Face Detection Using Deep Learning by Code Warriors | OpenCV | DNN | Deep Learning
We are welcoming all of you on this tutorial.
Recently, I came across the website https://www.pyimagesearch.com/ which has some of the greatest tutorials on OpenCV.
While reading through its numerous articles, I found that OpenCV has its own Face Detection Neural Network with really high accuracy.
So I decided to work on a project using this Neural Network from OpenCV.
In this video I’ll discuss:
Where this “hidden” deep learning face detector lives in the OpenCV library
How you can perform face detection in images using OpenCV and deep learning
Project Link - https://github.com/mayank8200/Deep-Le...
Today’s tutorial is broken down into two parts.
In the first part we’ll discuss the origin of the more accurate OpenCV face detectors and where they live inside the OpenCV library.
From there I’ll demonstrate how you can perform face detection in images using OpenCV and deep learning.
However, what most OpenCV users do not know is that Rybnikov has included a more accurate, deep learning-based face detector included in the official release of OpenCV (although it can be a bit hard to find if you don’t know where to look).
The Caffe-based face detector can be found in the face_detector sub-directory of the https://github.com/opencv/opencv/tree...
When using OpenCV’s deep neural network module with Caffe models, you’ll need two sets of files:
The .prototxt file(s) which define the model architecture (i.e., the layers themselves)
The .caffemodel file which contains the weights for the actual layers
Both files are required when using models trained using Caffe for deep learning.
However, you’ll only find the prototxt files here in the GitHub repo.
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