Image-Stitching | OpenCV and Python program to stitch two input images | Computer Vision library
kandi X-RAY | Image-Stitching Summary
kandi X-RAY | Image-Stitching Summary
OpenCV and Python program to stitch two input images.
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Top functions reviewed by kandi - BETA
- Compute the homography of two images .
- Get the stitch of two images .
- Main function .
- equalize a histogram color
Image-Stitching Key Features
Image-Stitching Examples and Code Snippets
Community Discussions
Trending Discussions on Image-Stitching
QUESTION
For text detection, I split the entire image for better results (all those images with the same dimensions having overlapping) and generate its mask(Binary image) and merge those split images into one full image(with the dimension of the original image).
image: Full image split images masked binary image
now I used to merge all these images, but the overlapped image where the text not detected removes the white patch in the image full merged mask image.
In order to overcome this issue I came to know about the stitching image in OpenCV, hence I used this link for stitching imagehttps://www.pyimagesearch.com/2018/12/17/image-stitching-with-opencv-and-python/#pyi-pyimagesearch-plus-pricing-modal, but this code doesn't work for a binary image. Is it possible to stitch binary image with overlapping in OpenCV?
...ANSWER
Answered 2020-Nov-10 at 11:17Stitching in OpenCV python is only for panorama images(camera images) where it finds and matches the features in the image as you refer to this link:https://docs.opencv.org/master/d1/d46/group__stitching.html
if you want to get merge those image you can use it simply with PIL in python:https://pillow.readthedocs.io/en/stable/reference/Image.html#PIL.Image.Image.paste
merge those image with :image.paste(im, (x, y),mask=im) Where the mask is 255, the given image is copied as is. Where the mask is 0, the current value is preserved.
QUESTION
I need to stitch five video streams on the fly. The cameras recording the videos are mounted onto a rack side by side and will never change their relative position to one another. Homography matrices are therefore static.
I'm following the approach from this github repo:
Starting from the center image, you first stitch to the left, and then stitch the remaining images to the right.
The code from that repo works, but it is painfully slow. I've been able to dramatically improve its performance (factor 300), but it still takes 0.25 seconds to stitch a panorama of five images (on a 2015 Macbook Pro).
The slow part: Applying each result of cv2.warpPerspective(...) to the images stitched up to that point. I'm currently doing this by using the alpha channel and blending the two images, inspired by this SO answer. It is this blending that makes the stitching slow.
(Pseudo) code:
...ANSWER
Answered 2019-Jan-10 at 13:08Alpha channel is useful when your image has transparency, but here you manually add an alpha channel by converting. This channel could be used to store computation but I think you would lose performance. I suggest the following function for blend_transparent:
QUESTION
Using OpenCV in python, I am trying to stitch multiple images that are out of order. I have a functioning stitch method that stitches two images, given which one is on the left and right.
...ANSWER
Answered 2018-Jun-27 at 17:37For multiple images stitching available in random order you can try the following:
1)find feature in one image
2)try to match those features in all the images
3) the image for which you get maximum match with initial image select that and perform the stitching
4) now you have a new stitched image, and you can features in it and match them again in other frames and so on.
It would be time consuming but something in this direction can be thought.
QUESTION
I am trying to create a stitching algorithm. I have been successful in creating it with a few tweaks needed. The photos below are examples of my stitching program so far. I am able to provide it with an unordered list of image (so long as image is in flight path or side by side it will work regardless of their orientation to one another.
The issue is if the images are reversed some of the image doesn't make it into the final product. Here is the code for the actual stitching. Assume that finding keypoints, matching, and homography is done correctly.
By altering this code is there a way to centre the first image to the destination blank image and still stitch to it. Also, I got this code on stack overflow (Opencv Image Stitching or Panorama ) and am not fully sure how it works and would love if someone could explain it.
Thanks for any help in advance!
...ANSWER
Answered 2017-Jun-14 at 00:07It's normally easy to center an image; you simply create a bigger matrix padded with zeros (or whatever color you want), and define an ROI in the center with the same size of your image, and place it in there. However, you cannot in general do this with your two images. The problem is that if an image is shifted, or rotated, so that parts of it are outside your destination image bounds, then your returned warped image from warpPerspective is cut off at those bounds. What you need to do is create the padded image, insert the image that is not being warped wherever you like, and modify the transformation (homography, in this case) by adding in the translation to those pixels.
For example, if your centered image has it's top-left point at (400,500) in the padded image, then you need to add a translation of (400, 500) to your homography so the pixels get mapped to the correct space, and as long as your padded image is large enough, none of it will be cut off.
You will need to create a translational homography and compose it with your original homography to add the translation in. For example, suppose your anchor point for the non-warped image inside the padded image is at (x,y). Translation in an homography is given by the last two columns; if your homography is a 3x3 matrix H then (using normal mathematical indexing) H(1,3) is your translation in x and H(2,3) is the translation in y given by your homography. So we need to create a new identity homography H_t and add those translations in:
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Install Image-Stitching
You can use Image-Stitching like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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