I have used cv2.matchTemplate() to identify target objects in an image. Now I want to convert below image into binary image(black and white) in such a way that detected target object(white frames) should be in white color and rest of the objects in image should be in black color.
This is how I want an output(Binary output illustrative). Wherever white frames (in input image) is there, image area should be white and rest are in black color.
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I have for example Example image where the object of interest is white and the rest of the image is black.
Is there any way to crop the image in python so that all that is left is a rectangle that has the white mask in it?
The end result should look something like this: Cropped image
I have some cropped images and i also applied otsu thresholding on it. Now, i want to convert white pixels that are in the background into black pixels
Need solution to solve this problem.
So I have two images, one is a white image with a blurred spot and other is a image of a street(taken from KITTI dataset). I want to blend both the white image with blurred spot and street image such that the whiteness doesnt appear while blending.\
In the first image below, you can see a translucent gray spot. This I achieved by making a copy of the street image and then drawing a circle on it using cv2.circle function. This i blended it back with the original image and controlled the transparency of the circle.
In place of the circular spot, I want the blurred spot in the white image to appear with transparency. How can this be achieved?
When i do normal blending the white shade also appears. I tried converting into RGBA image and then blending but didnt work. Any idea how this could be achieved?
I am trying to do lung extraction from CT images. I would like to remove the background and keep only the lungs (the yellow color background must change to blue-ish color and lungs must have unique color). How can I do that?
I used semantic segmentation to color code the different elements in an image shown below.
In Python, I want to crop the original image into many small images based on the colors of the second image, so that the sofa becomes one cropped part, the lamp becomes one.etc. The overlap of the pillows on the sofa can be ignored. Say I have a 3D array of an image, I want to separate that array into the individual colored sections, and apply the coordinate of those elements in cropping the original image. How should I achieve this?
You can do it like this:
find the number of unique colours in the segmented image - see here
iterate over that list of colours making that colour white and everything else black, then findContours() to get the bounding box and save the contents of that bounding box as a PNG.