image-processing

问题 This question already has answers here : How to get the cells of a sudoku grid with OpenCV? (3 answers) Closed 8 days ago . i have converted sudoku image into sudoku grid using opencv now i want to extract each box from image what is best way to do this? as per my knowledge i am trying to find intersection points of lines to find corner of each box class SudokuSolverPlay: def __init__(self, image): def __preProcess(self, img): """return grayscale image""" def __maskSudoku(self, img): ""

问题 This question already has answers here : How to get the cells of a sudoku grid with OpenCV? (3 answers) Closed 8 days ago . i have converted sudoku image into sudoku grid using opencv now i want to extract each box from image what is best way to do this? as per my knowledge i am trying to find intersection points of lines to find corner of each box class SudokuSolverPlay: def __init__(self, image): def __preProcess(self, img): """return grayscale image""" def __maskSudoku(self, img): ""

问题 The AVIF image format looks to be a really promising format. How can you compile and use it on a web server? Mine specifically is Ubuntu 18.04/Nginx but I'm looking for a gist of how to compile and start converting images? 回答1: AVIF seems to be a new format, and not much info could be found. But, let's go right away into the findings, that were there: From [1] I found a cook book how to serve those on Nginx: http { # ... Omitted. map $http_accept $ai { "~avif" "a"; "~webp" "w"; default ""; }

问题 I have implemented a cropping algorithm on my solution that works pretty good. The problem is when the image is tilted, the crop will work but it will have background space showing as the images will show. Cropping flow: First step: Second step: Final result: I have searched/tried multiple solutions but could not get a decent result or I'm not thinking the right way. The expected result is this: EDIT [FINAL RESULT]: import cv2 import numpy as np def order_corner_points(corners): # Separate

问题 I'm trying to remove the background of an image that im trying to train a neural network with. I've had little luck using the method described here (How do I remove the background from this kind of image?), but I have been able to use the Canny Edge Detector to get a semi-good "boundary" of the object in my image. Heres my code I'm running import cv2 as cv, sys, numpy as np, PIL.Image, matplotlib.pylab as plt # read command-line arguments filename = '/Users/colew/Desktop/Good_Cups_Frames

问题 I'm trying to remove the background of an image that im trying to train a neural network with. I've had little luck using the method described here (How do I remove the background from this kind of image?), but I have been able to use the Canny Edge Detector to get a semi-good "boundary" of the object in my image. Heres my code I'm running import cv2 as cv, sys, numpy as np, PIL.Image, matplotlib.pylab as plt # read command-line arguments filename = '/Users/colew/Desktop/Good_Cups_Frames

问题 I'm trying to remove the background of an image that im trying to train a neural network with. I've had little luck using the method described here (How do I remove the background from this kind of image?), but I have been able to use the Canny Edge Detector to get a semi-good "boundary" of the object in my image. Heres my code I'm running import cv2 as cv, sys, numpy as np, PIL.Image, matplotlib.pylab as plt # read command-line arguments filename = '/Users/colew/Desktop/Good_Cups_Frames

问题 I'm trying to remove the background of an image that im trying to train a neural network with. I've had little luck using the method described here (How do I remove the background from this kind of image?), but I have been able to use the Canny Edge Detector to get a semi-good "boundary" of the object in my image. Heres my code I'm running import cv2 as cv, sys, numpy as np, PIL.Image, matplotlib.pylab as plt # read command-line arguments filename = '/Users/colew/Desktop/Good_Cups_Frames

问题 I'm trying to remove the background of an image that im trying to train a neural network with. I've had little luck using the method described here (How do I remove the background from this kind of image?), but I have been able to use the Canny Edge Detector to get a semi-good "boundary" of the object in my image. Heres my code I'm running import cv2 as cv, sys, numpy as np, PIL.Image, matplotlib.pylab as plt # read command-line arguments filename = '/Users/colew/Desktop/Good_Cups_Frames

问题 Whats the real conversion formula for this because I found so many ways on how to convert I don't know which one is real From wikipedia: From microsoft https://msdn.microsoft.com/en-us/library/ff635643.aspx : and microsoft is the same with this conversion site http://www.equasys.de/colorconversion.html: Can anybody explain the difference of the formula? 回答1: If it still actual they are almost the same. Differences are what value ranges you'll get in the result. From Wiki's matrix (R',G',B' =