Ok I have a strange problem. I'll try to describe it as best as I can.
I've learned my app to detect a car when looking on it from the side
Imgproc.cvtColor(aInputFrame, grayscaleImage, Imgproc.COLOR_RGBA2RGB);
MatOfRect objects = new MatOfRect();
// Use the classifier to detect cars
if (cascadeClassifier != null) {
cascadeClassifier.detectMultiScale(grayscaleImage, objects, 1.1, 1,
2, new Size(absoluteObjectSize, absoluteObjectSize),
new Size());
}
for (int i = 0; i < dataArray.length; i++) {
Core.rectangle(aInputFrame, dataArray[i].tl(), dataArray[i].br(),
new Scalar(0, 255, 0, 255), 3);
mRenderer.setCameraPosition(-5, 5, 60f);
}
Now, this code works nice. I mean that i detects cars and it marks them with green rectangle. The problem is that the marked rectangle jumps like hell. I mean even when the phone is hold still the rectangle jumps from left to right to middle. There is never one still rectangle. I hope I've described the problem properly. I would like to stabilizy the marking cause I want to draw an overlay based on it and I can't make it to jump like this
See(1) the parameters for detectMultiScale and it expects
image of type CV_8U. You will need to convert to gray scale image
with COLOR_RGBA2GRAY instead of COLOR_RGBA2RGB
In detectMultiScale, increase the number of neighbours parameter to avoid false positives.
Suggestion: If input is a video stream, don't run
detectMultiScale on every frame. It is slow even if you use LBP
cascades. Try detection in one frame, followed by tracking techniques.
Related
Not sure if this is the right way to ask, but please help. I have an image of a dented car. I have to process it and highlight the dents and return the number of dents. I was able to do it reasonably well with the following result:
The matlab code is:
img2=rgb2gray(i1);
imshow(img2);
img3=imtophat(img2,strel('disk',15));
img4=imadjust(img3);
layer=img4(:,:,1);
img5=layer>100 & layer<250;
img6=imfill(img5,'holes');
img7=bwareaopen(img6,5);
[L,ans]=bwlabeln(img7);
imshow(img7);
I=imread(i1);
Ians=CarDentIdentification(I);
However, when I try to do this using opencv, I get this:
With the following code:
Imgproc.cvtColor(source, middle, Imgproc.COLOR_RGB2GRAY);
Imgproc.equalizeHist(middle, middle);
Imgproc.threshold(middle, middle, 150, 255, Imgproc.THRESH_OTSU);
Please tell me how can I obtain better results in opencv, and also how to count the dents? I tried findcontour() but it gives a very large number. I tried on other images as well, but I'm not getting proper results.
Please help.
So you basically from the MATLAB site, imtophat does - Top-hat filtering computes the morphological opening of the image (using imopen) and then subtracts the result from the original image.
You could do this in OpenCV with the following steps:
Step 1: Get the disk structuring element
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (15, 15))
Step 2: Compute opening of the image and then subtract the result from the original image
tophat = cv2.morphologyEx(v, cv2.MORPH_TOPHAT, kernel)
This gives following result -
Step 3 - Now you could just manually threshold it or use Otsu -
ret, thresh = cv2.threshold(tophat, 17, 255, 0)
which gives you the following image -
Since the OP wants the code in Java, here is the probable code in Java:
private Mat topHat(Mat image)
{
Mat element = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(15, 15), new Point (0, 0));
Mat dst = new Mat;
Imgproc.morphologyEx(image, dst, Imgproc.MORPH_TOPHAT, element, new Point(0, 0));
return dst;
}
Make sure you do this on a gray scale image (CvType.8UC1) and then you can threshold suitably.
I started by reading in this Mat.
Then I converted it to Greyscale and applied Imgproc.canny() to it, getting the following mask.
Then I used Imgproc.findContours() to find the contours, Imgproc.drawContours(), and Core.putText() to label the contours with numbers:
Then I did Rect boundingRect = Imgproc.boundingRect(contours.get(0));
Mat submatrix = new Mat();
submatrix = originalMat.submat(boundingRect); to get following submatrix:
So far so good. The Problem starts hereafter:
NOW I NEEDED A MASK OF THE submatrix. So I decided to use Imgproc.drawContours() to get the mask:
Mat mask = new Mat(submatrix.rows(), submatrix.cols(), CvType.CV_8UC1);
List<MatOfPoint> contourList = new ArrayList<>();
contourList.add(contours.get(0));
Imgproc.drawContours(mask, contourList, 0, new Scalar(255), -1);
I got the following mask:
WHAT I WAS EXPECTING was a filled (in white color) diamond shape on black background.
WHy am I getting this unexpected result?
EDIT:
When I replaced Mat mask = new Mat(submatrix.rows(),
submatrix.cols(), CvType.CV_8UC1); by Mat mask =
Mat.zeros(submatrix.rows(), submatrix.cols(), CvType.CV_8UC1);,
the last mask with white colored garbage was replaced by an empty
black mask withOUT any white color on it. I got the following submat
and mask:
I was getting the first contour in the list of contours (named
contours) by contours.get(0), and using this first contour to
calculate Imgproc.boundingRect() as well as in
contourList.add(contours.get(0)); later (where contourList is
the list of just one contour which will be used in the last
drawContours()).
Then I went ahead to change contours.get(0) to
contours.get(1) in Imgproc.boundingRect() as well as in contourList.add(); (just before Imgproc.drawContours()). That
resulted in this submat and mask:
Then I changed back to contours.get(0) in
Imgproc.boundingRect(); and let
contourList.add(contours.get(1)); be there. Got the following
submat and mask:
NOW I am completely Unable to Understand what is happening here.
I am not sure how this is handle in JAVA (I usually use OpenCV in c++ or python), but there is an error in your code...
The contours list will have a list of list of points. This points will refer to the original image. So, this mean that if the figure one is in lets say, x=300, y= 300, width= 100, height=100 then when you get your submatrix it will try to draw those points in a smaller image... so when it tries to draw point (300,300) in a 100 x 100 image, it will simply fail... probably throws an error or simply doesn't draw anything...
A solution for this is, do a for loop and substract to each point of the contour the initial point of the bounding rect (in my example (300,300)).
As, why there is some garbage drawn... well you never initialize the matrix. Not sure in JAVA, but in c++ you have to set them to 0.
I think it should be something like this:
Mat mask = new Mat(submatrix.rows(), submatrix.cols(), CvType.CV_8UC1, new Scalar(0));
I hope this helps :)
EDIT
I think I did not explain myself clearly before.
Your contours are an array of points (x,y). These are the coordinates of the points that represent each contour in the original image. This image has a size, and your submatrix has a smaller size. The points are outside of this small image boundaries....
you should do something like this to fix it:
for (int j = 0; j < contours[0].length; j++) {
contours[0][j].x -= boundingrect.x;
contours[0][j].y -= boundingrect.y;
}
and then you can draw the contours, since they will be in boundaries of the submat.
I think in java it is also possible to subtract the opencv points directly:
for (int j = 0; j < contours[0].length; j++) {
contours[0][j] -= boundingrect.tl();
}
but in this case I am not sure, since I have tried it in c++ only
boundingrect.tl() -> gives you the top left point of the rect
Hello I'm tring to recognize a car using cascade classifier, android and opencv library. My problem is that my phone is marking almoust everything as a car.
I've created my code based on:
https://www.youtube.com/watch?v=WEzm7L5zoZE
and face detection sample. My app behave very strange cause marking looks like random. I even don't know if marking car is correct or maybe it is just some random behaviour. At the moment it is even marking my keyboard as a car. I'm not sure what can I improve. I don't see any progress between training it up to 5 or 14 stages
I've trained my file up to 14 stages
my code looks like this:
#Override
public Mat onCameraFrame(Mat aInputFrame) {
// return FrameAnalyzer.analyzeFrame(aInputFrame);
// Create a grayscale image
Imgproc.cvtColor(aInputFrame, grayscaleImage, Imgproc.COLOR_RGBA2RGB);
MatOfRect objects = new MatOfRect();
// Use the classifier to detect faces
if (cascadeClassifier != null) {
cascadeClassifier.detectMultiScale(grayscaleImage, objects, 1.1, 1,
2, new Size(absoluteObjectSize, absoluteObjectSize),
new Size());
}
Rect[] dataArray = objects.toArray();
for (int i = 0; i < dataArray.length; i++) {
Core.rectangle(aInputFrame, dataArray[i].tl(), dataArray[i].br(),
new Scalar(0, 255, 0, 255), 3);
}
return aInputFrame;
}
Try changing the below.
Using COLOR_RGBA2RGB with cvtColor as in sample code will not give a gray scale image. Try RGBA2GRAY
Increase the number of neighbors in detectMultiScale. Now it's 2. More neighbors means more confidence in result.
Hope there are enough samples to train with. A quick search and reading through books, gives an impression like thousands of images are needed for training. For e.g. around 10000 images are used for OCR haar training. For face training, 3000 to 5000 samples are used.
More importantly, decide if you really want to go with haar training for identifying a car. There could be better methods of vehicle identification. For e.g. for a moving vehicle we could use optical flow based techniques.
I am trying to detect the number of blobs for example placed on a surface. What i have tried so far:
Converted image to grayscale
Applied threshold to the image
3, Obtained the edges
Drawn the edges using the mat (the image below)
I am using opencv for android in my case, and i need help in order to find the number of objects in the image. Could anyone please help me. I have tried filling the image using the code below but it doesnot help
for(int ii=0;ii<dst.rows();ii++) {
for(int j=0;j<dst.cols();j++) {
double checker = dst.get(ii, j)[0];
if(checker == 255) {
Imgproc.floodFill(dst, matMask,
new Point(j,ii), new Scalar(255),
null,new Scalar(255), new Scalar(255), 8);
}
}
}
EDIT:
The captured image on which processing has to be done:
the background might look like this
!
Or another possibility
Thanking you
I am trying to build an app that tracks touchpoints and draws circles at those points using Flash Builder. The following works perfectly, but after a while, it begins to lag and the touch will be well ahead of the drawn circles. Is there a way of drawing the circles that does not produce lag as more and more of them are added?
In declarations, I have:
<fx:Component className="Circle">
<s:Ellipse>
<s:stroke>
<s:SolidColorStroke alpha="0"/>
</s:stroke>
</s:Ellipse>
</fx:Component>
And this is the drawing function:
var c:Circle = new Circle();
c.x = somex;
c.y = somey;
c.fill = new SolidColor(somecolorint);
c.height = somesize;
c.width = somesize;
c.alpha = 1;
addElement(c);
c = null;
Try taking a look at doing a fullscreen Bitmap created with a BitmapData class. As the touch points are moved, update the bitmap data at the coordinates where the touch occured. Modifying and blitting a screen-sized bitmap is extremely fast and will probably work great for what you're trying to do.
Another performance trade off often done is to make a series of lines instead of continuous circles. You create a new line segment only when a certain distance has been traveled, this lets you limit the number of nodes in the segment thereby keeping performance high.