What you would learn in Smile Detection with Deep Learning course?
In this class, we will develop an end-to-end application to identify smiles in pictures and videos.
To do this, we'll make use of deep learning and begin with the training of a convolutional neural network using the SMILES dataset, which includes smiles of people and faces not smiling. Once the network has been developed, we'll take the following steps to identify smiles in photos and videos:
We will make use of Haar cascades to identify faces in images.
Then, we will extract the face area from the image.
Then we'll send the face region onto the network to classify.
Then, we'll mark the image with the word "smiling" or "not smiling" by how the image is processed by the network.
This course was designed specifically for advanced Python programmers who know computer vision and deep learning.
When you finish this course at the end of this course, you'll be able to use a fully-functional smile detection program that you can implement in the projects you create.
What you'll receive:
If you purchase the course, you'll receive:
One hour of high-definition video tutorials
Source code, sample images, and videos that are used during the course
Access to the course for life
Priority assistance
What is covered in this class:
To give you a notion of what you'll be learning in this course, here are the topics we will be covering:
Content of the Course:
- Identify faces in images using Haar Cascades
- Learn to train a CNN to distinguish between smiles and not
- Use the smile detector on photographs from the real world
- Use the smile detector in videos
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