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Face Detection Using Dlib and DNN in OpenCV

PROJECT


Face Detection Using Dlib and DNN in OpenCV

Face detection is a computer vision task that allows a program to detect a human face in a photo or video. Face detection can help embellish selfies and portraits or produce virtual avatars from a user's photo. In this project, we’ll learn to detect the faces in an image using dlib and OpenCV.

Face Detection Using Dlib and DNN in OpenCV

You will learn to:

Apply pre-trained model on an image for face detection

Use Resnet10-SDD-300x300 in OpenCV

Use HOG-based face detector from dlib

Detect and plot face boundaries in an image

Skills

Data Visualization

Data Manipulation

Machine Learning Fundamentals

Prerequisites

Basic understanding of Python

Basic understanding of data analysis

Basic understanding of data visualization

Technologies

Python

OpenCV

Project Description

Face detection is one of the most fundamental aspects of computer vision.

We’ll use:

Frontal face detector dlib: Dlib is a C++ toolbox for employing machine learning techniques to solve real-world problems. Despite being built in C++, it includes Python bindings executed in Python. The dlib frontal face detector extracts feature using Histogram of Oriented Gradients (HOG) and then processes using an SVM.

Caffe model with DNN from OpenCV: The Caffe model is based on the Single Shot-Multibox Detector (SSD) that uses the ResNet-10 architecture. It was added to OpenCV’s deep neural network module after version 3.3.

After we have worked with both, we’ll compare them to see which one performs better for different examples. Let’s get started!

Project Tasks

1

Introduction

Task 0: Getting Started

Task 1: Import Libraries

2

Face Detection Using OpenCV

Task 2: Download the Image

Task 3: Load the DNN Network

Task 4: Prepare the Image and Run the Network

Originally Task 5: Merged with Task 4

Task 5: Label and Visualize the Image

Task 6: Run Performance Test

3

Testing Your Solution - This category with 1 task will be deleted

Originally Task 8: Merged with Task 7 which is now Task 6

4

Face Detection Using dlib

Task 7: Prepare the Image and Run the Detector

Originally Task 10: Merged with Task 9 (now Task 7)

Task 8: Label the Image and Visualize the Result

Task 9: Run Performance Test

5

This will be deleted along with the merged task

Originally Task 13: Merged with Task 12 (now task 9))

Congratulations!

has successfully completed the Guided ProjectFace Detection Using Dlib and DNN in OpenCV

Relevant Courses

Use the following content to review prerequisites or explore specific concepts in detail.