CODEWITHSUNDEEP
androidperformanceopencvshapesdetection
Giancarlo
Giancarlo

Reputation: 11

Opencv findContours in Android seems much slower than findContours in Python. Do you have any suggestion to improve algorithm speed?

it's the first time for me that I ask help here. I will try to be as precise as possible in my question.

I am trying to develop a shape detection app for Android.

I first identified the algorithm which works for my case playing with Python. Basically for each frame I do this:

 hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
 mask = cv2.inRange(hsv, lower_color, upper_color)
 contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

 for cnt in contours:
   #here I filter my results

by this algorithm I am able to run the analysis realtime on videos having a frame rate of 120fps.

So I tryied to implement the same algorithm on Android Studio, doing the following for each Frame:

Imgproc.cvtColor(frameInput, tempFrame, Imgproc.COLOR_BGR2HSV);
Core.inRange(tempFrame,lowColorRoi,highColorRoi,tempFrame);

List<MatOfPoint> contours1 = new ArrayList<MatOfPoint>();
Imgproc.findContours(tempFrame /*.clone()*/, contours1, new Mat(), Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE);

 for(MatOfPoint c : contours1){
     //here I filter my results
}

and I see that only the findContour function takes 5-600ms to be performed at each iteration (I noticed that it takes also more using tempFrame.clone()), allowing more or less to run the analysis with only 2fps.

This speed is not acceptable at all of course. Do you have any suggestion about how to improve this speed? 30-40fps would be already a good target for me. I will really appreciate any help from you all. Many thanks in advance.

Upvotes: 1

Views: 931

Answers (1)

MaRib
MaRib

Reputation: 31

I would suggest trying to do your shape analysis on a lower resolution version of the image, if that is acceptable. I often see directly proportional timing with number of pixels of the image and the number of channels of the image - so if you can halve the width and height it could be a 4 times performance improvement. If that works, likely the first thing to do is a resize, then all subsequent calls have a smaller burden.

Next, be careful using OpenCV in Java/Kotlin because there is a definite cost to marshalling over the JNI interface. You could write the majority of your code in native C++, and then make just a single call across JNI to a C++ function that handles all of the shape analysis at once.

Upvotes: 1

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