$5\mathrm{.}3$ Final Final Project Part II Download the OOO$\_$BLUUUE.zip file from the assignment page.

UNZIP IT BEFORE YOU UPLOAD IT TO YOUR GOOGLE DRIVE!!

Make sure to upload the FOLDER to your drive and not just the individual files

The previous code showed a method for identifying red pixels in an image.

For the final section of the project, modify the code below to:

$1.$ Read all of the images in the folder

$2.$ Outline all BLUE objects in the image

$3.$ Saves all analyzed images in the working directory folder

Common HSV Color Map:

Hue $($H$)$: $0-179($Represents color position on the color wheel$)$

Red: $0-10$

Yellow: $20-30$

Green: $60-70$

Cyan: $90-100$

Blue: $120-130$

Magenta: $150-160$

Saturation $($S$)$: $0-255($Represents color intensity$/$purity$)$

$0$: Grayscale

$255$: Full color intensity

Va

Correlation Coefficient $|$ Types, Formulas & Examples

NumPy, SciPy, and pandas: Correlation With Python

Visualizing statistical relationships

Estimating Regression Fits

Regression Line Object

The seaborn.objects Interface

Create a function to read each column of Atmosphere Temperature, Soil Temperature, Atmosphere Humidity and Soil Humidity using the $.$values method from the numpy library.

Pass the $.$values to a second function that will calculate and display the correlation coefficient of the two highest correlation values to the console. Choose any correlation method you

For the first section of this project, you will use the csv library to read Atmosphere Temperature, Soil Temperature, Atmosphere Humidity and Soil Humidity for Plant Data.csv$.$ Don't forget to close your file at the end!

Create a function to read each variable into a dictionary using the csv$.$DictReader$()$ function

Inside of that same function, use a for loop to append each of the value pairs for each category to an empty list

Pass these lists to another function that will calculate the averages if the values in each list $($Hint: Make sure your data is the correct data type$)$

Use the function to return these averages to the main$().$ Display the $4$ average values inside main$()$ with $2$ digit precision.