[self.camera start];
} else {
[self.camera stop];
}
}
- (void)viewWillLayoutSubviews
{
[super viewWillLayoutSubviews];
self.imageView.frame = self.view.frame;
NSArray *layers = [[self.imageView layer] sublayers];
for (CALayer *layer in layers) {
layer.frame = self.view.frame;
}
}
- (void)viewDidLoad
{
//Camera
self.camera = [[FCVideoCamera alloc] initWithParentView: self.imageView];
self.camera.defaultAVCaptureDevicePosition = AVCaptureDevicePositionBack;
self.camera.defaultAVCaptureSessionPreset = AVCaptureSessionPreset1280x720;
self.camera.defaultAVCaptureVideoOrientation = AVCaptureVideoOrientationPortrait;
self.camera.defaultFPS = 30;
self.camera.useAVCaptureVideoPreviewLayer = NO;
self.camera.grayscaleMode = NO;
self.camera.delegate = self;
self.isAutoEdgeMode = NO;
self.imageOrientation = UIImageOrientationUp;
}
- (void)setIsAutoEdgeMode:(BOOL)isAutoEdgeMode
{
_isAutoEdgeMode = isAutoEdgeMode;
if (!self.started && self.imageView.image != nil) {
cv::Mat mat = [self CVMatFromUIImage:self.imageView.image];
self.imageOrientation = self.imageView.image.imageOrientation;
[self processImage:mat];
}
}
#pragma mark - CvVideoCameraDelegate
cv::Mat original, src_gray, drawing_mat, cropped_area;
int thresh = 192;//100;
int max_thresh = 255;
cv::RNG rng(12345);
- (void)processImage:(cv::Mat &)image
{
if (!self.isAutoEdgeMode) {
return;
}
original = image.clone();
cropped_area = [self crop:image];
cv::cvtColor(cropped_area, src_gray, cv::COLOR_BGR2GRAY);
cv::blur(src_gray, src_gray, cv::Size(3,3));
cv::Mat threshold_output;
std::vector<std::vector<cv::Point> > contours;
std::vector<cv::Vec4i> hierarchy;
/// Detect edges using Threshold
cv::threshold( src_gray, threshold_output, thresh, 255, cv::THRESH_BINARY );
/// Find contours
cv::findContours(threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, cv::Point(0, 0) );
// approximate the convex hulls
std::vector<std::vector<cv::Point>> hull(contours.size());
for( size_t i = 0; i < contours.size(); i++ ) {
convexHull( cv::Mat(contours[i]), hull[i], false );
}
// Approximate contours to polygons + get bounding rects and circles
std::vector<std::vector<cv::Point> > contours_poly( contours.size() );
std::vector<cv::Rect> boundRect( contours.size() );
std::vector<cv::Point2f>center( contours.size() );
std::vector<float>radius( contours.size() );
std::vector<cv::Point> *largestContourPoly = nil;
std::vector<cv::Point> *secondLargest = nil;
double largestArea = 0;
for(int i = 0; i < contours.size(); i++ ) {
std::vector<cv::Point> a_contour = contours[i];
double contourArea = cv::contourArea(a_contour);
double size = contourArea;
// Calculate the polygon based on the contour
cv::approxPolyDP(cv::Mat(contours[i]), contours_poly[i], 1, true );
// Get random color
cv::Scalar color(rand() & 255, rand() & 255, rand() & 255);
cv::Vec3b otherColor(color[2], color[0], color[1]);
// DEBUG HELPER: Draw all polygons
cv::polylines(cropped_area, contours_poly[i], true, color, FCLineWidth);
// DEBUG HELPER: Draw convex hull
cv::drawContours(cropped_area, hull, (int)i, RED, 2, 8, std::vector<cv::Vec4i>(), 0, cv::Point() );
// Save the largest polygon
if (size > largestArea) {
largestArea = contourArea;
secondLargest = largestContourPoly;
largestContourPoly = &contours_poly[i];
}
}
// Draw the largest polygon on the non-gray scale
if (largestContourPoly != NULL) {
cv::polylines(cropped_area, *largestContourPoly, true, GREEN, FCLineWidth);
// Show on ImageView if using a still image
if (!self.started) {
// use with imageOrientation in mind
UIImage *convertedImage = [self UIImageFromCVMat:cropped_area];
self.imageView.image = convertedImage;
}
// Add back to original image
UIImage *testCrop = [self UIImageFromCVMat:cropped_area];
cropped_area.copyTo(image(cv::Rect(300, 300, cropped_area.cols, cropped_area.rows)));
// Show drawing on other image view
cv::Mat matContour(image.size(), CV_8UC1);
matContour = cv::Scalar(255,255,255,0); // make background white
cv::polylines(matContour, *largestContourPoly, true, GREEN, FCLineWidth);
// TODO: will need to offset the matContour drawing by the croped_area's offset
UIImage *autoEdge = [self UIImageFromCVMat:matContour];
self.autoEdgeImage = [autoEdge replaceColor:[UIColor colorWithRed:1.0f green:1.0f blue:1.0f alpha:1.0] inImage:autoEdge withTolerance:10];
}
}
#pragma mark - Helpers
- (cv::Mat)crop:(cv::Mat)uncropped {
// Setup a rectangle to define your region of interest
cv::Rect myROI(300, 300, 300, 300);
// Crop the full image to that image contained by the rectangle myROI
// Note that this doesn't copy the data
cv::Mat croppedRef = uncropped(myROI);
// Copy the data into new matrix
cv::Mat cropped;
croppedRef.copyTo(cropped);
UIImage *croppedImage = [self UIImageFromCVMat:cropped];
return cropped;
}
-(cv::Mat)CVMatFromUIImage:(UIImage *)image
{
CGColorSpaceRef colorSpace = CGImageGetColorSpace(image.CGImage);
CGFloat cols = image.size.width;
CGFloat rows = image.size.height;
if (image.imageOrientation == UIImageOrientationUp
|| image.imageOrientation == UIImageOrientationDown) {
cols = image.size.height;
rows = image.size.width;
}
cv::Mat cvMat(rows, cols, CV_8UC4); // 8 bits per component, 4 channels
CGContextRef contextRef = CGBitmapContextCreate(cvMat.data, // Pointer to backing data
cols, // Width of bitmap
rows, // Height of bitmap
8, // Bits per component
cvMat.step[0], // Bytes per row
colorSpace, // Colorspace
kCGImageAlphaNoneSkipLast |
kCGBitmapByteOrderDefault); // Bitmap info flags
CGContextDrawImage(contextRef, CGRectMake(0, 0, cols, rows), image.CGImage);
CGContextRelease(contextRef);
return cvMat;
}
- (UIImage *)UIImageFromCVMat:(cv::Mat)cvMat
{
NSData *data = [NSData dataWithBytes:cvMat.data length:cvMat.elemSize()*cvMat.total()];
CGColorSpaceRef colorSpace;
if (cvMat.elemSize() == 1) {
colorSpace = CGColorSpaceCreateDeviceGray();
} else {
colorSpace = CGColorSpaceCreateDeviceRGB();
}
CGDataProviderRef provider = CGDataProviderCreateWithCFData((__bridge CFDataRef)data);
// Creating CGImage from cv::Mat
CGImageRef imageRef = CGImageCreate(cvMat.cols, //width
cvMat.rows, //height
8, //bits per component
8 * cvMat.elemSize(), //bits per pixel
cvMat.step[0], //bytesPerRow
colorSpace, //colorspace
kCGImageAlphaNone|kCGBitmapByteOrderDefault,// bitmap info
provider, //CGDataProviderRef
NULL, //decode
false, //should interpolate
kCGRenderingIntentDefault //intent
);
// Getting UIImage from CGImage
UIImage *finalImage = [UIImage imageWithCGImage:imageRef scale:1 orientation:self.imageOrientation];
CGImageRelease(imageRef);
CGDataProviderRelease(provider);
CGColorSpaceRelease(colorSpace);
return finalImage;
}
@end
我最终将 converting UIBezierPath 用于 CGPoint 数组。使用这些点，我使用 cv::drawContours 绘制区域并创建遮罩。最后，我 return 感兴趣的区域，现在我用它来计算我原来 post.
中的最大轮廓区域
- (cv::Mat)cropArbitrary:(cv::Mat)uncropped {
cv::Mat dst(uncropped.rows, uncropped.cols, uncropped.type(), cv::Scalar(0));
int new_w=0;
int new_h=0;
if(uncropped.cols>dst.cols)
new_w=dst.cols;
else
new_w=uncropped.cols;
if(uncropped.rows>dst.rows)
new_h=dst.rows;
else
new_h=uncropped.rows;
cv::Rect rectROI(0,0,uncropped.cols,uncropped.rows);
cv::Mat mask(uncropped.rows, uncropped.cols, CV_8UC1, cv::Scalar(0));
std::vector< std::vector<cv::Point> > co_ordinates;
co_ordinates.push_back(std::vector<cv::Point>());
for (int i = 0; i < self.points.count; i++) {
NSValue *value = self.points[i];
CGPoint point = value.CGPointValue;
cv::Point newPoint(point.x, point.y);
co_ordinates[0].push_back(newPoint);
}
cv::drawContours( mask,co_ordinates,0, cv::Scalar(255),CV_FILLED, 8 );
cv::Mat srcROI = uncropped(rectROI);
cv::Mat dstROI = dst(rectROI);
cv::Mat dst1;
cv::Mat dst2;
srcROI.copyTo(dst1,mask);
bitwise_not(mask,mask);
dstROI.copyTo(dst2,mask);
dstROI.setTo(0);
dstROI=dst1+dst2;
return dst1;
}
我正在使用 CvVideoCamera 的输出到 UIImageView，然后计算轮廓并将最大轮廓绘制到覆盖的 UIImageView 上。我正在使用矩形 ROI（感兴趣区域）来裁剪图像，以便计算出的轮廓完全在裁剪区域内。现在我怎样才能对可以在 iPad?
上用手势绘制的任何形状做同样的事情使用 OpenCV 3.1
@interface FCCameraViewController() <CvVideoCameraDelegate>
@property (nonatomic, strong) FCVideoCamera *camera;
@property (nonatomic, assign) UIImageOrientation imageOrientation;
@end
@implementation FCCameraViewController
- (void)setStarted:(BOOL)started {
_started = started;
if (started) {
[self.camera start];
} else {
[self.camera stop];
}
}
- (void)viewWillLayoutSubviews
{
[super viewWillLayoutSubviews];
self.imageView.frame = self.view.frame;
NSArray *layers = [[self.imageView layer] sublayers];
for (CALayer *layer in layers) {
layer.frame = self.view.frame;
}
}
- (void)viewDidLoad
{
//Camera
self.camera = [[FCVideoCamera alloc] initWithParentView: self.imageView];
self.camera.defaultAVCaptureDevicePosition = AVCaptureDevicePositionBack;
self.camera.defaultAVCaptureSessionPreset = AVCaptureSessionPreset1280x720;
self.camera.defaultAVCaptureVideoOrientation = AVCaptureVideoOrientationPortrait;
self.camera.defaultFPS = 30;
self.camera.useAVCaptureVideoPreviewLayer = NO;
self.camera.grayscaleMode = NO;
self.camera.delegate = self;
self.isAutoEdgeMode = NO;
self.imageOrientation = UIImageOrientationUp;
}
- (void)setIsAutoEdgeMode:(BOOL)isAutoEdgeMode
{
_isAutoEdgeMode = isAutoEdgeMode;
if (!self.started && self.imageView.image != nil) {
cv::Mat mat = [self CVMatFromUIImage:self.imageView.image];
self.imageOrientation = self.imageView.image.imageOrientation;
[self processImage:mat];
}
}
#pragma mark - CvVideoCameraDelegate
cv::Mat original, src_gray, drawing_mat, cropped_area;
int thresh = 192;//100;
int max_thresh = 255;
cv::RNG rng(12345);
- (void)processImage:(cv::Mat &)image
{
if (!self.isAutoEdgeMode) {
return;
}
original = image.clone();
cropped_area = [self crop:image];
cv::cvtColor(cropped_area, src_gray, cv::COLOR_BGR2GRAY);
cv::blur(src_gray, src_gray, cv::Size(3,3));
cv::Mat threshold_output;
std::vector<std::vector<cv::Point> > contours;
std::vector<cv::Vec4i> hierarchy;
/// Detect edges using Threshold
cv::threshold( src_gray, threshold_output, thresh, 255, cv::THRESH_BINARY );
/// Find contours
cv::findContours(threshold_output, contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, cv::Point(0, 0) );
// approximate the convex hulls
std::vector<std::vector<cv::Point>> hull(contours.size());
for( size_t i = 0; i < contours.size(); i++ ) {
convexHull( cv::Mat(contours[i]), hull[i], false );
}
// Approximate contours to polygons + get bounding rects and circles
std::vector<std::vector<cv::Point> > contours_poly( contours.size() );
std::vector<cv::Rect> boundRect( contours.size() );
std::vector<cv::Point2f>center( contours.size() );
std::vector<float>radius( contours.size() );
std::vector<cv::Point> *largestContourPoly = nil;
std::vector<cv::Point> *secondLargest = nil;
double largestArea = 0;
for(int i = 0; i < contours.size(); i++ ) {
std::vector<cv::Point> a_contour = contours[i];
double contourArea = cv::contourArea(a_contour);
double size = contourArea;
// Calculate the polygon based on the contour
cv::approxPolyDP(cv::Mat(contours[i]), contours_poly[i], 1, true );
// Get random color
cv::Scalar color(rand() & 255, rand() & 255, rand() & 255);
cv::Vec3b otherColor(color[2], color[0], color[1]);
// DEBUG HELPER: Draw all polygons
cv::polylines(cropped_area, contours_poly[i], true, color, FCLineWidth);
// DEBUG HELPER: Draw convex hull
cv::drawContours(cropped_area, hull, (int)i, RED, 2, 8, std::vector<cv::Vec4i>(), 0, cv::Point() );
// Save the largest polygon
if (size > largestArea) {
largestArea = contourArea;
secondLargest = largestContourPoly;
largestContourPoly = &contours_poly[i];
}
}
// Draw the largest polygon on the non-gray scale
if (largestContourPoly != NULL) {
cv::polylines(cropped_area, *largestContourPoly, true, GREEN, FCLineWidth);
// Show on ImageView if using a still image
if (!self.started) {
// use with imageOrientation in mind
UIImage *convertedImage = [self UIImageFromCVMat:cropped_area];
self.imageView.image = convertedImage;
}
// Add back to original image
UIImage *testCrop = [self UIImageFromCVMat:cropped_area];
cropped_area.copyTo(image(cv::Rect(300, 300, cropped_area.cols, cropped_area.rows)));
// Show drawing on other image view
cv::Mat matContour(image.size(), CV_8UC1);
matContour = cv::Scalar(255,255,255,0); // make background white
cv::polylines(matContour, *largestContourPoly, true, GREEN, FCLineWidth);
// TODO: will need to offset the matContour drawing by the croped_area's offset
UIImage *autoEdge = [self UIImageFromCVMat:matContour];
self.autoEdgeImage = [autoEdge replaceColor:[UIColor colorWithRed:1.0f green:1.0f blue:1.0f alpha:1.0] inImage:autoEdge withTolerance:10];
}
}
#pragma mark - Helpers
- (cv::Mat)crop:(cv::Mat)uncropped {
// Setup a rectangle to define your region of interest
cv::Rect myROI(300, 300, 300, 300);
// Crop the full image to that image contained by the rectangle myROI
// Note that this doesn't copy the data
cv::Mat croppedRef = uncropped(myROI);
// Copy the data into new matrix
cv::Mat cropped;
croppedRef.copyTo(cropped);
UIImage *croppedImage = [self UIImageFromCVMat:cropped];
return cropped;
}
-(cv::Mat)CVMatFromUIImage:(UIImage *)image
{
CGColorSpaceRef colorSpace = CGImageGetColorSpace(image.CGImage);
CGFloat cols = image.size.width;
CGFloat rows = image.size.height;
if (image.imageOrientation == UIImageOrientationUp
|| image.imageOrientation == UIImageOrientationDown) {
cols = image.size.height;
rows = image.size.width;
}
cv::Mat cvMat(rows, cols, CV_8UC4); // 8 bits per component, 4 channels
CGContextRef contextRef = CGBitmapContextCreate(cvMat.data, // Pointer to backing data
cols, // Width of bitmap
rows, // Height of bitmap
8, // Bits per component
cvMat.step[0], // Bytes per row
colorSpace, // Colorspace
kCGImageAlphaNoneSkipLast |
kCGBitmapByteOrderDefault); // Bitmap info flags
CGContextDrawImage(contextRef, CGRectMake(0, 0, cols, rows), image.CGImage);
CGContextRelease(contextRef);
return cvMat;
}
- (UIImage *)UIImageFromCVMat:(cv::Mat)cvMat
{
NSData *data = [NSData dataWithBytes:cvMat.data length:cvMat.elemSize()*cvMat.total()];
CGColorSpaceRef colorSpace;
if (cvMat.elemSize() == 1) {
colorSpace = CGColorSpaceCreateDeviceGray();
} else {
colorSpace = CGColorSpaceCreateDeviceRGB();
}
CGDataProviderRef provider = CGDataProviderCreateWithCFData((__bridge CFDataRef)data);
// Creating CGImage from cv::Mat
CGImageRef imageRef = CGImageCreate(cvMat.cols, //width
cvMat.rows, //height
8, //bits per component
8 * cvMat.elemSize(), //bits per pixel
cvMat.step[0], //bytesPerRow
colorSpace, //colorspace
kCGImageAlphaNone|kCGBitmapByteOrderDefault,// bitmap info
provider, //CGDataProviderRef
NULL, //decode
false, //should interpolate
kCGRenderingIntentDefault //intent
);
// Getting UIImage from CGImage
UIImage *finalImage = [UIImage imageWithCGImage:imageRef scale:1 orientation:self.imageOrientation];
CGImageRelease(imageRef);
CGDataProviderRelease(provider);
CGColorSpaceRelease(colorSpace);
return finalImage;
}
@end
我最终将 converting UIBezierPath 用于 CGPoint 数组。使用这些点，我使用 cv::drawContours 绘制区域并创建遮罩。最后，我 return 感兴趣的区域，现在我用它来计算我原来 post.
中的最大轮廓区域- (cv::Mat)cropArbitrary:(cv::Mat)uncropped {
cv::Mat dst(uncropped.rows, uncropped.cols, uncropped.type(), cv::Scalar(0));
int new_w=0;
int new_h=0;
if(uncropped.cols>dst.cols)
new_w=dst.cols;
else
new_w=uncropped.cols;
if(uncropped.rows>dst.rows)
new_h=dst.rows;
else
new_h=uncropped.rows;
cv::Rect rectROI(0,0,uncropped.cols,uncropped.rows);
cv::Mat mask(uncropped.rows, uncropped.cols, CV_8UC1, cv::Scalar(0));
std::vector< std::vector<cv::Point> > co_ordinates;
co_ordinates.push_back(std::vector<cv::Point>());
for (int i = 0; i < self.points.count; i++) {
NSValue *value = self.points[i];
CGPoint point = value.CGPointValue;
cv::Point newPoint(point.x, point.y);
co_ordinates[0].push_back(newPoint);
}
cv::drawContours( mask,co_ordinates,0, cv::Scalar(255),CV_FILLED, 8 );
cv::Mat srcROI = uncropped(rectROI);
cv::Mat dstROI = dst(rectROI);
cv::Mat dst1;
cv::Mat dst2;
srcROI.copyTo(dst1,mask);
bitwise_not(mask,mask);
dstROI.copyTo(dst2,mask);
dstROI.setTo(0);
dstROI=dst1+dst2;
return dst1;
}