opencv3.0

I am currently working on simple lane detection and I have some trouble finding the range/input values for yellow colored lane lines. def color_filter(image): #convert to HLS to mask based on HLS hls = cv2.cvtColor(image, cv2.COLOR_BGR2HLS) lower = np.array([0,190,0]) upper = np.array([255,255,255]) yellower = np.array([40,70,60]) #NOT SURE WHAT TO PUT yelupper = np.array([50,90,65]) #NOT SURE WHAT TO PUT yellowmask = cv2.inRange(hls, yellower, yelupper) whitemask = cv2.inRange(hls, lower, upper) mask = cv2.bitwise_or(yellowmask, whitemask) masked = cv2.bitwise_and(image, image, mask = mask)

I would like to create project with enabled Visual Studio memory leak detector ( Memory Leak Detector ) It always worked fine and I could easily find memory leaks by running bunch of tests on my application and then checking the report. But after statically linking OpenCV 3.0 to my project I got some false positives. For instance the most frustrating error comes from StereoBMImpl::compute method and call: ocl::useOpenCL() After debugging I found the source of the "leak": TLSData<CoreTLSData>& getCoreTlsData() { static TLSData<CoreTLSData> *value = new TLSData<CoreTLSData>(); return *value; }

I want to distort and rectified my stereo images. For which I used Opencv 3.3 in Python 2.7. Code I used is : import cv2 import numpy as np cameraMatrixL = np.load('mtx_left.npy') distCoeffsL = np.load('dist_left.npy') cameraMatrixR = np.load('mtx_right.npy') distCoeffsR = np.load('dist_right.npy') R = np.load('R.npy') T = np.load('T.npy') imgleft = cv2.imread('D:\python\camera calibration and 3d const\left\left60.png',0) imgright = cv2.imread('D:\python\camera calibration and 3d const\Right/right60.png',0) R1,R2,P1,P2,Q,validPixROI1, validPixROI2 = cv2.stereoRectify(cameraMatrixL,distCoeffsL

I searched a lot for finding the threshold values for the below mention methods. methods = ['cv2.TM_CCOEFF', 'cv2.TM_CCOEFF_NORMED', 'cv2.TM_CCORR', 'cv2.TM_CCORR_NORMED', 'cv2.TM_SQDIFF', cv2.TM_SQDIFF_NORMED'] I also tried to figure them out by myself but I could only find thresholds for 3 methods which have max value of 1.0. The other methods values were in range of 10^5. I would like to know the bounds of these methods. Can somebody point me in the right direction. My agenda is to loop through all the methods for template matching and get the best outcome.I went through the documentation

I develop the code in VS2015 + OpenCV3.0 in Windows 7 64bit. This is a demo code that I want have a try. And I have tried many demo but I was coming across the same problem: object of abstract class type "cv::BackgroundSubtractorMOG2" is not allowed. all the methods are pure virtual function. The demo code is: using namespace cv; using namespace std; int main() { VideoCapture video("1.avi"); Mat frame, mask, thresholdImage, output; //video>>frame; Ptr<BackgroundSubtractor> pMOG2; pMOG2 = new BackgroundSubtractorMOG2(); BackgroundSubtractorMOG2 bgSubtractor(20, 16, true); while (true) { video >

I'm trying to create a video from a sequence of images and display it in a browser but from some weird reason no matter what codec or file format I use I get the following error: No video with supported format and mime type found Here is my code: ready_images = [] import cv2 for img in videos['Images']: image = cv2.imread(img.fileName) ready_images.append(image) fourcc = cv2.VideoWriter_fourcc(*'MP4V') video_name = videos['Images'][0].gifLocationPath + "//" + videos['Name'] frame = cv2.imread(videos['Images'][0].fileName) height, width, layers = frame.shape video_name = video_name[:-4]+".mp4"