The edge-detection function ( detectEdges ) described in Chapter 7 andshown below returns a black and white image. Think of a similar way totransform color values so that the new image is still in its original colors butthe outlines within it are merely sharpened.def detectEdges(image, amount):""'Builds and returns a new image in which the edges ofthe argument image are highlighted and the colors arereduced to black and white."""def average(triple):(r, g, b) = triplereturn (r + g + b) // 3(0, 0, 0)(255, 255, 255)blackPixel =whitePixel =new = image.clone()for y in range(image.getHeight() - 1):for x in range(1, image.getWidth()):image.getPixel(x, y)image.getPixel(xoldPixel =1, y)leftPixelbottomPixel =image.getPixel(x, y + 1)oldLum = average(oldPixel)leftLum = average(leftPixel)bottomLum = average(bottomPixel)if abs(oldLum ·abs (oldLum - bottomLum) > amount:new.setPixel(x, y, blackPixel)leftLum) > amount or \else:new.setPixel(x, y, whitePixel)return newThen, define a function named sharpen that performs this operation.The function should expect an image and two integers as arguments. Oneinteger should represent the degree to which the image should besharpened. The other integer should represent the threshold used todetect edges.

The edge-detection function ( detectEdges ) described in Chapter 7 and shown below returns a black and white image. Think of a similar way to transform color values so that the new image is still in its original colors but the outlines within it are merely sharpened. def detectEdges(image, amount): ""Builds and returns a new image in which the edges of the argument image are highlighted and the colors are reduced to black and white.""" def average(triple): (r, g, b) return (r + g + b) // 3 triple blackPixel = (0, 0, 0)

The edge-detection function ( detectEdges ) described in Chapter 7 and shown below returns a black and white image. Think of a similar way to transform color values so that the new image is still in its original colors but the outlines within it are merely sharpened. def detectEdges(image, amount): ""Builds and returns a new image in which the edges of the argument image are highlighted and the colors are reduced to black and white.""" def average(triple): (r, g, b) return (r + g + b) // 3 triple blackPixel = (0, 0, 0)

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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The edge-detection function (detectEdges) described in Chapter 7 and shown below returns a black and white image. Think of a similar way to transform color values so that the new image is still in its original colors but the outlines within it are merely sharpened. def detectEdges(image, amount): """Builds and returns a new image in which the edges of the argument image are highlighted and the colors are reduced to black and white.""" def average(triple): (r, g, b) = triple return (r + g + b) // 3 blackPixel = (0, 0, 0) whitePixel = (255, 255, 255) new = image.clone() for y in range(image.getHeight() - 1): for x in range(1, image.getWidth()): oldPixel = image.getPixel(x, y) leftPixel = image.getPixel(x - 1, y) bottomPixel = image.getPixel(x, y + 1) oldLum = average(oldPixel) leftLum = average(leftPixel) bottomLum = average(bottomPixel) if abs(oldLum - leftLum) >…
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