Problem $1.$ Fade to Black and White Here the file namess you will use for the code are florida$-$keys$-800-480.$jpgDownload florida$-$keys$-800-480.$jpg

Grand$\_$Teton$-800-480.$jpg code in python

The animation$-$transition.py program discussed in class and posted on the

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 cut 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. 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$.$uint$8$ 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$.$uint$8$ 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$.$uint$8$ 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 $3$rd axis are repeated $3$ times. One can use the np$.$dstack$()$ function to stack arrays

on the $3$rd dimension, or the np$.$newaxis object, as in arr$[$:$,$:$,$ np$.$newaxis$],$ to create an array with a new

axis $($dimension$),$ or reshape. Look these up$.$

b$)$ Modify the image$\_$gen$()$ 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$.$

Insert the Python file into the h$7.$doc file.

No screenshot is needed.