image-processing

问题 H = K[R|t] where H (3*3) is homographic matrix, R is Rotation matrix, K is matrix of camera's intrinsic parameters and t is translation vector. I have calculated K using chess board pattern as follows ret, K, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, chess_gray.shape[::-1],None,None) Homograpy matrix H is calculated as pts_src = np.float32(pts_src) pts_dst = np.float32(pts_dst) H, status = cv2.findHomography(pts_src, pts_dst) How to decompose R and t from H and K using

问题 I have an image similar to the following. I want to separate two numbers 7 and 4 as shown in the image, in that I want to have a bounding box for each of these two objects. How could I do this with OpenCV? I have no idea, how could I do this and was thinking if there is some way by using Sobel operator. The only thing that I tired was getting the Sobel. s = cv2.Sobel(img, cv2.CV_64F,1,0,ksize=5) but have no idea on how to proceed from here. 回答1: To segment and detect figures in an image, the

问题 I have an image similar to the following. I want to separate two numbers 7 and 4 as shown in the image, in that I want to have a bounding box for each of these two objects. How could I do this with OpenCV? I have no idea, how could I do this and was thinking if there is some way by using Sobel operator. The only thing that I tired was getting the Sobel. s = cv2.Sobel(img, cv2.CV_64F,1,0,ksize=5) but have no idea on how to proceed from here. 回答1: To segment and detect figures in an image, the

问题 Referring to the following link Viola & Jones Face Detection The above link contains the calculation regarding the number of haar features corresponding to different templates(below is excerpt from the link). I am not getting how those(43200,27600,43200,27600,20736) exact calculations are made.Can somebody explain that to me in an easy way? 回答1: To understand, have a look at the algorithm #1. For the first pattern (a) , the following two lines (5 and 6 in the article) gives the explanations

问题 Referring to the following link Viola & Jones Face Detection The above link contains the calculation regarding the number of haar features corresponding to different templates(below is excerpt from the link). I am not getting how those(43200,27600,43200,27600,20736) exact calculations are made.Can somebody explain that to me in an easy way? 回答1: To understand, have a look at the algorithm #1. For the first pattern (a) , the following two lines (5 and 6 in the article) gives the explanations

问题 Referring to the following link Viola & Jones Face Detection The above link contains the calculation regarding the number of haar features corresponding to different templates(below is excerpt from the link). I am not getting how those(43200,27600,43200,27600,20736) exact calculations are made.Can somebody explain that to me in an easy way? 回答1: To understand, have a look at the algorithm #1. For the first pattern (a) , the following two lines (5 and 6 in the article) gives the explanations

问题 I have these images For which I want to remove the text in the background. Only the captcha characters should remain(i.e K6PwKA, YabVzu). The task is to identify these characters later using tesseract. This is what I have tried, but it isn't giving much good accuracy. import cv2 import pytesseract pytesseract.pytesseract.tesseract_cmd = r"C:\Users\HPO2KOR\AppData\Local\Tesseract-OCR\tesseract.exe" img = cv2.imread("untitled.png") gray_image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) gray

问题 How can I select question blocks in a jpg file with questions in Python code? The codes below select texts. I want to select question blocks with their choices. import cv2 image = cv2.imread('test2.jpg') gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) blur = cv2.GaussianBlur(gray, (9,9), 0) thresh = cv2.adaptiveThreshold(blur,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV,11,30) kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9,9)) dilate = cv2.dilate(thresh, kernel, iterations

问题 This is my code to save web_cam streaming. It is working but the problem with output video file. import numpy as np import cv2 cap = cv2.VideoCapture(0) # Define the codec and create VideoWriter object #fourcc = cv2.cv.CV_FOURCC(*'DIVX') #out = cv2.VideoWriter('output.avi',fourcc, 20.0, (640,480)) out = cv2.VideoWriter('output.avi', -1, 20.0, (640,480)) while(cap.isOpened()): ret, frame = cap.read() if ret==True: frame = cv2.flip(frame,0) # write the flipped frame out.write(frame) cv2.imshow(

问题 I have some raw .IMG format files which I'm converting to .jpg using ImageMagick to apply a CNN Classifier. The converted images, however have a black vertical line splitting the image into two. The part on the left side of the line should have actually been on the right side of the right part of the image. I've posted a sample image: I used the command magick convert input_filename.IMG output_filename.jpg Raw .IMG File Here is how the image is supposed to look (converted manually using numpy