- PYTHON OPENCV REGION OF INTEREST HOW TO
- PYTHON OPENCV REGION OF INTEREST FULL
- PYTHON OPENCV REGION OF INTEREST SOFTWARE
In the next line, we do an AND bitwise function between the original gray imageĪnd the region_of_interest_white, which is the image with the region of interest in white. The white represents a 1, so when we do an AND bitwise function, this part will The black represents a 0, so the blacked out part of the image willĪlways be 0. Remember that an AND function is only true when 2ġs are ANDed together. The reason we do this isīecause we then do a bitwise and function. The cv2.fillPoly() function allows us to fill the region of interestĪs a white color in the completely black image. We then create a variable, region_of_interest_white, which fills in the region of We then create a variable, blank, which blacks out the gray image. For our rightmost bottom coordinate, we have an x-coodinate of 750pxĪnd a y-coordinate of the height of the image. Top coordinate, we have an x-coordinate of 120px.
PYTHON OPENCV REGION OF INTEREST FULL
To see our original image with x and y axes, look at the image shown at the followingįor our leftmost coordinate on the bottom, we choose to start looking at 120pxįor the x-coordinate and the full height of the image for the y-coordinate.įor both the topmost coordinates, we choose a height of 220px.
Left bottom, to the left top, to the right top, to the right bottom to establish our coordinates. Look only 400 px to the left and to the right and maybe only 300px up.Īgain, in this example, we just hardcode in the coordinates starting from the Is located relative to the image that it takes and then from those coordinates look a certainĭistance to the left, right, up, and down to look for the lane markings. If you're actually building an autonomous system, you may want to find out where your camera In this example, we manually enter in the coordinates just for educational purposes, but You have to manually set the coordinates that you want to be a region of interest.įor an autonomous vehicle, you may think if you have to manually do it, how can itīe useful. Next, we create a variable, ROI, which contains all the coordinates for our region We then create a grayscale version of our image, which simplifies the image. Next, we want to get the height and width of our image, because they will help usĭefine our region of interest (in this case, the height). Next, we read in the image, which in this case is, Road-lanes.jpg We need this to black out the areas that are not in our region of interest. Region_of_interest_image= cv2.bitwise_and(image_gray, region_of_interest)Ĭv2.imshow('Region of Interest', region_of_interest_image)įirst, we import OpenCV using the line, import cv2. Region_of_interest= cv2.fillPoly(blank, ROI,255) Image_gray= cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
PYTHON OPENCV REGION OF INTEREST HOW TO
So let's see how to do this now how to establish a region of interest in Pythonīelow is the full code to establish the region of interest of the above image. Mostly down and to the immediate left and right for lane markings. You see that we have cut out the sky and much of the trees and vegetation.
PYTHON OPENCV REGION OF INTEREST SOFTWARE
Now we have a much more focused view of where our software should be looking for Interest so that we can narrow our focus to where the lanes are, so that we can stay centered.Īfter establishing a region of interest, our new image with a region of interest is We don't want to lookįor lanes in the vegetation or in the mountains or in the sky. There is a mountain in the distance and there is a sky above. Notice, though, there is vegetation on the side of the road, including
Now you see that there is a lot of things in this image but the most basic thing forĪn autonomous car is that it's a road that it drives on and it needs to detect the lanes, so that So, for this example, we are going to use the following image shown below. Not going to search the bathroom or living room when you know you didn't leave it there.Ī region of interest gives us a more narrow focus. You've only been to the kitchen and your bedroom, you'll only search the kitchen and bedroom. You can also think of it like searching for something. So establishing a region of interest in the image is important because itĪllows us to zoom into a certain region to look for something, which helps to narrow our focus. The lane will be somewhat to the left and right and near Or in all the way to the right or the left. Lanes with the camera centered maybe in the center of the car, you're not going to look for lanes in the sky So, in order to do this, we need to be able to identify lanes on the image. Let's say we want to establish autonomous features in the car like lane centering assistance. In this article, we show how to create a region of interest in an imageįirst, let's explain the concept of a region of interest.Ī region of interest is a place on an image where we want to search for something.įor example, let's say that we have a car and there is a camera centered in the middle How to Create a Region of Interest in an Image in Python using OpenCV
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