Computer Vision Task: Face Detection and Blurring

This task has been prepared for the Computer Vision Engineer Virtual Internship Program in Intern2Grow.

Objective

Your task is to build a program that can detect faces in an image using the Haar Cascade Classifier and then apply a Gaussian blur to the detected faces.

Task Breakdown

1. Face Detection: Import the necessary libraries. Load the Haar Cascade Classifier. Load the image. Use the detectMultiScale function of the classifier to detect faces in the image. Draw a rectangle around each detected face. Display the image with the detected faces. (or follow any similar steps that can lead to the same result)

2. Gaussian Blur: After detecting the faces, apply a Gaussian blur to each detected face. Display the image with the blurred faces.

3. Saving the Result: Finally, save the image with the blurred faces.

Deliverable

Submit a report detailing your approach, methodology, and results. Your report should include:

• An explanation of your steps in the face detection and blurring process.
• The libraries and tools you used and why you chose them.
• The results of your face detection and blurring process, including any challenges you faced and how you overcame them.

Also, submit your code files along with your report. Your code should be well-commented and easy to understand.