Answered step by step
Verified Expert Solution
Question
1 Approved Answer
animation-transition.py - https://pastebin.com/BzECEmDR florida-keys-800-480.jpg Grand_Teton-800-480.jpg: Problem 1. Fade to Black and White The animation-transition.py program discussed in class and posted on the Module 7 Canvas
animation-transition.py - https://pastebin.com/BzECEmDR
florida-keys-800-480.jpg
Grand_Teton-800-480.jpg:
Problem 1. Fade to Black and White The animation-transition.py program discussed in class and posted on the Module 7 Canvas page animates a smooth transition from one image to another and back. Modify that program so that it displays an animation of a transition from the original color image to its black-and-white (B/W) version and back to original. An animation video of that transition is posted on the homework 7 page to give you the idea of how it should look like CAUTION: To get any credit do not corners, such as calling np.imread with a grayscale option, or generating a B/W version of the color image and then using that as image 2 with no changes to the code. It's silly, but students do this sort of thing and hope to get a good grade. Follow the requirements or expect a low grade Details a) Write a function convert bw(img) that takes an image ndarray with shape (height,width,3) and dtype np.uint8 and returns the B/W (actually, grayscale) version of that image, also with shape (height,width,3) and the same dtype The color image pixel is represented by a shape (3.) array of np.uint8 integers: [red, green, blue], where these numbers are in the range 0, 1, 2,..., 255. A color with equal values for red, green, and blue is a grayscale color. We use a trivial conversion of a pixel from [r,g,b] to B/W: the B/W pixel color is the average of the r, g b values. So, for each pixel [r.g,b] in the original color image we compute the B/W image pixel [a, a, a where a is the np.uint8 average of the red, green, and blue values. Understand that we represent a B/W image with pixels that have all values for its colors (i.e. red, green, and blue) equal to the average of red, green, and blue. It's worth repeating that to avoid confusion. Hence, the B/W image will have the same shape (height, width, 3) as the original color image The convert bw function MUST use broadcasting and numpy's functions to compute the B/W image. Do NOT use nested for loops to compute the average for each individual pixel. If any loop is used in this function, no credit is given for part a) HINTS: the tricky part is converting from a (h,w) B/W array to a (h,w,3) array, where in the latter all elements along the 3d axis are repeated 3 times. One can use the np.dstack0 function to stack arrays on the 3"d dimension, or the np.newaxis object, as in arrl:,:, np.newaxis], to create an array with a new axis (dimension), or reshape. Look these up b) Modify the image gen0 function so that it takes just one image file name and the steps as parameters and then it uses the B/W version of the original image to yield ndarray objects that are intermediate images between the color version and the B/W version, just like in the original py file. c) Modify the remainder of the program accordingly in order to animate image transition from color to B/W Problem 1. Fade to Black and White The animation-transition.py program discussed in class and posted on the Module 7 Canvas page animates a smooth transition from one image to another and back. Modify that program so that it displays an animation of a transition from the original color image to its black-and-white (B/W) version and back to original. An animation video of that transition is posted on the homework 7 page to give you the idea of how it should look like CAUTION: To get any credit do not corners, such as calling np.imread with a grayscale option, or generating a B/W version of the color image and then using that as image 2 with no changes to the code. It's silly, but students do this sort of thing and hope to get a good grade. Follow the requirements or expect a low grade Details a) Write a function convert bw(img) that takes an image ndarray with shape (height,width,3) and dtype np.uint8 and returns the B/W (actually, grayscale) version of that image, also with shape (height,width,3) and the same dtype The color image pixel is represented by a shape (3.) array of np.uint8 integers: [red, green, blue], where these numbers are in the range 0, 1, 2,..., 255. A color with equal values for red, green, and blue is a grayscale color. We use a trivial conversion of a pixel from [r,g,b] to B/W: the B/W pixel color is the average of the r, g b values. So, for each pixel [r.g,b] in the original color image we compute the B/W image pixel [a, a, a where a is the np.uint8 average of the red, green, and blue values. Understand that we represent a B/W image with pixels that have all values for its colors (i.e. red, green, and blue) equal to the average of red, green, and blue. It's worth repeating that to avoid confusion. Hence, the B/W image will have the same shape (height, width, 3) as the original color image The convert bw function MUST use broadcasting and numpy's functions to compute the B/W image. Do NOT use nested for loops to compute the average for each individual pixel. If any loop is used in this function, no credit is given for part a) HINTS: the tricky part is converting from a (h,w) B/W array to a (h,w,3) array, where in the latter all elements along the 3d axis are repeated 3 times. One can use the np.dstack0 function to stack arrays on the 3"d dimension, or the np.newaxis object, as in arrl:,:, np.newaxis], to create an array with a new axis (dimension), or reshape. Look these up b) Modify the image gen0 function so that it takes just one image file name and the steps as parameters and then it uses the B/W version of the original image to yield ndarray objects that are intermediate images between the color version and the B/W version, just like in the original py file. c) Modify the remainder of the program accordingly in order to animate image transition from color to B/WStep by Step Solution
There are 3 Steps involved in it
Step: 1
Get Instant Access to Expert-Tailored Solutions
See step-by-step solutions with expert insights and AI powered tools for academic success
Step: 2
Step: 3
Ace Your Homework with AI
Get the answers you need in no time with our AI-driven, step-by-step assistance
Get Started