opencv3.0

I'm trying to get OpenCV 3.0.0 native to run in my Android Studio 1.5 with Gradle experimental 0.4.0. I can already use the Java components of OpenCV and the regular NDK functions. But as soon as I try to use the namespace cv in my native code I get the following exception (it is shortened. The complete exception was too long): app\src\main\jniLibs\armeabi\libopencv_core.a(matrix.cpp.o):matrix.cpp:function std::vector<unsigned char, std::allocator<unsigned char> >::resize(unsigned int, unsigned char): error: undefined reference to 'std::__throw_length_error(char const*)' app\src\main\jniLibs

Can a sample implementation code or a pointer be provided for implementing LSD with opencv 3.0 and python? HoughLines and HoughLinesP are not giving desired results in python and want to test LSD in python but am not getting anywhere. I have tried to do the following: LSD=cv2.createLineSegmentDetector(0) lines_std=LSD.detect(mixChl) LSD.drawSegments(mask,lines_std) However when I draw lines on the mask I get an error which is: LSD.drawSegments(mask,lines_std) TypeError: lines is not a numerical tuple Can someone please help me with this? Thanks in advance. You can use cv2.drawSegments function

How can I merge images like below into a single image using OpenCV (there can be any number of them both horizontally and vertically)? Is there any built-in solution to do it? Additional pieces: Well, it seems that I finished the puzzle: Main steps: Compare each pair of images ( puzzle pieces ) to know the relative position ( findRelativePositions and getPosition ). Build a map knowing the relative positions of the pieces ( buildPuzzle and builfForPiece ) Create the final collage putting each image at the correct position (final part of buildPuzzle ). Comparison between pieces A and B in step

I am working on dress feature identification using opencv. As a first step, I need to segment t-shirt by removing face and hands from the image. Any suggestion is appreciated. I suggest the following approach: Use Adrian Rosebrock's skin detection algorithm for detecting the skin (thank you for Rosa Gronchi for his comment). Use region growing algorithm on the variance map. The initial seed can be calculated by using stage 1(see the attached code for more information). code: %stage 1: skin detection - Adrian Rosebrock solution im = imread(<path to input image>); hsb = rgb2hsv(im)*255; skinMask

I have drawn a contour around extreme points. Inside polygon figure I have others points. How to check if they are inside contour? You can use the cv2.pointPolygonTest() function available in OpenCV. For example: dist = cv2.pointPolygonTest(cnt,(50,50),True) In this example we are checking whether the coordinate (50, 50) is present withing the contour cnt dist returns one of the following three: Positive value if the point is inside the contour Negative value if the point is outside the contour Zero if the point is on the contour Within the function cv2.pointPolygonTest() the third parameter