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WebSep 25, 2024 · We then load the image, we get the threshold of the image to have a black and white image, where the background is white and all the shapes are black. From the black and white image we find the contours, so the boundaries of all the shapes. img = cv2.imread("shapes.jpg", cv2.IMREAD_GRAYSCALE) _, threshold = cv2.threshold(img, 240, … WebMay 21, 2016 · pradeep, that gives a binary image where it's true, white, 1 where the red channel of im is less than 10, and false, black, 0 elsewhere. By the way, the first 5 lines inside Matt's for loop, along with the call to bwboundaries, can be eliminated if you simply pass 'BoundingBox' into regionprops(), which will give simpler code. WebFeb 8, 2016 · Notice how our image has been binarized — the shapes appear as a white foreground against a black background.. Lastly, we find contours in our binary image, handle grabbing the correct tuple value from cv2.findContours based on our OpenCV version, and finally initialize our ShapeDetector (Lines 27-30).. The last step is to identify each of the … new image towing and recovery ga