OpenCV

问题 I am creating a stitching program using OpenCV and python and currently am stitching the images well and am now trying to blend them together. The ultimate goal will be to use a graph cut to better stitch them but for now I am just overlapping the images based on their found homography. Here is a photo of my current result when stitching two images. My goal is to determine the area of overlap and put it into a mask that I can apply to the top right image (that is the one on top in terms of

问题 I am creating a stitching program using OpenCV and python and currently am stitching the images well and am now trying to blend them together. The ultimate goal will be to use a graph cut to better stitch them but for now I am just overlapping the images based on their found homography. Here is a photo of my current result when stitching two images. My goal is to determine the area of overlap and put it into a mask that I can apply to the top right image (that is the one on top in terms of

问题 I am creating a stitching program using OpenCV and python and currently am stitching the images well and am now trying to blend them together. The ultimate goal will be to use a graph cut to better stitch them but for now I am just overlapping the images based on their found homography. Here is a photo of my current result when stitching two images. My goal is to determine the area of overlap and put it into a mask that I can apply to the top right image (that is the one on top in terms of

问题 I am creating a stitching program using OpenCV and python and currently am stitching the images well and am now trying to blend them together. The ultimate goal will be to use a graph cut to better stitch them but for now I am just overlapping the images based on their found homography. Here is a photo of my current result when stitching two images. My goal is to determine the area of overlap and put it into a mask that I can apply to the top right image (that is the one on top in terms of

问题 I am trying to segment the blood vessels in retinal images using Python and OpenCV. Here is the original image: Ideally I want all the blood vessels to be very visible like this (different image): Here is what I have tried so far. I took the green color channel of the image. img = cv2.imread('images/HealthyEyeFundus.jpg') b,g,r = cv2.split(img) Then I tried to create a matched filter by following this article and this is what the output image is: Then I tried doing max entropy thresholding:

问题 I am trying to segment the blood vessels in retinal images using Python and OpenCV. Here is the original image: Ideally I want all the blood vessels to be very visible like this (different image): Here is what I have tried so far. I took the green color channel of the image. img = cv2.imread('images/HealthyEyeFundus.jpg') b,g,r = cv2.split(img) Then I tried to create a matched filter by following this article and this is what the output image is: Then I tried doing max entropy thresholding:

问题 I wanted to work on a small project to challenge my computer vision and image processing skills. I came across a project where I want to remove the hidden marks from the image. Hidden here refers to the watermarks that are not easily visible in rgb space but when you convert into hsv or some other space the marks become visible. Here's one example: BGR SPACE: HSV SPACE: I've tried different ways but was able to implement a solution that would remove those watermarks from the image. I am

问题 I 'm having troubles trying to capture a live stream from my new GoPro Hero 4 camera and do some image processing on it using openCV. Here is my trial (nothing shows up on the created window import cv2 import argparse import time import datetime from goprohero import GoProHero ap = argparse.ArgumentParser() ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area size") args = vars(ap.parse_args()) camera = cv2.VideoCapture("http://10.5.5.9:8080/gp/gpControl/executep1

问题 I'm trying to match a slightly irregular shape to a database of shapes. For example, here the contour I'm trying to match: For more information, this is an outline of an HDMI connector, represented as a contour. It is slightly rough as this was taken with a phone while holding the HDMI. This is my database of connectors: HDMI: DVI: 5PinDIN: DB25: These are a lot clearer as these are contours gathered from connector images from the internet. For what I have tried: cv2.matchShapes() Since these

问题 I am new in OpenCV, and could not find normal tutorial for stereoCalibration on Python. If you have some samples, please share. I do single calibration for each of cameras, and i have next problem. The left one: The right one: PS: I'm doing Depth-map and by the metter of it, i received bad map. UPDATE: I have ported the C++ version from https://github.com/jayrambhia/Vision/blob/master/OpenCV/C%2B%2B/stereocalibrate.cpp Yeah, it has no error but it return only fully black images Ported cod: