template-matching

问题 Here is an example of a code that works perfectly: #include<iostream> #include<vector> template< class D, template< class D, class A > class C, class A = std::allocator< D > > void foo( C< D, A > *bar, C< D, A > *bas ) { std::cout << "Ok!" << std::endl; } int main( ) { std::vector< int > *sample1 = nullptr; std::vector< int > *sample2 = nullptr; foo( sample1, sample2 ); return( 0 ); } In the code below, however, the compiler is unable to match std::vector< int >* with nullptr for the second

问题 I had a problem where I need to search for a pattern (present as a numpy ndarray) within another image (also present as a numpy ndarray) and compute a template match (minimum difference position in the image). My question is... is there any in-built image that I can possibly use in the Python Imaging Library or Numpy or anything possible that can do this without me manually writing a function to do so??? Thank you.... 回答1: This is likely best done as an inverse convolution or correlation.

问题 Anybody know about the fastest method for calculating convolution? Unfortunately the matrix which I deal with is very large (500x500x200) and if I use convn in MATLAB it takes a long time (I have to iterate this calculation in a nested loop). So, I used convolution with FFT and it is faster now. But, I am still looking for a faster method. Any idea? 回答1: If your kernel is separable, the greatest speed gains will be realized by performing multiple sequential 1D convolutions. Steve Eddins of

问题 Anybody know about the fastest method for calculating convolution? Unfortunately the matrix which I deal with is very large (500x500x200) and if I use convn in MATLAB it takes a long time (I have to iterate this calculation in a nested loop). So, I used convolution with FFT and it is faster now. But, I am still looking for a faster method. Any idea? 回答1: If your kernel is separable, the greatest speed gains will be realized by performing multiple sequential 1D convolutions. Steve Eddins of

问题 I have a template image , with white background and black shape over it.I also have an image which have a similar shape but in different rotation and scale,also have some noise in image.Just like the pic as follow! I want to use a rotateRect to get a Rect which includes the template shape and use the template to find a rotateRect which includes the target sharp.I have known matchTemplate() is not good when object is rotated or scaled in scene.So I try to use matchShapes() function.But

问题 I am trying to implement real-time tracking using templates. I wish to update the template with every frame. The main modifications I have done are: 1) separated the template matching and minmaxLoc into separate modules namely, TplMatch() and minmax() functions, respectively. 2) Inside the track() function, the select_flag is kept always true so that new template is copied to 'myTemplate' with every iteration. 3) The last 3 lines of function track() are to update the template (roiImg). 4)

问题 I am a newbie in Image Processing and learning about Template Matching by getting some help from OpenCV documentation, but I didn't understand some lines of the code. Here is the code: import cv2 import numpy as np from matplotlib import pyplot as plt img_rgb = cv2.imread('mario.png') img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY) template = cv2.imread('coin.png', 0) w, h = template.shape[::-1] count = 0 res = cv2.matchTemplate(img_gray, template, cv2.TM_CCOEFF_NORMED) threshold = 0.8

问题 I have several scanned images I would like to compute with Python/Opencv. Each of these images (see an example below) contains n rows of coloured squares. Each of these squares have the same size. The goal is to crop each of these squares and to extract the data from it. I have found there a code which is able to extract squares from an image. Here is my code where I have used it : import numpy as np import cv2 from matplotlib import pyplot as plt def angle_cos(p0, p1, p2): import numpy as np

问题 I'm a beginner in matlab programming and i'm having some troubles with template matching. I have a few white boxes with a black border (link for pic below) along with some text and I want to extract all the boxes,and there's also one that has an X in it(it's a multiple choice answer). In the beginning I used normxcorr2 , but the problem is that due to the many white pixels of the template, I get allot of irrelevant templates like only white spaces. I was looking for an algorithm that does

问题 To all skimage and opencv gurus, given: Scene Image Template Image What is the best approach to find the cross in the scene image ? These are output from smoothing, and canny filters. Now, I tried all kinds of examples in skimage, and opencv template matching but the results are not satisfactory. My ideal solution will be rotation, translation invariant (scale invariant will be a bonus) . Is there a way to just convert to contour points and them do a registration point cloud ? Will that be