OpenCV

问题 I'm currently using the below function to remove noise from two images of size (240x720). I'm currently computing this on my computer but would like to implement this in real time. However on my computer the function results in significant delays to the program. Is there an alternative to removing noise from an image that could work in real time? Gaussian blur perhaps? fastNlMeansDenoising(ipmOfLeftLaneRobust, ipmOfLeftLaneRobust,10,7,21); 回答1: Given a function fastNlMeansDenoising(InputArray

问题 I have an image of a "windows control" lets say a Text-box and I want to get background color of the text written within the text box by finding max color occurred in that picture by pixel color comparison. I searched in google and I found that every one is talking about histogram and also some code is given to find out histogram of an image but no one described the procedure after finding histogram. the code I found on some sites is like // Create a grayscale image Image<Gray, Byte> img =

问题 i am trying to set up Opencv on android using the given tutorials as the base. i havenot been able to control the video size on the screen, i want to enlarge it to full screen. i am using the CameraBridgeViewBase object as the VideoCapture object does not work. does anyone know how to set up the picture to be full screen? relevant code: public class Sample3Native extends Activity implements CvCameraViewListener { private static final String TAG = "OCVSample::Activity"; private Mat mRgba;

问题 I have the following code where the user can press p to pause the video, draw a bounding box around the object to be tracked, and then press Enter (carriage return) to track that object in the video feed: import cv2 import sys major_ver, minor_ver, subminor_ver = cv2.__version__.split('.') if __name__ == '__main__' : # Set up tracker. tracker_types = ['BOOSTING', 'MIL','KCF', 'TLD', 'MEDIANFLOW', 'GOTURN', 'MOSSE', 'CSRT'] tracker_type = tracker_types[1] if int(minor_ver) < 3: tracker = cv2

问题 First of all i have python 3 with the library Gstreamer in it. print(cv2.getBuildInformation()) it shows Gstreamer with YES next to it. Here is the transmitter code using gstreamer in rasperryPi 3: gst-launch-1.0 v4l2src device="/dev/video0" ! video/x-raw,width=320,height=240 ! videoconvert ! x264enc tune=zerolatency ! rtph264pay ! udpsink host='my ip address' port=10000 and i will be using a python code to determine shapes , recognize objects .. etc here is my python code: import numpy as np

问题 I am working on object tracking by camshift algorithm. For the time being I am using the inbuilt opencv code wherein I have trouble dealing with occlusion. hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV) mask = cv2.inRange(hsv, np.array((0., 60., 32.)), np.array((180., 255., 255.))) prob = cv2.calcBackProject([hsv], [0], self.hist, [0, 180], 1) cv2.imshow('prob_0',prob) prob &= mask cv2.imshow('prob',prob) term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 ) track_box,

问题 I am working on object tracking by camshift algorithm. For the time being I am using the inbuilt opencv code wherein I have trouble dealing with occlusion. hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV) mask = cv2.inRange(hsv, np.array((0., 60., 32.)), np.array((180., 255., 255.))) prob = cv2.calcBackProject([hsv], [0], self.hist, [0, 180], 1) cv2.imshow('prob_0',prob) prob &= mask cv2.imshow('prob',prob) term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 ) track_box,

问题 I am trying to convert an image back to greyscale after applying Sobel filtering on it. I have the following code: import numpy as np import matplotlib.pyplot as plt import cv2 image = cv2.imread("train.jpg") img = np.array(image, dtype=np.uint8) #convert to greyscale img_grey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #remove noise img_smooth = cv2.GaussianBlur(img_grey, (13,13), 0) sobely = cv2.Sobel(img_smooth,cv2.CV_64F,0,1,ksize=9) I want to convert the image sobely back to greyscale using

问题 I am doing some machine learning in OpenCV and i'm using Decision Trees . I am currently using OpenCV 3.0.0-rc1 . Whenever i attempt to train Decision Trees with my training data and labels, i get either terminate called after throwing an instance of 'std::bad_alloc' what(): std::bad_alloc or Segmentation fault Depending on what i put into setMaxDepth(); if the number is larger than 22, it's bad_alloc, else it's seg fault. Here's my source code: //import data Mat trainData=imread("/home

问题 I'm trying to build my application against tesseract, which i have installed through brew (working on mac os x). While i can compile my application without problem using g++ and pkg-config, i'm not sure how to do the same with cmake. I tried FIND_PACKAGE tesseract REQUIRED but it can't seem to find it. Does anyone have a sample CMakeLists.txt ? Appreciate the help. 回答1: It seems the only (or the easiest) way to use tesseract in your project with CMake is to download tesseract sources (from