opencv3.0

I am following this question: How can I sort contours from left to right and top to bottom? to sort contours from left-to-right and top-to-bottom. However, my contours are found using this (OpenCV 3): im2, contours, hierarchy = cv2.findContours(threshold,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) and they are formatted like this: array([[[ 1, 1]], [[ 1, 36]], [[63, 36]], [[64, 35]], [[88, 35]], [[89, 34]], [[94, 34]], [[94, 1]]], dtype=int32)] When I run the code max_width = max(contours, key=lambda r: r[0] + r[2])[0] max_height = max(contours, key=lambda r: r[3])[3] nearest = max_height * 1.4

I have OpenCV 3.0, and I have compiled & installed it with the opencv_contrib module so that's not a problem. Unfortunately the examples from previous versions do not work with the current one, and so although this question has already been asked more than once I would like a more current example that I can actually work with. Even the official examples don't work in this version (feature detection works but not other feature examples) and they use SURF anyway. So, how do I use OpenCV SIFT on C++? I want to grab the keypoints in two images and match them, similar to this example , but even

The documentation does not seem to explain what the expected range of the input is for an HSV->BGR conversion. Here is some example code where I am trying to get back the original BGR value after converting it to HSV. Does anyone know which scaling is expected? #include <iostream> #include <opencv2/opencv.hpp> cv::Vec3b HSVtoBGR(const cv::Vec3f& hsv) { cv::Vec3f hsvAdjusted = hsv; // If we use this directly, the output is (0,0,1) which is very wrong //hsvAdjusted[0] *= 360.; // If we do this to bring all of the values into the range (0,1), the output is (0,1,0), which is also very wrong // If

I am creating a face recognition system using Python and OpenCV on these versions: Python 3.6.2 :: Anaconda custom (64-bit) Anaconda 4.3.23 OpenCV 3.3.0 When I try to train the face recognizer: face_recognizer = cv2.face.createLBPHFaceRecognizer() I get this error: AttributeError: module 'cv2' has no attribute 'face' Update: I've tried to do this: pip install opencv_python‑3.3.0+contrib‑cp36‑cp36m‑win_amd64.whl Also: conda install -c menpo opencv3=3.3.0 And I still have the error. The Menpo project does not have an installer for OpenCV 3.3. The Menpo project is up to 3.1 on macOS and Windows,

I'm upgrading from opencv 2.4.11 to 3.0.0 I have used cv::vector in my code <br> but now I get the error vector in not a member of 'cv' I will start using std::vector instead <br> however I can't find anywhere was it removed or just moved to another header file? In OpenCV prior to 3.0, you can see at the beginning of core.hpp that OpenCV is using std::vector internally: #ifndef __OPENCV_CORE_HPP__ #define __OPENCV_CORE_HPP__ ... #include <vector> ... /*! \namespace cv Namespace where all the C++ OpenCV functionality resides */ namespace cv { ... using std::vector; ... So you can access std:

I have issue using OpenCV 3 tracking module for tracking. It behaves same, either I use interface class (cv::Tracker) or class with implementation (like cv::TrackerMedianFlow or cv::TrackerMIL, etc). Sample is a bit modified sample from OpenCV sample folder After correct creation Ptr<Tracker> tracker = Tracker::create( tracker_algorithm ); if ( tracker == NULL ) { std::cout << "***Error in the instantiation of the tracker...***\n"; return -1; } initialization works just fine if ( !tracker->init( frame, boundingBox ) ) { std::cout << "***Could not initialize tracker...***\n"; return -1; }