我正在研究Android + OpenCv + JNI，找出图像中最大的轮廓，然后使用透视变换裁剪最大的轮廓。我的问题是在应用转换后我无法将结果Mat转换为位图并返回错误
OpenCV错误：断言失败（src.type（）== CV_8UC1 || src.type（）== CV_8UC3 || src.type（）== CV_8UC4）void Java_org_opencv_android_Utils_nMatToBitmap2（JNIEnv *，jclass， jlong，jobject，jboolean），file /home/reports/ci/slave_desktop/50-SDK/opencv/modules/java/generator/src/cpp/utils.cpp，第98行
这是我的JNI代码：
JNIEXPORT jint JNICALL Java_org_opencv_samples_tutorial3_Sample3Native_FindSquares（
JNIEnv* env, jobject, jlong addrRgba, jint draw, jlong addrDescriptor) {
Mat& image = *(Mat*) addrRgba;
Mat& pMatDesc = *(Mat*) addrDescriptor;
int thresh = 50, N = 4;
int found = 0;
Mat pyr, timg, gray0(image.size(), CV_8U), gray;
// down-scale and upscale the image to filter out the noise
pyrDown(image, pyr, Size(image.cols / 2, image.rows / 2));
pyrUp(pyr, timg, image.size());
vector < vector<Point> > contours;
// find squares in every color plane of the image
for (int c = 1; c < 3; c++) {
int ch[] = { c, 0 };
mixChannels(&timg, 1, &gray0, 1, ch, 1);
// try several threshold levels
for (int l = 0; l < N; l++) {
// hack: use Canny instead of zero threshold level.
// Canny helps to catch squares with gradient shading
if (l == 0) {
// apply Canny. Take the upper threshold from slider
// and set the lower to 0 (which forces edges merging)
Canny(gray0, gray, 0, thresh, 5);
// dilate canny output to remove potential
// holes between edge segments
dilate(gray, gray, Mat(), Point(-1, -1));
} else {
// apply threshold if l!=0:
// tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
gray = gray0 >= (l + 1) * 255 / N;
}
// find contours and store them all as a list
findContours(gray, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
vector<Point> approx;
// test each contour
for (size_t i = 0; i < contours.size(); i++) {
//__android_log_print(ANDROID_LOG_INFO, "Test", "Error:", v);
// approximate contour with accuracy proportional
// to the contour perimeter
approxPolyDP(Mat(contours[i]), approx,
arcLength(Mat(contours[i]), true) * 0.02, true);
// square contours should have 4 vertices after approximation
// relatively large area (to filter out noisy contours)
// and be convex.
// Note: absolute value of an area is used because
// area may be positive or negative - in accordance with the
// contour orientation
if (approx.size() == 4 && fabs(contourArea(Mat(approx))) > 1000
&& isContourConvex(Mat(approx))) {
double maxCosine = 0;
for (int j = 2; j < 5; j++) {
// find the maximum cosine of the angle between joint edges
double cosine = fabs(
angle(approx[j % 4], approx[j - 2],
approx[j - 1]));
maxCosine = MAX(maxCosine, cosine);
}
// if cosines of all angles are small
// (all angles are ~90 degree) then write quandrange
// vertices to resultant sequence
if (maxCosine < 0.3) {
circle(image, approx[0], 5, Scalar(255, 0, 0, 255), 3,
4, 0);
circle(image, approx[1], 5, Scalar(255, 0, 0, 255), 3,
4, 0);
circle(image, approx[2], 5, Scalar(255, 0, 0, 255), 3,
4, 0);
circle(image, approx[3], 5, Scalar(255, 0, 0, 255), 3,
4, 0);
//rectangle(image, approx[0], approx[2], Scalar(0,255,0,255), 5, 4, 0);
//Center of this rectangle
int x = (int) ((approx[0].x + approx[1].x + approx[2].x
+ approx[3].x) / 4.0);
int y = (int) ((approx[0].y + approx[1].y + approx[2].y
+ approx[3].y) / 4.0);
if ((int) draw) {
//outline
line(image, approx[0], approx[1],
Scalar(0, 255, 0, 255), 1, 4, 0);
line(image, approx[1], approx[2],
Scalar(0, 255, 0, 255), 1, 4, 0);
line(image, approx[2], approx[3],
Scalar(0, 255, 0, 255), 1, 4, 0);
line(image, approx[3], approx[0],
Scalar(0, 255, 0, 255), 1, 4, 0);
//center
//circle(image, Point(x,y), 1, Scalar(255,0,0,255));
}
vector<Point2f> src(4);
src[0] = approx[0];
src[1] = approx[1];
src[2] = approx[2];
src[3] = approx[3];
cv::Mat quad = cv::Mat::zeros(300, 220, CV_32FC1 );
// transformed quadrangle
vector<Point2f> quad_pts(4);
quad_pts[0] = Point(0, 0);
quad_pts[1] = Point(quad.cols, 0);
quad_pts[2] = Point(quad.cols, quad.rows);
quad_pts[3] = Point(0, quad.rows);
Mat transmtx = getPerspectiveTransform(src, quad_pts);
warpPerspective(src, quad, transmtx, quad.size());
quad.copyTo(pMatDesc);
found = 1;
jint result = (jint) found;
return result;
}
}
}
}
}
jint result = (jint) found;
return result;
}
在我的java代码中，我将此函数称为
found = FindSquares（mRgba.getNativeObjAddr（），mDraw， descriptor.getNativeObjAddr（））;
最后我试图将最终的Mat转换为Bitmap
Mat final_mat = new Mat(descriptor.height(), descriptor.width(), CvType.CV_8UC4);
descriptor.copyTo(final_mat);
bitmap = Bitmap.createBitmap(final_mat.cols(), final_mat.rows(),
Bitmap.Config.ARGB_8888);
Utils.matToBitmap(final_mat, bitmap);
final_mat通道类型正在变为CV_32FC1。 如何将频道类型转换为CV_8UC4请帮我找出解决方案。
编辑： 我已将finat_mat图像更改为CV_8UC3
descriptor.copyTo(final_mat);
descriptor.convertTo(final_mat, CvType.CV_8UC1);
Imgproc.cvtColor(final_mat,final_mat,Imgproc.COLOR_GRAY2RGB);
但是我得到了空白（黑色）图像？
答案 0 :(得分：1)
经过长时间的研究，我找到了解决方案。这里出现的问题是因为实际图像的转换。我们应该使用实际Mat对象的副本来应用转换（模糊，canny等..），并使用warp透视转换实际的Mat对象。这里我附上参考代码以找出最大的轮廓。
<强> jni_part.cpp：
extern "C" {
double angle(Point pt1, Point pt2, Point pt0);
JNIEXPORT jint Java_info_androidhive_androidcameraapi_CameraMainActivity_findSquare(
JNIEnv*, jobject, jlong addrRgba, jlong addrDescriptor, jint width_,
jint height_);
JNIEXPORT jint Java_info_androidhive_androidcameraapi_CameraMainActivity_findSquare(
JNIEnv*, jobject, jlong addrRgba, jlong addrDescriptor, jint width_,
jint height_) {
Mat& image = *(Mat*) addrRgba;
Mat& imageCropped = *(Mat*) addrDescriptor;
int screen_width = (int) width_;
int screen_height = (int) height_;
Mat newSrc = image.clone();
imageCropped = image.clone();
Mat testImage = image.clone();
// blur will enhance edge detection
Mat blurred(testImage);
medianBlur(testImage, blurred, 9);
Mat gray0(blurred.size(), CV_8U), gray;
vector<vector<Point> > contours;
// find squares in every color plane of the image
cv::vector<cv::vector<cv::Point> > squares;
for (int c = 0; c < 3; c++) {
int ch[] = { c, 0 };
mixChannels(&blurred, 1, &gray0, 1, ch, 1);
// try several threshold levels
const int threshold_level = 2;
for (int l = 0; l < threshold_level; l++) {
// Use Canny instead of zero threshold level!
// Canny helps to catch squares with gradient shading
if (l == 0) {
Canny(gray0, gray, 10, 20, 3); //
// Dilate helps to remove potential holes between edge segments
dilate(gray, gray, Mat(), Point(-1, -1));
} else {
gray = gray0 >= (l + 1) * 255 / threshold_level;
}
// Find contours and store them in a list
findContours(gray, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE);
// Test contours
vector<Point> approx;
if (contours.size() > 0) {
for (size_t i = 0; i < contours.size(); i++) {
// approximate contour with accuracy proportional
// to the contour perimeter
approxPolyDP(Mat(contours[i]), approx,
arcLength(Mat(contours[i]), true) * 0.02, true);
// Note: absolute value of an area is used because
// area may be positive or negative - in accordance with the
// contour orientation
if (approx.size() == 4
&& fabs(contourArea(Mat(approx))) > 1000
&& isContourConvex(Mat(approx))) {
double maxCosine = 0;
for (int j = 2; j < 5; j++) {
double cosine = fabs(
angle(approx[j % 4], approx[j - 2],
approx[j - 1]));
maxCosine = MAX(maxCosine, cosine);
}
if (maxCosine < 0.3) {
squares.push_back(approx);
/*circle(image, approx[0], 5, Scalar(255, 0, 0, 255), 3,
4, 0);
circle(image, approx[1], 5, Scalar(255, 0, 0, 255), 3,
4, 0);
circle(image, approx[2], 5, Scalar(255, 0, 0, 255), 3,
4, 0);
circle(image, approx[3], 5, Scalar(255, 0, 0, 255), 3,
4, 0);
if ((int) draw) {
line(image, approx[0], approx[1],
Scalar(0, 255, 0, 255), 2, 4, 0);
line(image, approx[1], approx[2],
Scalar(0, 255, 0, 255), 2, 4, 0);
line(image, approx[2], approx[3],
Scalar(0, 255, 0, 255), 2, 4, 0);
line(image, approx[3], approx[0],
Scalar(0, 255, 0, 255), 2, 4, 0);
}*/
}
}
}
}
}
}
if (squares.size() > 0) {
int max_width = 0;
int max_height = 0;
int max_square_idx = 0;
cv::vector<cv::Point> biggest_square;
squares.size());
for (size_t i = 0; i < squares.size(); i++) {
cv::Rect structure.
cv::Rect rectangle = boundingRect(cv::Mat(squares[i]));
// Store the index position of the biggest square found
if ((rectangle.width >= max_width)
&& (rectangle.height >= max_height)) {
max_width = rectangle.width;
max_height = rectangle.height;
max_square_idx = i;
}
}
biggest_square = squares[max_square_idx];
vector<Point> _adjustRect;
_adjustRect = squares[max_square_idx];
if (biggest_square.size() == 4) {
vector<Point> sortedPoints;
sortedPoints = squares[max_square_idx];
Point ptbiggest_square = biggest_square[0];
Point ptBottomLeft1 = biggest_square[0];
Point ptBottomRight1 = biggest_square[1];
Point ptTopRight1 = biggest_square[2];
Point ptTopLeft1 = biggest_square[3];
int bl = ptBottomLeft1.x + ptBottomLeft1.y;
int br = ptBottomRight1.x + ptBottomRight1.y;
int tr = ptTopRight1.x + ptTopRight1.y;
int tl = ptTopLeft1.x + ptTopLeft1.y;
int value_array[] = { bl, br, tr, tl };
int max = value_array[0];
int min = value_array[0];
for (int s = 0; s < 4; s++) {
if (value_array[s] > max) {
max = value_array[s];
} else if (value_array[s] < min) {
min = value_array[s];
}
}
int minIndex = 0;
int maxIndex = 0;
int missingIndexOne = 0;
int missingIndexTwo = 0;
for (int i = 0; i < 4; i++) {
if (value_array[i] == min) {
sortedPoints[0] = biggest_square[i];
minIndex = i;
continue;
}
if (value_array[i] == max) {
sortedPoints[2] = biggest_square[i];
maxIndex = i;
continue;
}
missingIndexOne = i;
}
for (int i = 0; i < 4; i++) {
if (missingIndexOne != i && minIndex != i && maxIndex != i) {
missingIndexTwo = i;
}
}
if (biggest_square[missingIndexOne].x
< biggest_square[missingIndexTwo].x) {
//2nd Point Found
sortedPoints[3] = biggest_square[missingIndexOne];
sortedPoints[1] = biggest_square[missingIndexTwo];
} else {
//4rd Point Found
sortedPoints[1] = biggest_square[missingIndexOne];
sortedPoints[3] = biggest_square[missingIndexTwo];
}
_adjustRect[0] = sortedPoints[0];
_adjustRect[1] = sortedPoints[1];
_adjustRect[2] = sortedPoints[2];
_adjustRect[3] = sortedPoints[3];
}
Point ptTopLeft = _adjustRect[0];
Point ptTopRight = _adjustRect[1];
Point ptBottomRight = _adjustRect[2];
Point ptBottomLeft = _adjustRect[3];
float imageScale = fminf((float) screen_width / newSrc.cols,
(float) screen_height / newSrc.rows);
__android_log_print(ANDROID_LOG_INFO, "OpenGLTest", "imageScale %f",
imageScale);
__android_log_print(ANDROID_LOG_INFO, "OpenGLTest", "width_ %d",
screen_width);
float w1 = sqrt(
pow(ptBottomRight.x / imageScale - ptBottomLeft.x / imageScale,
2)
+ pow(
ptBottomRight.x / imageScale
- ptBottomLeft.x / imageScale, 2));
float w2 = sqrt(
pow(ptTopRight.x / imageScale - ptTopLeft.x / imageScale, 2)
+ pow(
ptTopRight.x / imageScale
- ptTopLeft.x / imageScale, 2));
float h1 = sqrt(
pow(ptTopRight.y / imageScale - ptBottomRight.y / imageScale, 2)
+ pow(
ptTopRight.y / imageScale
- ptBottomRight.y / imageScale, 2));
float h2 = sqrt(
pow(ptTopLeft.y / imageScale - ptBottomLeft.y / imageScale, 2)
+ pow(
ptTopLeft.y / imageScale
- ptBottomLeft.y / imageScale, 2));
float maxWidth = (w1 < w2) ? w1 : w2;
float maxHeight = (h1 < h2) ? h1 : h2;
Point2f src[4], quad[4];
src[0].x = ptTopLeft.x;
src[0].y = ptTopLeft.y;
src[1].x = ptTopRight.x;
src[1].y = ptTopRight.y;
src[2].x = ptBottomRight.x;
src[2].y = ptBottomRight.y;
src[3].x = ptBottomLeft.x;
src[3].y = ptBottomLeft.y;
quad[0].x = 0;
quad[0].y = 0;
quad[1].x = maxWidth - 1;
quad[1].y = 0;
quad[2].x = maxWidth - 1;
quad[2].y = maxHeight - 1;
quad[3].x = 0;
quad[3].y = maxHeight - 1;
cv::Mat undistorted = cv::Mat(cvSize(maxWidth, maxHeight), CV_8UC1);
cv::warpPerspective(newSrc, undistorted,
cv::getPerspectiveTransform(src, quad),
cvSize(maxWidth, maxHeight));
imageCropped = undistorted.clone();
}
return 1;
}
double angle(Point pt1, Point pt2, Point pt0) {
double dx1 = pt1.x - pt0.x;
double dy1 = pt1.y - pt0.y;
double dx2 = pt2.x - pt0.x;
double dy2 = pt2.y - pt0.y;
return (dx1 * dx2 + dy1 * dy2)
/ sqrt((dx1 * dx1 + dy1 * dy1) * (dx2 * dx2 + dy2 * dy2) + 1e-10);
}
}
快乐编码!!