ExamplesIf the input is:13050130the output should be:(80, 0, 80)Note: You will always have at least one zero in the resulting tuple. If you had (130, 50, 130) you will have (80, 0, 80). If you had (100,5, 100) you will have (95, 0, 95).Note: This page converts the RGB values into colors, so you can visualize the values as colors.414136.2652726.qx3zqy7LABACTIVITY3.18.1: LAB: Different shades of grey1 # Define your function here.23 if name == '__main__":45main.py# Type your code here. Your code must call the function.0/8Load default template... IntroductionComputers represent color by combining the sub-colors red, green, and blue (RGB). Each sub-color's value can range from 0 to 255. Thus,(255, 0, 0) is bright red,(130, 0, 130) is a medium purple,(0, 0, 0) is black,●●• (255, 255, 255) is white, and• (40, 40, 40) is a dark grey.Equal amounts of red, green, blue result in different shades of grey. Note that (130, 50, 130) is a faded purple, due to the (50, 50, 50)grey part.Given integer values for red, green, and blue, you will subtract the grey from each value and report the results.InstructionsThe functionWrite a function subtract_grey() that takes as input a tuple with three integer values. These values represent the sub-colors red, green,and blue (RGB).The function should return a new tuple that results from decrementing all values by the smallest value, thus removing the grey. You need touse the comparison operators <> ==, and to cover all the cases i.e. if only one is the min, if two numbers are equal and if they are all equalThe main programIn your main program, ask the user for 3 numbers and create the tuple that you will use as an argument into the subtract_grey()function.In your main program, print the result of calling the subtract_grey () function.

Here I have taken input from the user and then created a tuple from it. Then, I have called the…

Examples If the input is: 130 50 130 the output should be: (80, 0, 80) Note: You will always have at least one zero in the resulting tuple. If you had (130, 50, 130) you will have (80, 0, 80). If you had (100, 5, 100) you will have (95, 0, 95). Note: This page converts the RGB values into colors, so you can visualize the values as colors. 414136.2652726.qx3zqy7 LAB ACTIVITY 3.18.1: LAB: Different shades of grey 1 # Define your function here. 3 if _name__ == '____main__': 4 5 main.py # Type your code here. Your code must call the function. 0/8 Load default template...

Examples If the input is: 130 50 130 the output should be: (80, 0, 80) Note: You will always have at least one zero in the resulting tuple. If you had (130, 50, 130) you will have (80, 0, 80). If you had (100, 5, 100) you will have (95, 0, 95). Note: This page converts the RGB values into colors, so you can visualize the values as colors. 414136.2652726.qx3zqy7 LAB ACTIVITY 3.18.1: LAB: Different shades of grey 1 # Define your function here. 3 if _name == 'main': 4 5 main.py # Type your code here. Your code must call the function. 0/8 Load default template...

Systems Architecture

7th Edition

ISBN:9781305080195

Author:Stephen D. Burd

Publisher:Stephen D. Burd

Chapter7: Input/output Technology

Section: Chapter Questions

Problem 27VE

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Create empty images for Ix, Iy, Ixx, Iyy, and Ixy (all the same dimensions as your original image) Loop through pixels of image and fill in values for Ix, Iy, Ixx, Iyy, and Ixy (ignore the edges when you set up the range of your loops) Create empty image to hold "cornerness" values Loop through pixels of image Access the a neighborhood surrounding each pixel (start with a 3x3, you can expand it later if you'd like) Sum up all the Ixx, Iyy, and Ixy values in this neighborhood Compute the determinant of the M matrix Compute the trace of the M matrix Compute the "cornerness" value for the center pixel - store in the "cornerness" image find max cornerness value in imageset threshold = 0.01(max C value) loop through pixels. if(C at pixel) > threshold: cv2.circle(image(X,Y),size(b,g,r) - 1) Do may not make use of any existing functions/code that extract features. Use opencv and python. Also don't use sobel.
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See code in attached image.Please explain what this code is doing / what is happening.
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ST_MapAlgebra has the capability to work with: One pixel at a time Neighborhoods of pixels Both a and b None of the above
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